system

Abstract

We provide the system. [Solution] A means of obtaining a user's personal information and preference information by operating a terminal that provides an interface for inputting user information, A means for sending the acquired user information to a server and creating a user profile, A means of collecting relevant data from external sources based on user preference information and analyzing it, A means of generating recommendations tailored to user preferences using generative AI, A means of presenting recommendations to users and providing links to external sites, A means of obtaining user feedback and updating the AI ​​model, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, as travel plans and entertainment selections have become more diverse and complex, users need to spend a lot of time and effort to find the most suitable options for themselves from a vast amount of information. In particular, in travel planning, tasks such as selecting a destination, checking transportation means, and making reservations at restaurants need to be carried out on different platforms respectively, which is very time-consuming. Also, in entertainment, it is not easy to find works that suit one's preferences from multiple content distribution services with which one has contracts. There is a demand for providing a system that can solve these problems and enable users to enjoy travel and entertainment more efficiently and effectively..

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides an interface for inputting user information and uses a terminal to acquire the user's personal information and preference information. The acquired information is sent to a server to create a user profile, thereby identifying the user's interests and preferences. Furthermore, based on the user's preference information, information on relevant public wireless communication networks, restaurants, and video streaming service content for travel destinations is collected from external sources and analyzed using a generative AI. Based on the results of this analysis, recommendations tailored to the user's preferences are generated and presented on the terminal. The presented information also includes links to external sites, allowing users to easily make reservations or view content. Furthermore, the AI ​​model can be updated based on feedback obtained from the user to improve the accuracy of recommendations. In this way, the present invention provides a system that enables users to quickly and effectively make optimal choices in travel and entertainment.

[0006] "User information" refers to users' personal information and preferences, and is data used to generate travel and entertainment options.

[0007] A "device" refers to a device used by users to input information or receive recommendations, and primarily includes smartphones and tablets.

[0008] A "server" is a computer system that receives user information, collects and analyzes data, generates recommendations, and sends the results to the terminal.

[0009] A "profile" is a dataset created based on a user's personal information and preferences, and serves as the foundation for improving the accuracy of recommendations.

[0010] "Generative AI" is an artificial intelligence technology that automatically generates appropriate recommendations based on the user's profile.

[0011] "Recommendation" refers to the suggested travel destinations and entertainment content options based on the user's interests and preferences.

[0012] "Feedback" refers to the opinions and impressions provided by users, and is information collected to help improve the system and enhance the accuracy of recommendations. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

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

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

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

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

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

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

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

[0021] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0034] A system for carrying out the present invention includes a terminal that provides an interface for inputting user information, a server that receives and analyzes the acquired information, and a communication means for presenting the results to the user.

[0035] Users launch the application using a smartphone or tablet and input personal information, travel destinations, preferred entertainment categories, and other details through the interface. The device immediately transmits the information entered by the user to the server. The server receives this information and creates a user profile in its database. This profile reflects the user's preferences and interests and serves as foundational data necessary for future recommendation generation.

[0036] Next, the server collects relevant information based on the user's profile information through the internet and APIs of partner services. This includes information on tourist attractions and public Wi-Fi in travel destinations, restaurant reservation status, and even content information from video streaming services. The server analyzes this information and uses AI to create recommendations tailored to the user's preferences.

[0037] The generated recommendations are returned to the device and presented to the user in a visually easy-to-understand format. Users can use this information to plan their travel schedules or select movies and anime. Furthermore, the device provides links to external websites for the user's chosen options, supporting them in immediately starting reservations or viewing.

[0038] For example, if a user is planning a trip to Japan and wants to visit Kyoto, the server can recommend popular tourist spots in Kyoto, the best time to visit, and even highly-rated Japanese restaurants in Kyoto. Similarly, video streaming services can suggest documentaries and films related to Japanese culture that the user might find interesting.

[0039] Thus, the system according to the present invention makes it possible to streamline and enhance users' travel and entertainment experiences. By combining the analytical capabilities of the server with the power of generative AI to provide accurate recommendations, users are freed from cumbersome information searches and can enjoy a richer experience.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user launches the application on their device and enters personal information, travel destination, and preferred entertainment categories on the interface. The device retrieves this information and prepares to send it to the server.

[0043] Step 2:

[0044] The terminal sends the information entered by the user to the server. The server receives this information and creates a user profile in its database. This profile is a database entry that reflects the user's preferences and interests.

[0045] Step 3:

[0046] The server accesses external information sources to collect relevant information based on the user profile. Through API calls, it retrieves tourist information for travel destinations, restaurant reservation status, and content information for video streaming services. The results are then temporarily stored.

[0047] Step 4:

[0048] The server analyzes the collected information and uses generative AI to generate recommendations tailored to the user's preferences. The analysis includes a process of comparing user profile data with collected external information.

[0049] Step 5:

[0050] The device receives recommendations from the server and presents them to the user. The recommendations are formatted in a visually easy-to-understand format and include itineraries, sightseeing spots, and available content.

[0051] Step 6:

[0052] Users view the presented recommendations and select travel destinations or content that interest them. Based on the user's selection, the device provides links to external sites and assists with booking or viewing procedures.

[0053] Step 7:

[0054] After using a travel experience or content, users enter feedback via their device. The device then prepares to send this feedback to the server.

[0055] Step 8:

[0056] The server analyzes the feedback received and updates the AI ​​model to improve the accuracy of future recommendations. This data will be used to generate recommendations in the future.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] Existing information provision systems struggle to efficiently collect and provide personalized information tailored to users' diverse preferences and interests. Furthermore, there is a need to provide users with timely and accurate feedback on the information they desire, thereby improving convenience. Additionally, a mechanism is required to continuously improve the quality of the recommended information provided.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes means for creating a user profile, means for collecting and analyzing relevant information data based on the user's preferences, and means for generating recommendation information tailored to the user's preferences using generative artificial intelligence. This makes it possible to provide information tailored to the user's individual preferences very quickly and accurately, and furthermore, to realize a high-quality personalized experience by continuously improving the artificial intelligence model based on user evaluations.

[0062] "User information" refers to data that includes the user's personally identifiable information and preference information.

[0063] A "display device" is an electronic device used to provide information to users visually.

[0064] A "processing device" is a computer or server used to receive, analyze, and store data.

[0065] A "user profile" is recorded data that reflects a user's individual hobbies and interests.

[0066] "Information data" refers to all collectible information about people and things.

[0067] "External information resources" refer to information sources outside the system, including the internet and other data provision services.

[0068] "Generative artificial intelligence" is a technology that uses computer programs to automatically mimic human intellectual work.

[0069] "Recommended information" refers to suggestions and content generated based on user preferences.

[0070] A "path" is a link or connection that allows a user to reach the information or service they are looking for.

[0071] "Rating" refers to feedback or opinions from users regarding the information or services they receive.

[0072] An "artificial intelligence model" is a structure that uses machine learning algorithms to analyze and learn information.

[0073] This invention is a system that provides personalized recommendations based on user information, and is realized through the collaboration of the user, terminal, and server. The user launches an application using an information terminal such as a smartphone or tablet. This application provides an interface for the user to input personal information and preferences. The user inputs, for example, travel destinations or entertainment categories of interest. The terminal immediately transmits the entered information to the server. This transmission ensures secure communication using the HTTPS protocol.

[0074] The server uses a database system to store received information and create user profiles. For example, database software such as MySQL® can be used. Next, the server uses a generative AI model to collect information from external information resources. The collected data is then analyzed using libraries such as Scikit-learn and TENSORFLOW®, which run in a Python environment.

[0075] The server generates and sends recommendation information to the device based on the user's preferences. This recommendation information includes tourist attractions at the travel destination, suitable times to visit, restaurant reservation availability, and content from video services. The device presents the information to the user in a visually easy-to-understand manner and, if necessary, provides a route to external information resources.

[0076] As a concrete example, consider a case where a user is planning a trip to Japan and is particularly interested in Kyoto. Based on this information, the server can create and present a list of Kyoto tourist spots, highly-rated Japanese restaurants, and even movies related to Japanese culture. An example of a prompt used might be, "Please suggest tourist spots that the user might be interested in."

[0077] This system enables the creation of an excellent user experience tailored to individual needs by providing users with information that is neither too much nor too little.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] Users launch an application on their smartphone or tablet and enter personal and preference information through the interface. This information includes travel destinations and entertainment preferences. This information is formatted by the device and prepared for the next processing step. The entered information is then sent directly to the server and used as foundational data to understand the user's needs.

[0081] Step 2:

[0082] The terminal sends data entered by the user to the server using the HTTPS protocol. This input consists of the user's personal and preference data, which is sent to the server. This data reaches the server securely and is stored in a database. The output is then prepared as stored user data for use in subsequent processing.

[0083] Step 3:

[0084] The server creates a user profile in the database based on the received user information. During this profile creation process, the data is structured to reflect the user's personality and interests. The input is the stored user data, and the output is the constructed profile information. This profile is used for further analysis of the user's needs and for generating recommendations.

[0085] Step 4:

[0086] The server collects relevant information from external sources based on the user profile. This process utilizes the internet and various APIs to obtain data on tourist attractions, restaurants, and video content. The server uses the profile as input and obtains relevant information as output. This information is then prepared for further advanced analysis using generative AI.

[0087] Step 5:

[0088] The server analyzes the collected data using generative AI to generate recommendations tailored to the user's preferences. Specifically, it runs machine learning models using Python and libraries such as Scikit-learn and TensorFlow to identify the most relevant information for the user. The input consists of external information and the user profile, and the output is specific recommendations. These recommendations are then formatted for presentation to the user.

[0089] Step 6:

[0090] The server sends generated recommendations to the device. The device receives this information and presents it to the user in a visually easy-to-understand format. The input here is the recommended information generated by the server, and the output is the on-screen display to the user. Furthermore, the device provides routes to external sites as needed, supporting the user in taking immediate action.

[0091] (Application Example 1)

[0092] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0093] In today's world, users find it difficult to select content and services that match their preferences and needs from a vast amount of information. Furthermore, as user preferences diversify, there is a need for technology that can efficiently provide individually tailored recommendations. To solve this problem, a system is needed that appropriately utilizes users' personal data and provides information quickly and accurately based on that data.

[0094] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0095] In this invention, the server includes means for operating a device that provides an interface for inputting user information to acquire the user's personal data and preference data; means for transmitting the acquired user information to a data processing device and generating a user profile; and means for collecting relevant data from external sources based on the user's preference data and analyzing it. This makes it possible for users to easily select content that suits their interests.

[0096] "User information" refers to personal data and preference data obtained by users through their devices.

[0097] An "interface" is a means of interaction between a user and a device for inputting user information.

[0098] "Device" refers to electronic equipment used for inputting and displaying user information.

[0099] A "data processing device" is a device that receives user information and generates a user profile based on that information.

[0100] A "user profile" is a collection of foundational data about a user, generated based on their personal data and preferences.

[0101] "External information sources" refer to external data sources or services used to collect relevant data based on user preference data.

[0102] A "generative model" refers to artificial intelligence technology used to generate suggestions tailored to the user's preferences.

[0103] A "suggestion" is a selection of recommended content or services presented to the user using a generative model.

[0104] "External resources" refer to the services and data linked to and accessible based on the proposal.

[0105] "Response" refers to the reaction or feedback that a user provides to a presented suggestion.

[0106] "Model" refers to the learning algorithm in a generative model that is updated in response to user feedback.

[0107] "Viewing provision services" refer to video and audio content distribution services used to provide users with appropriate content.

[0108] The system for carrying out this invention has a configuration that combines a user terminal, a server, and a generation AI model. First, the user uses a user terminal such as a smartphone or tablet to launch a specific application. Here, the user can input personal information and preference information through the interface. This information is immediately transmitted from the terminal to a server for data processing.

[0109] The server generates a user profile based on the received user information. This profile is generated based on the user's interests and needs and forms the core for providing personalized suggestions. Next, the server uses this profile to collect necessary data through external sources and APIs.

[0110] Based on the collected data, the server inputs the data into a generative model and generates the most suitable suggestions for the user. This generative model uses technology such as OpenAI®. The generated suggestions are presented to the user's terminal in a visually easy-to-understand format. By selecting the presented content, the user can smoothly access external resources. This system allows users to efficiently and accurately obtain information that matches their interests from a vast amount of information.

[0111] For example, if a user is interested in "action movies" and "Japanese culture," the server can search for relevant content from related streaming services and suggest titles such as "The Last Samurai" or "47 Ronin." If the user expresses interest, a link to immediately begin watching is also provided. An example of a prompt to input into the generating AI model would be, "Based on the user profile, please recommend content related to action movies and Japanese culture."

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The device inputs user information via an application. The user enters personal and preference information into the interface, which the device converts into a digital format and sends to the server. The input information is output as personal data.

[0115] Step 2:

[0116] The server generates a user profile based on user information received from the terminal. This profile is stored in a database. During this process, the server analyzes the data and extracts specific patterns related to the user's interests and preferences. The profile is output as an analysis result generated from the user data.

[0117] Step 3:

[0118] The server collects relevant data from external sources and APIs based on the user profile. Specifically, it searches for and retrieves information on content that matches the user's preferences. The collected data is output as information obtained from external sources.

[0119] Step 4:

[0120] The server inputs the collected data into an AI model to generate suggestions. Here, the AI ​​model analyzes the data using a prompt to generate optimal suggestions based on the user's preferences. This prompt is: "Based on the user profile, please recommend action movies and content related to Japanese culture." The generated suggestions are output as the AI ​​analysis results.

[0121] Step 5:

[0122] The server sends the generated suggestions to the terminal and presents them to the user. The terminal displays these suggestions in a visually easy-to-understand format, allowing the user to make a selection. This information is output as a list of available content.

[0123] Step 6:

[0124] The user selects a suggested option and uses a link to an external resource, such as a viewing service. The device opens the selected link and begins providing the actual service. The action taken based on the user's selection is output.

[0125] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0126] The system implementing this invention acquires not only the user's personal information and preference information, but also the user's emotional state, and provides optimal recommendations based on this information. To achieve this, the terminal provides an input interface for user information and performs emotion recognition using an emotion engine. The server then comprehensively analyzes this information and provides the user with individualized and optimized suggestions.

[0127] Users open the application using their device and enter personal information, including their travel destination and entertainment preferences. Furthermore, devices equipped with an emotion engine recognize emotions in real time from the user's voice, facial expressions, and input actions, and send this data to a server. Emotion recognition is crucial for determining the optimal state of mind for users to enjoy their travel destination and content.

[0128] When the server receives information sent from the terminal, it creates a user profile in the database and also records sentiment information. Next, based on the profile information and sentiment data, it collects relevant data from external sources. This data includes information on tourist attractions and restaurants in travel destinations, as well as content from video streaming services.

[0129] The AI ​​analyzes this data and generates recommendations best suited to the user's current emotional state. For example, if the user wants to relax, it might suggest relaxing tourist destinations or heartwarming movies. These recommendations are sent to the device and presented to the user in an easy-to-understand visual format.

[0130] This system also includes a feedback function, allowing users to input their thoughts and opinions via their devices after a trip or using content. The server can then update its AI model based on this feedback, improving the accuracy of future recommendations.

[0131] For example, if a user is planning a trip to Scandinavia and is feeling stressed when using this system, the emotion engine will recognize this and the server may recommend a Scandinavian fjord cruise where the user can enjoy a peaceful natural environment. If the user is feeling down, the system can also recommend uplifting comedy movies from a streaming service.

[0132] Thus, the system according to the present invention provides comprehensive support that takes into account the user's emotions, thereby realizing a more fulfilling travel and entertainment experience.

[0133] The following describes the processing flow.

[0134] Step 1:

[0135] The user launches an application on their device and enters personal information and preferences regarding travel and entertainment. The device then activates an emotion engine that recognizes the user's current emotional state based on their voice, facial expressions, and input.

[0136] Step 2:

[0137] The device sends the recognized user's emotional data and entered personal information to the server. This allows the server to receive the basic data needed to create a comprehensive profile of the user.

[0138] Step 3:

[0139] The server creates a user profile based on the received user information and sentiment data. This profile records the user's preferences, interests, and current emotional state.

[0140] Step 4:

[0141] The server collects relevant travel information and content data from external sources based on the user's preferences and emotional state. It retrieves details about tourist attractions, restaurants, and video streaming services at the travel destination via an API.

[0142] Step 5:

[0143] Using generative AI, the server generates recommendations best suited to the user's emotional state from the collected data. Based on this emotional data, it analyzes what kinds of experiences and content the user enjoys most.

[0144] Step 6:

[0145] The server sends the generated recommendations to the device. The recommendations are presented visually and clearly on the device, designed to make it easy for the user to select them.

[0146] Step 7:

[0147] Users can use the provided recommendations to plan their trips or watch video content. They can also select recommendations that interest them and immediately book or start watching them via their device.

[0148] Step 8:

[0149] After a trip or entertainment experience, users enter feedback such as their impressions and ratings via their device. This feedback is also sent to the server.

[0150] Step 9:

[0151] The server analyzes user feedback and updates the AI ​​model. This update improves the accuracy and relevance of future recommendations. The feedback is used to improve the user experience in the future.

[0152] (Example 2)

[0153] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0154] Traditional information systems primarily rely on recommendations based on users' personal information and preferences, but they fail to consider the user's emotional state. Therefore, the challenge lies in enabling users to enjoy travel destinations and entertainment that best suit their mood at any given time.

[0155] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0156] In this invention, the server includes means for acquiring user emotional information and analyzing it using emotional recognition technology, means for collecting relevant data from external sources based on user preference information and emotional information, and means for generating recommendations that correspond to the user's preferences and emotions using generative AI technology. This enables optimal recommendations that correspond to the user's emotional state.

[0157] "User information" refers to a collection of data that includes user attribute information, preference information, and emotional information.

[0158] A "terminal" is a device used by a user to input information and to review the recommendations they receive.

[0159] A "server" is a central processing unit that receives and processes user information, generates recommendations, and sends them to the terminal.

[0160] "Emotion recognition technology" is a technology that analyzes a user's voice, facial expressions, input actions, etc., to infer the user's emotional state.

[0161] "Generative AI technology" is an artificial intelligence technology that generates optimal recommendations based on user preference and emotional information.

[0162] A "prompt" is an instruction or question used when generating recommendations for a generative AI.

[0163] "External information sources" refer to information services and databases used to collect relevant data based on user preferences and sentiments.

[0164] "Recommendations" refer to suggestions for travel destinations and content generated based on the user's preferences and emotional information.

[0165] "Feedback" refers to comments and opinions from users regarding recommendations, and is information used to improve the system.

[0166] The system implementing this invention aims to acquire not only user attribute information and preference information, but also emotional state, and to provide optimal recommendations based on these. To achieve this, hardware and software are used in combination as follows.

[0167] First, the terminal functions as a device for the user to input information. Smartphones and tablet devices fall into this category. Through the terminal, the user inputs attribute information and preference information, such as travel destination preferences and movie genres. The terminal is equipped with an emotion engine that recognizes the user's emotional state by analyzing their voice, facial expressions, and input actions in real time. The data thus obtained is securely transmitted to the server via a communication protocol.

[0168] As a central processing unit, the server receives data transmitted from terminals and creates or updates user profiles in the database. User profiles include attribute information, preference information, and the latest sentiment information. Based on this profile, the server accesses external information sources and collects highly relevant data. Specifically, this includes tourist information for travel destinations, food information, and content from video streaming services.

[0169] The generative AI model analyzes this information and generates recommendations best suited to the user's current emotional state. For example, if the user is seeking relaxation, it might suggest a travel plan that allows them to enjoy tranquil natural scenery. Or, if they need a boost of energy, it might recommend a cheerful comedy movie.

[0170] The generated recommendations are sent to the device and presented visually to the user. The user can review the recommendations and find more detailed information about topics that interest them. For example, a prompt might ask, "Please recommend a relaxing travel destination that suits my current mood."

[0171] Furthermore, after experiencing the provided recommendations, users can send feedback to the server via their device. The server analyzes this feedback and updates the generating AI model, thereby further improving the accuracy of future recommendations. In this way, the system of the present invention realizes comprehensive information provision that takes user emotions into consideration.

[0172] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0173] Step 1:

[0174] The user operates the terminal to input attribute and preference information. The terminal is equipped with an information input interface, where the user selects preferences such as travel destinations and movie genres. The entered information is temporarily stored on the terminal as text data.

[0175] Step 2:

[0176] The device uses its built-in emotion engine to recognize the user's emotional state in real time. The emotion engine analyzes voice and facial expressions using a voice analysis module and facial recognition software, calculating the user's emotions as numerical data. This emotion data is prepared as packet data along with the input information.

[0177] Step 3:

[0178] The terminal sends packet data containing user attribute information, preference information, and sentiment information to the server. A secure communication protocol is used to ensure data integrity and confidentiality. Upon arrival at the server, the transmitted data is decoded and used for further processing.

[0179] Step 4:

[0180] The server creates or updates user profiles based on the received information. Profile creation involves saving user attribute information, preference information, and sentiment information to a database. Once the database update is complete, the profile is used as the basis for subsequent data collection and analysis.

[0181] Step 5:

[0182] The server analyzes the user's profile and collects relevant data from external sources. Specifically, it obtains tourist information about travel destinations and content information from video streaming services from the internet. Web crawling technology and API access are used for this collection, and the collected data is temporarily stored.

[0183] Step 6:

[0184] The server analyzes collected data using a generative AI model and generates recommendations based on user preferences and emotions. The AI ​​model uses machine learning algorithms to determine the optimal travel plan or movie list, and the generated results are prepared as text and image data.

[0185] Step 7:

[0186] The server sends the generated recommendations to the device. The device visually displays the received recommendations, and the user reviews the content. The recommendations include links to more information, and the user can click on suggestions that interest them to learn more.

[0187] Step 8:

[0188] After experiencing the provided recommendations, users send their thoughts and opinions as feedback to the server via their device. This feedback may include text or selected data, which the server receives and stores.

[0189] Step 9:

[0190] The server analyzes collected user feedback and updates the generated AI model. This AI model update involves parameter adjustments based on feedback data to improve recommendation performance in subsequent uses. This feedback loop enhances the overall system adaptability and user satisfaction.

[0191] (Application Example 2)

[0192] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0193] Providing personalized content suggestions tailored to each user's individual preferences and emotions is not easy. In particular, there is a need to provide more accurate recommendations by taking into account the user's real-time emotional state. Traditional systems have struggled to fully meet users' current needs because they do not adequately utilize emotional information.

[0194] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0195] In this invention, the server includes means for operating a device that provides an interface for inputting user information to acquire the user's personal data and preference data; means for acquiring the user's emotional state using the device's emotion recognition sensor and transmitting the emotional information to a data processing device; and means for selecting relevant multimedia content from external information sources based on the emotional information and generating recommendations appropriate to the emotional state. This makes it possible to provide personalized recommendations that reflect the user's emotional state in real time.

[0196] "User information" refers to information that includes a user's personal data and preference data, and indicates the characteristics and preferences of an individual user.

[0197] An "interface" refers to the point of contact between a device or software that allows a user to input information into a system.

[0198] A "data processing device" refers to an electronic computer that receives and analyzes user input and emotional information.

[0199] An "emotion recognition sensor" refers to a device or technology that analyzes a user's voice and facial expressions to identify their emotional state.

[0200] "External information sources" refer to internet resources and databases from which the server obtains additional information for use in making recommendations.

[0201] "Multimedia content" refers to information that combines multiple media formats, such as video, audio, and text, and is intended to be presented to users as recommendations.

[0202] "Recommendation" refers to suggestions and recommendations generated based on the user's preferences and emotional state.

[0203] A system for carrying out this invention includes a terminal equipped with an interface for inputting user information. The user operates this terminal to input personal data and preference data. The terminal is equipped with an emotion recognition sensor that analyzes voice and facial expressions, thereby enabling the identification of the user's emotional state in real time. This acquired user information and emotion information is transmitted to a server using a data processing device.

[0204] The server creates a user profile based on the received information and generates personalized recommendations using generative AI. It collects and analyzes necessary multimedia content from external sources based on the user's preferences and emotions. For example, if the user wants to relax, it will recommend movies or music with relaxation effects.

[0205] The technologies used include emotion recognition software equipped with machine learning models that enable facial recognition and voice analysis, as well as application programming interfaces (APIs) implemented in Python and JavaScript® for processing information in conjunction with databases.

[0206] As a concrete example, if a user is feeling stressed, the emotion recognition sensor detects this, and the server sends a corresponding prompt to the AI. For instance, a possible prompt might read, "For a user whose current emotional state is 'relaxed,' please suggest some soothing video content." This makes it possible to suggest content that is optimally suited to the user's emotions.

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] The device acquires the user's personal and preference data through its interface. This input is done through text input and checkbox selection. The data is temporarily stored in local storage.

[0210] Step 2:

[0211] The device's emotion recognition sensor operates, analyzing the user's voice and facial expressions to recognize their emotional state. The acquired sensor data is processed by an algorithm to identify the user's emotional state in real time. The output is a defined emotion label such as "relaxed" or "stressed."

[0212] Step 3:

[0213] User input data and recognized emotional states are sent from the terminal to the server. Here, the data is transferred via a secure communication protocol (e.g., HTTPS). The server analyzes the received data and creates or updates the user profile.

[0214] Step 4:

[0215] The server uses a generative AI model to collect multimedia content from relevant external sources based on the user's preferences and emotional state. The input is the user profile and emotional labels, and the output is a list of recommended content.

[0216] Step 5:

[0217] The server analyzes multimedia content collected from external sources and generates recommendations best suited to the user's emotional state. Here, a generative AI model organizes the data based on prompt text and lists appropriate content.

[0218] Step 6:

[0219] The server sends the generated recommendations to the device and presents them to the user. The recommendations are displayed in the user interface so that the user can visually select them.

[0220] Step 7:

[0221] Users select from the presented recommendations, experience the content, and then send their feedback to the server via their device. The input consists of user feedback and evaluation information, while the output is an improved version of the AI ​​model.

[0222] Step 8:

[0223] The server collects user feedback and updates the AI ​​model to improve the accuracy of future recommendations. This ensures a continuous improvement in the user experience.

[0224] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0225] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0226] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0230] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0231] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0232] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0233] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0234] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0235] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0236] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0237] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0238] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0239] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0240] A system for carrying out the present invention includes a terminal that provides an interface for inputting user information, a server that receives and analyzes the acquired information, and a communication means for presenting the results to the user.

[0241] Users launch the application using a smartphone or tablet and input personal information, travel destinations, preferred entertainment categories, and other details through the interface. The device immediately transmits the information entered by the user to the server. The server receives this information and creates a user profile in its database. This profile reflects the user's preferences and interests and serves as foundational data necessary for future recommendation generation.

[0242] Next, the server collects relevant information based on the user's profile information through the internet and APIs of partner services. This includes information on tourist attractions and public Wi-Fi in travel destinations, restaurant reservation status, and even content information from video streaming services. The server analyzes this information and uses AI to create recommendations tailored to the user's preferences.

[0243] The generated recommendations are returned to the device and presented to the user in a visually easy-to-understand format. Users can use this information to plan their travel schedules or select movies and anime. Furthermore, the device provides links to external websites for the user's chosen options, supporting them in immediately starting reservations or viewing.

[0244] For example, if a user is planning a trip to Japan and wants to visit Kyoto, the server can recommend popular tourist spots in Kyoto, the best time to visit, and even highly-rated Japanese restaurants in Kyoto. Similarly, video streaming services can suggest documentaries and films related to Japanese culture that the user might find interesting.

[0245] Thus, the system according to the present invention makes it possible to streamline and enhance users' travel and entertainment experiences. By combining the analytical capabilities of the server with the power of generative AI to provide accurate recommendations, users are freed from cumbersome information searches and can enjoy a richer experience.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user launches the application on their device and enters personal information, travel destination, and preferred entertainment categories on the interface. The device retrieves this information and prepares to send it to the server.

[0249] Step 2:

[0250] The terminal sends the information entered by the user to the server. The server receives this information and creates a user profile in its database. This profile is a database entry that reflects the user's preferences and interests.

[0251] Step 3:

[0252] The server accesses external information sources to collect relevant information based on the user profile. Through API calls, it retrieves tourist information for travel destinations, restaurant reservation status, and content information for video streaming services. The results are then temporarily stored.

[0253] Step 4:

[0254] The server analyzes the collected information and uses generative AI to generate recommendations tailored to the user's preferences. The analysis includes a process of comparing user profile data with collected external information.

[0255] Step 5:

[0256] The device receives recommendations from the server and presents them to the user. The recommendations are formatted in a visually easy-to-understand format and include itineraries, sightseeing spots, and available content.

[0257] Step 6:

[0258] Users view the presented recommendations and select travel destinations or content that interest them. Based on the user's selection, the device provides links to external sites and assists with booking or viewing procedures.

[0259] Step 7:

[0260] After using a travel experience or content, users enter feedback via their device. The device then prepares to send this feedback to the server.

[0261] Step 8:

[0262] The server analyzes the feedback received and updates the AI ​​model to improve the accuracy of future recommendations. This data will be used to generate recommendations in the future.

[0263] (Example 1)

[0264] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0265] Existing information provision systems struggle to efficiently collect and provide personalized information tailored to users' diverse preferences and interests. Furthermore, there is a need to provide users with timely and accurate feedback on the information they desire, thereby improving convenience. Additionally, a mechanism is required to continuously improve the quality of the recommended information provided.

[0266] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0267] In this invention, the server includes means for creating a user profile, means for collecting and analyzing relevant information data based on the user's preference information, and means for generating recommendation information tailored to the user's preferences using generative artificial intelligence. This makes it possible to provide information tailored to the user's individual preferences very quickly and accurately, and furthermore, to realize a high-quality personalized experience by continuously improving the artificial intelligence model based on user evaluations.

[0268] "User information" refers to data that includes the user's personally identifiable information and preference information.

[0269] A "display device" is an electronic device used to provide information to users visually.

[0270] A "processing device" is a computer or server used to receive, analyze, and store data.

[0271] A "user profile" is recorded data that reflects a user's individual hobbies and interests.

[0272] "Information data" refers to all collectible information about people and things.

[0273] "External information resources" refer to information sources outside the system, including the internet and other data provision services.

[0274] "Generative artificial intelligence" is a technology that uses computer programs to automatically mimic human intellectual work.

[0275] "Recommended information" refers to suggestions and content generated based on user preferences.

[0276] A "path" is a link or connection that allows a user to reach the information or service they are looking for.

[0277] "Rating" refers to feedback or opinions from users regarding the information or services they receive.

[0278] An "artificial intelligence model" is a structure that uses machine learning algorithms to analyze and learn information.

[0279] This invention is a system that provides personalized recommendations based on user information, and is realized through the collaboration of the user, terminal, and server. The user launches an application using an information terminal such as a smartphone or tablet. This application provides an interface for the user to input personal information and preferences. The user inputs, for example, travel destinations or entertainment categories of interest. The terminal immediately sends the entered information to the server. This transmission ensures secure communication using the HTTPS protocol.

[0280] The server uses a database system to store received information and create user profiles. For this, database software such as MySQL can be used. Next, the server uses a generative AI model to collect information from external information resources. The collected data is then analyzed using libraries such as Scikit-learn and TensorFlow, which run in a Python environment.

[0281] The server generates and sends recommendation information to the device based on the user's preferences. This recommendation information includes tourist attractions at the travel destination, suitable times to visit, restaurant reservation availability, and content from video services. The device presents the information to the user in a visually easy-to-understand manner and, if necessary, provides a route to external information resources.

[0282] As a specific example, consider the case where a user plans a trip to Japan and is particularly interested in Kyoto. Based on this information, the server can create a list of tourist attractions in Kyoto, highly rated Japanese restaurants, and even movies related to Japanese culture, and present it to the user. An example of the prompt sentence used is "Please propose tourist attractions that the user might be interested in."

[0283] By providing information that perfectly suits the user without excess or deficiency, this system makes it possible to realize an excellent user experience tailored to individual needs.

[0284] The flow of the specific process in Example 1 will be described using FIG. 11.

[0285] Step 1:

[0286] The user launches an application on a smartphone or tablet and enters personal information and preference information via the interface. The information entered includes the destination of the trip, entertainment preferences, etc. This information is formatted by the terminal and prepared for the next processing step. The input information is directly sent to the server and used as basic data for understanding the user's needs.

[0287] Step 2:

[0288] The terminal sends the data entered by the user to the server using the HTTPS protocol. The input here is the user's personal and preference data and is sent to the server. This data reaches the server in a secure state and is saved in the database. The output is prepared as the saved user data for subsequent processing.

[0289] Step 3:

[0290] The server creates a user profile in the database based on the received user information. During this profile creation process, the data is structured to reflect the user's personality and interests. The input is the stored user data, and the output is the constructed profile information. This profile is used for further analysis of the user's needs and for generating recommendations.

[0291] Step 4:

[0292] The server collects relevant information from external sources based on the user profile. This process utilizes the internet and various APIs to obtain data on tourist attractions, restaurants, and video content. The server uses the profile as input and obtains relevant information as output. This information is then prepared for further advanced analysis using generative AI.

[0293] Step 5:

[0294] The server analyzes the collected data using generative AI to generate recommendations tailored to the user's preferences. Specifically, it runs machine learning models using Python and libraries such as Scikit-learn and TensorFlow to identify the most relevant information for the user. The input consists of external information and the user profile, and the output is specific recommendations. These recommendations are then formatted for presentation to the user.

[0295] Step 6:

[0296] The server sends generated recommendations to the device. The device receives this information and presents it to the user in a visually easy-to-understand format. The input here is the recommended information generated by the server, and the output is the on-screen display to the user. Furthermore, the device provides routes to external sites as needed, supporting the user in taking immediate action.

[0297] (Application Example 1)

[0298] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0299] In today's world, users find it difficult to select content and services that match their preferences and needs from a vast amount of information. Furthermore, as user preferences diversify, there is a need for technology that can efficiently provide individually tailored recommendations. To solve this problem, a system is needed that appropriately utilizes users' personal data and provides information quickly and accurately based on that data.

[0300] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0301] In this invention, the server includes means for operating a device that provides an interface for inputting user information to acquire the user's personal data and preference data; means for transmitting the acquired user information to a data processing device and generating a user profile; and means for collecting relevant data from external sources based on the user's preference data and analyzing it. This makes it possible for users to easily select content that suits their interests.

[0302] "User information" refers to personal data and preference data obtained by users through their devices.

[0303] An "interface" is a means of interaction between a user and a device for inputting user information.

[0304] "Device" refers to electronic equipment used for inputting and displaying user information.

[0305] A "data processing device" is a device that receives user information and generates a user profile based on that information.

[0306] The "user profile" is a collection of basic data about a user, generated based on the user's personal data and preferences.

[0307] The "external information source" refers to external data sources or services used to collect relevant data based on the user's preference data.

[0308] The "generation model" refers to artificial intelligence technology used to generate proposals according to the user's preferences.

[0309] A "proposal" is an option of recommended content or service presented to the user using the generation model.

[0310] The "external resource" refers to the linked service or data that can be accessed based on the proposal.

[0311] A "response" refers to the reaction or feedback provided by the user to the presented proposal.

[0312] The "model" refers to the learning algorithm that is updated according to the user's feedback in the generation model.

[0313] The "video / audio content delivery service" refers to the service for delivering video and audio content used to provide appropriate content for the user.

[0314] The system for implementing this invention has a configuration that combines a user terminal, a server, and a generation AI model. First, the user uses a user terminal such as a smartphone or tablet to launch a specific application. Here, the user can input personal information and preference information through the interface. This information is immediately sent from the terminal to the server for data processing.

[0315] The server generates a user profile based on the received user information. This profile is generated based on the user's interests and needs and forms the core for providing personalized suggestions. Next, the server uses this profile to collect necessary data through external sources and APIs.

[0316] Based on the collected data, the server inputs the data into a generative model and generates the most suitable suggestions for the user. This generative model uses technology such as OpenAI. The generated suggestions are presented to the user's terminal in a visually easy-to-understand format. By selecting the presented content, the user can smoothly access external resources. This system allows users to efficiently and accurately obtain information that matches their interests from a vast amount of information.

[0317] For example, if a user is interested in "action movies" and "Japanese culture," the server can search for relevant content from related streaming services and suggest titles such as "The Last Samurai" or "47 Ronin." If the user expresses interest, a link to immediately begin watching is also provided. An example of a prompt to input into the generating AI model would be, "Based on the user profile, please recommend content related to action movies and Japanese culture."

[0318] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0319] Step 1:

[0320] The device inputs user information via an application. The user enters personal and preference information into the interface, which the device converts into a digital format and sends to the server. The input information is output as personal data.

[0321] Step 2:

[0322] The server generates a user profile based on user information received from the terminal. This profile is stored in a database. During this process, the server analyzes the data and extracts specific patterns related to the user's interests and preferences. The profile is output as an analysis result generated from the user data.

[0323] Step 3:

[0324] The server collects relevant data from external sources and APIs based on the user profile. Specifically, it searches for and retrieves information on content that matches the user's preferences. The collected data is output as information obtained from external sources.

[0325] Step 4:

[0326] The server inputs the collected data into an AI model to generate suggestions. Here, the AI ​​model analyzes the data using a prompt to generate optimal suggestions based on the user's preferences. This prompt is: "Based on the user profile, please recommend action movies and content related to Japanese culture." The generated suggestions are output as the AI ​​analysis results.

[0327] Step 5:

[0328] The server sends the generated suggestions to the terminal and presents them to the user. The terminal displays these suggestions in a visually easy-to-understand format, allowing the user to make a selection. This information is output as a list of available content.

[0329] Step 6:

[0330] The user selects a suggested option and uses a link to an external resource, such as a viewing service. The device opens the selected link and begins providing the actual service. The action taken based on the user's selection is output.

[0331] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0332] The system implementing this invention acquires not only the user's personal information and preference information, but also the user's emotional state, and provides optimal recommendations based on this information. To achieve this, the terminal provides an input interface for user information and performs emotion recognition using an emotion engine. The server then comprehensively analyzes this information and provides the user with individualized and optimized suggestions.

[0333] Users open the application using their device and enter personal information, including their travel destination and entertainment preferences. Furthermore, devices equipped with an emotion engine recognize emotions in real time from the user's voice, facial expressions, and input actions, and send this data to a server. Emotion recognition is crucial for determining the optimal state of mind for users to enjoy their travel destination and content.

[0334] When the server receives information sent from the terminal, it creates a user profile in the database and also records sentiment information. Next, based on the profile information and sentiment data, it collects relevant data from external sources. This data includes information on tourist attractions and restaurants in travel destinations, as well as content from video streaming services.

[0335] The AI ​​analyzes this data and generates recommendations best suited to the user's current emotional state. For example, if the user wants to relax, it might suggest relaxing tourist destinations or heartwarming movies. These recommendations are sent to the device and presented to the user in an easy-to-understand visual format.

[0336] This system also includes a feedback function, allowing users to input their thoughts and opinions via their devices after a trip or using content. The server can then update its AI model based on this feedback, improving the accuracy of future recommendations.

[0337] For example, if a user is planning a trip to Scandinavia and is feeling stressed when using this system, the emotion engine will recognize this and the server may recommend a Scandinavian fjord cruise where the user can enjoy a peaceful natural environment. If the user is feeling down, the system can also recommend uplifting comedy movies from a streaming service.

[0338] Thus, the system according to the present invention provides comprehensive support that takes into account the user's emotions, thereby realizing a more fulfilling travel and entertainment experience.

[0339] The following describes the processing flow.

[0340] Step 1:

[0341] The user launches an application on their device and enters personal information and preferences regarding travel and entertainment. The device then activates an emotion engine that recognizes the user's current emotional state based on their voice, facial expressions, and input.

[0342] Step 2:

[0343] The device sends the recognized user's emotional data and entered personal information to the server. This allows the server to receive the basic data needed to create a comprehensive profile of the user.

[0344] Step 3:

[0345] The server creates a user profile based on the received user information and sentiment data. This profile records the user's preferences, interests, and current emotional state.

[0346] Step 4:

[0347] The server collects relevant travel information and content data from external sources based on the user's preferences and emotional state. It retrieves details about tourist attractions, restaurants, and video streaming services at the travel destination via an API.

[0348] Step 5:

[0349] Using generative AI, the server generates recommendations best suited to the user's emotional state from the collected data. Based on this emotional data, it analyzes what kinds of experiences and content the user enjoys most.

[0350] Step 6:

[0351] The server sends the generated recommendations to the device. The recommendations are presented visually and clearly on the device, designed to make it easy for the user to select them.

[0352] Step 7:

[0353] Users can use the provided recommendations to plan their trips or watch video content. They can also select recommendations that interest them and immediately book or start watching them via their device.

[0354] Step 8:

[0355] After a trip or entertainment experience, users enter feedback such as their impressions and ratings via their device. This feedback is also sent to the server.

[0356] Step 9:

[0357] The server analyzes user feedback and updates the AI ​​model. This update improves the accuracy and relevance of future recommendations. The feedback is used to improve the user experience in the future.

[0358] (Example 2)

[0359] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0360] Traditional information systems primarily rely on recommendations based on users' personal information and preferences, but they fail to consider the user's emotional state. Therefore, the challenge lies in enabling users to enjoy travel destinations and entertainment that best suit their mood at any given time.

[0361] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0362] In this invention, the server includes means for acquiring user emotional information and analyzing it using emotional recognition technology, means for collecting relevant data from external sources based on user preference information and emotional information, and means for generating recommendations that correspond to the user's preferences and emotions using generative AI technology. This enables optimal recommendations that correspond to the user's emotional state.

[0363] "User information" refers to a collection of data that includes user attribute information, preference information, and emotional information.

[0364] A "terminal" is a device used by a user to input information and to review the recommendations they receive.

[0365] A "server" is a central processing unit that receives and processes user information, generates recommendations, and sends them to the terminal.

[0366] "Emotion recognition technology" is a technology that analyzes a user's voice, facial expressions, input actions, etc., to infer the user's emotional state.

[0367] "Generative AI technology" is an artificial intelligence technology that generates optimal recommendations based on user preference and emotional information.

[0368] A "prompt" is an instruction or question used when generating recommendations for a generative AI.

[0369] "External information sources" refer to information services and databases used to collect relevant data based on user preferences and sentiments.

[0370] "Recommendations" refer to suggestions for travel destinations and content generated based on the user's preferences and emotional information.

[0371] "Feedback" refers to comments and opinions from users regarding recommendations, and is information used to improve the system.

[0372] The system implementing this invention aims to acquire not only user attribute information and preference information, but also emotional state, and to provide optimal recommendations based on these. To achieve this, hardware and software are used in combination as follows.

[0373] First, the terminal functions as a device for the user to input information. Smartphones and tablet devices fall into this category. Through the terminal, the user inputs attribute information and preference information, such as travel destination preferences and movie genres. The terminal is equipped with an emotion engine that recognizes the user's emotional state by analyzing their voice, facial expressions, and input actions in real time. The data thus obtained is securely transmitted to the server via a communication protocol.

[0374] As a central processing unit, the server receives data transmitted from terminals and creates or updates user profiles in the database. User profiles include attribute information, preference information, and the latest sentiment information. Based on this profile, the server accesses external information sources and collects highly relevant data. Specifically, this includes tourist information for travel destinations, food information, and content from video streaming services.

[0375] The generative AI model analyzes this information and generates recommendations best suited to the user's current emotional state. For example, if the user is seeking relaxation, it might suggest a travel plan that allows them to enjoy tranquil natural scenery. Or, if they need a boost of energy, it might recommend a cheerful comedy movie.

[0376] The generated recommendations are sent to the device and presented visually to the user. The user can review the recommendations and find more detailed information about topics that interest them. For example, a prompt might ask, "Please recommend a relaxing travel destination that suits my current mood."

[0377] Furthermore, after experiencing the provided recommendations, users can send feedback to the server via their device. The server analyzes this feedback and updates the generating AI model, thereby further improving the accuracy of future recommendations. In this way, the system of the present invention realizes comprehensive information provision that takes user emotions into consideration.

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] The user operates the terminal to input attribute and preference information. The terminal is equipped with an information input interface, where the user selects preferences such as travel destinations and movie genres. The entered information is temporarily stored on the terminal as text data.

[0381] Step 2:

[0382] The device uses its built-in emotion engine to recognize the user's emotional state in real time. The emotion engine analyzes voice and facial expressions using a voice analysis module and facial recognition software, calculating the user's emotions as numerical data. This emotion data is prepared as packet data along with the input information.

[0383] Step 3:

[0384] The terminal sends packet data containing user attribute information, preference information, and sentiment information to the server. A secure communication protocol is used to ensure data integrity and confidentiality. Upon arrival at the server, the transmitted data is decoded and used for further processing.

[0385] Step 4:

[0386] The server creates or updates user profiles based on the received information. Profile creation involves saving user attribute information, preference information, and sentiment information to a database. Once the database update is complete, the profile is used as the basis for subsequent data collection and analysis.

[0387] Step 5:

[0388] The server analyzes the user's profile and collects relevant data from external sources. Specifically, it obtains tourist information about travel destinations and content information from video streaming services from the internet. Web crawling technology and API access are used for this collection, and the collected data is temporarily stored.

[0389] Step 6:

[0390] The server analyzes collected data using a generative AI model and generates recommendations based on user preferences and emotions. The AI ​​model uses machine learning algorithms to determine the optimal travel plan or movie list, and the generated results are prepared as text and image data.

[0391] Step 7:

[0392] The server sends the generated recommendations to the device. The device visually displays the received recommendations, and the user reviews the content. The recommendations include links to more information, and the user can click on suggestions that interest them to learn more.

[0393] Step 8:

[0394] After experiencing the provided recommendations, users send their thoughts and opinions as feedback to the server via their device. This feedback may include text or selected data, which the server receives and stores.

[0395] Step 9:

[0396] The server analyzes collected user feedback and updates the generated AI model. This AI model update involves parameter adjustments based on feedback data to improve recommendation performance in subsequent uses. This feedback loop enhances the overall system adaptability and user satisfaction.

[0397] (Application Example 2)

[0398] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0399] Providing personalized content suggestions tailored to each user's individual preferences and emotions is not easy. In particular, there is a need to provide more accurate recommendations by taking into account the user's real-time emotional state. Traditional systems have struggled to fully meet users' current needs because they do not adequately utilize emotional information.

[0400] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0401] In this invention, the server includes means for operating a device that provides an interface for inputting user information to acquire the user's personal data and preference data; means for acquiring the user's emotional state using the device's emotion recognition sensor and transmitting the emotional information to a data processing device; and means for selecting relevant multimedia content from external information sources based on the emotional information and generating recommendations appropriate to the emotional state. This makes it possible to provide personalized recommendations that reflect the user's emotional state in real time.

[0402] "User information" refers to information that includes a user's personal data and preference data, and indicates the characteristics and preferences of an individual user.

[0403] An "interface" refers to the point of contact between a device or software that allows a user to input information into a system.

[0404] A "data processing device" refers to an electronic computer that receives and analyzes user input and emotional information.

[0405] An "emotion recognition sensor" refers to a device or technology that analyzes a user's voice and facial expressions to identify their emotional state.

[0406] "External information sources" refer to internet resources and databases from which the server obtains additional information for use in making recommendations.

[0407] "Multimedia content" refers to information that combines multiple media formats, such as video, audio, and text, and is intended to be presented to users as recommendations.

[0408] "Recommendation" refers to suggestions and recommendations generated based on the user's preferences and emotional state.

[0409] A system for carrying out this invention includes a terminal equipped with an interface for inputting user information. The user operates this terminal to input personal data and preference data. The terminal is equipped with an emotion recognition sensor that analyzes voice and facial expressions, thereby enabling the identification of the user's emotional state in real time. This acquired user information and emotion information is transmitted to a server using a data processing device.

[0410] The server creates a user profile based on the received information and generates personalized recommendations using generative AI. It collects and analyzes necessary multimedia content from external sources based on the user's preferences and emotions. For example, if the user wants to relax, it will recommend movies or music with relaxation effects.

[0411] The technologies used include emotion recognition software equipped with machine learning models that enable facial recognition and voice analysis, as well as application programming interfaces (APIs) implemented in Python and JavaScript to process information in conjunction with databases.

[0412] As a concrete example, if a user is experiencing stress, an emotion recognition sensor detects this, and the server sends a corresponding prompt to the AI. For instance, a possible prompt might read, "For a user whose current emotional state is 'relaxed,' please suggest some soothing video content." This makes it possible to suggest content that best matches the user's emotions.

[0413] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0414] Step 1:

[0415] The device acquires the user's personal and preference data through its interface. This input is done through text input and checkbox selection. The data is temporarily stored in local storage.

[0416] Step 2:

[0417] The device's emotion recognition sensor operates, analyzing the user's voice and facial expressions to recognize their emotional state. The acquired sensor data is processed by an algorithm to identify the user's emotional state in real time. The output is a defined emotion label such as "relaxed" or "stressed."

[0418] Step 3:

[0419] User input data and recognized emotional states are sent from the terminal to the server. Here, the data is transferred via a secure communication protocol (e.g., HTTPS). The server analyzes the received data and creates or updates the user profile.

[0420] Step 4:

[0421] The server uses a generative AI model to collect multimedia content from relevant external sources based on the user's preferences and emotional state. The input is the user profile and emotional labels, and the output is a list of recommended content.

[0422] Step 5:

[0423] The server analyzes multimedia content collected from external sources and generates recommendations best suited to the user's emotional state. Here, a generative AI model organizes the data based on prompt text and lists appropriate content.

[0424] Step 6:

[0425] The server sends the generated recommendations to the device and presents them to the user. The recommendations are displayed in the user interface so that the user can visually select them.

[0426] Step 7:

[0427] Users select from the presented recommendations, experience the content, and then send their feedback to the server via their device. The input consists of user feedback and evaluation information, while the output is an improved version of the AI ​​model.

[0428] Step 8:

[0429] The server collects user feedback and updates the AI ​​model to improve the accuracy of future recommendations. This ensures a continuous improvement in the user experience.

[0430] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0431] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0432] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0433] [Third Embodiment]

[0434] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0435] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0436] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0437] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0438] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0439] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0440] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0441] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0442] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0443] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0444] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0445] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0446] A system for carrying out the present invention includes a terminal that provides an interface for inputting user information, a server that receives and analyzes the acquired information, and a communication means for presenting the results to the user.

[0447] Users launch the application using a smartphone or tablet and input personal information, travel destinations, preferred entertainment categories, and other details through the interface. The device immediately transmits the information entered by the user to the server. The server receives this information and creates a user profile in its database. This profile reflects the user's preferences and interests and serves as foundational data necessary for future recommendation generation.

[0448] Next, the server collects relevant information based on the user's profile information through the internet and APIs of partner services. This includes information on tourist attractions and public Wi-Fi in travel destinations, restaurant reservation status, and even content information from video streaming services. The server analyzes this information and uses AI to create recommendations tailored to the user's preferences.

[0449] The generated recommendations are returned to the device and presented to the user in a visually easy-to-understand format. Users can use this information to plan their travel schedules or select movies and anime. Furthermore, the device provides links to external websites for the user's chosen options, supporting them in immediately starting reservations or viewing.

[0450] For example, if a user is planning a trip to Japan and wants to visit Kyoto, the server can recommend popular tourist spots in Kyoto, the best time to visit, and even highly-rated Japanese restaurants in Kyoto. Similarly, video streaming services can suggest documentaries and films related to Japanese culture that the user might find interesting.

[0451] Thus, the system according to the present invention makes it possible to streamline and enhance users' travel and entertainment experiences. By combining the analytical capabilities of the server with the power of generative AI to provide accurate recommendations, users are freed from cumbersome information searches and can enjoy a richer experience.

[0452] The following describes the processing flow.

[0453] Step 1:

[0454] The user launches the application on their device and enters personal information, travel destination, and preferred entertainment categories on the interface. The device retrieves this information and prepares to send it to the server.

[0455] Step 2:

[0456] The terminal sends the information entered by the user to the server. The server receives this information and creates a user profile in its database. This profile is a database entry that reflects the user's preferences and interests.

[0457] Step 3:

[0458] The server accesses external information sources to collect relevant information based on the user profile. Through API calls, it retrieves tourist information for travel destinations, restaurant reservation status, and content information for video streaming services. The results are then temporarily stored.

[0459] Step 4:

[0460] The server analyzes the collected information and uses generative AI to generate recommendations tailored to the user's preferences. The analysis includes a process of comparing user profile data with collected external information.

[0461] Step 5:

[0462] The device receives recommendations from the server and presents them to the user. The recommendations are formatted in a visually easy-to-understand format and include itineraries, sightseeing spots, and available content.

[0463] Step 6:

[0464] Users view the presented recommendations and select travel destinations or content that interest them. Based on the user's selection, the device provides links to external sites and assists with booking or viewing procedures.

[0465] Step 7:

[0466] After using a travel experience or content, users enter feedback via their device. The device then prepares to send this feedback to the server.

[0467] Step 8:

[0468] The server analyzes the feedback received and updates the AI ​​model to improve the accuracy of future recommendations. This data will be used to generate recommendations in the future.

[0469] (Example 1)

[0470] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0471] Existing information provision systems struggle to efficiently collect and provide personalized information tailored to users' diverse preferences and interests. Furthermore, there is a need to provide users with timely and accurate feedback on the information they desire, thereby improving convenience. Additionally, a mechanism is required to continuously improve the quality of the recommended information provided.

[0472] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0473] In this invention, the server includes means for creating a user profile, means for collecting and analyzing relevant information data based on the user's preference information, and means for generating recommendation information tailored to the user's preferences using generative artificial intelligence. This makes it possible to provide information tailored to the user's individual preferences very quickly and accurately, and furthermore, to realize a high-quality personalized experience by continuously improving the artificial intelligence model based on user evaluations.

[0474] "User information" refers to data that includes the user's personally identifiable information and preference information.

[0475] A "display device" is an electronic device used to provide information to users visually.

[0476] A "processing device" is a computer or server used to receive, analyze, and store data.

[0477] A "user profile" is recorded data that reflects a user's individual hobbies and interests.

[0478] "Information data" refers to all collectible information about people and things.

[0479] "External information resources" refer to information sources outside the system, including the internet and other data provision services.

[0480] "Generative artificial intelligence" is a technology that uses computer programs to automatically mimic human intellectual work.

[0481] "Recommended information" refers to suggestions and content generated based on user preferences.

[0482] A "path" is a link or connection that allows a user to reach the information or service they are looking for.

[0483] "Rating" refers to feedback or opinions from users regarding the information or services they receive.

[0484] An "artificial intelligence model" is a structure that uses machine learning algorithms to analyze and learn information.

[0485] This invention is a system that provides personalized recommendations based on user information, and is realized through the collaboration of the user, terminal, and server. The user launches an application using an information terminal such as a smartphone or tablet. This application provides an interface for the user to input personal information and preferences. The user inputs, for example, travel destinations or entertainment categories of interest. The terminal immediately sends the entered information to the server. This transmission ensures secure communication using the HTTPS protocol.

[0486] The server uses a database system to store received information and create user profiles. For this, database software such as MySQL can be used. Next, the server uses a generative AI model to collect information from external information resources. The collected data is then analyzed using libraries such as Scikit-learn and TensorFlow, which run in a Python environment.

[0487] The server generates and sends recommendation information to the device based on the user's preferences. This recommendation information includes tourist attractions at the travel destination, suitable times to visit, restaurant reservation availability, and content from video services. The device presents the information to the user in a visually easy-to-understand manner and, if necessary, provides a route to external information resources.

[0488] As a concrete example, consider a case where a user is planning a trip to Japan and is particularly interested in Kyoto. Based on this information, the server can create and present a list of Kyoto tourist spots, highly-rated Japanese restaurants, and even movies related to Japanese culture. An example of a prompt used might be, "Please suggest tourist spots that the user might be interested in."

[0489] This system enables the creation of an excellent user experience tailored to individual needs by providing users with information that is neither too much nor too little.

[0490] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0491] Step 1:

[0492] Users launch an application on their smartphone or tablet and enter personal and preference information through the interface. This information includes travel destinations and entertainment preferences. This information is formatted by the device and prepared for the next processing step. The entered information is then sent directly to the server and used as foundational data to understand the user's needs.

[0493] Step 2:

[0494] The terminal sends data entered by the user to the server using the HTTPS protocol. This input consists of the user's personal and preference data, which is sent to the server. This data reaches the server securely and is stored in a database. The output is then prepared as stored user data for use in subsequent processing.

[0495] Step 3:

[0496] The server creates a user profile in the database based on the received user information. During this profile creation process, the data is structured to reflect the user's personality and interests. The input is the stored user data, and the output is the constructed profile information. This profile is used for further analysis of the user's needs and for generating recommendations.

[0497] Step 4:

[0498] The server collects relevant information from external sources based on the user profile. This process utilizes the internet and various APIs to obtain data on tourist attractions, restaurants, and video content. The server uses the profile as input and obtains relevant information as output. This information is then prepared for further advanced analysis using generative AI.

[0499] Step 5:

[0500] The server analyzes the collected data using generative AI to generate recommendations tailored to the user's preferences. Specifically, it runs machine learning models using Python and libraries such as Scikit-learn and TensorFlow to identify the most relevant information for the user. The input consists of external information and the user profile, and the output is specific recommendations. These recommendations are then formatted for presentation to the user.

[0501] Step 6:

[0502] The server sends generated recommendations to the device. The device receives this information and presents it to the user in a visually easy-to-understand format. The input here is the recommended information generated by the server, and the output is the on-screen display to the user. Furthermore, the device provides routes to external sites as needed, supporting the user in taking immediate action.

[0503] (Application Example 1)

[0504] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0505] In today's world, users find it difficult to select content and services that match their preferences and needs from a vast amount of information. Furthermore, as user preferences diversify, there is a need for technology that can efficiently provide individually tailored recommendations. To solve this problem, a system is needed that appropriately utilizes users' personal data and provides information quickly and accurately based on that data.

[0506] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0507] In this invention, the server includes means for operating a device that provides an interface for inputting user information to acquire the user's personal data and preference data; means for transmitting the acquired user information to a data processing device and generating a user profile; and means for collecting relevant data from external sources based on the user's preference data and analyzing it. This makes it possible for users to easily select content that suits their interests.

[0508] "User information" refers to personal data and preference data obtained by users through their devices.

[0509] An "interface" is a means of interaction between a user and a device for inputting user information.

[0510] "Device" refers to electronic equipment used for inputting and displaying user information.

[0511] A "data processing device" is a device that receives user information and generates a user profile based on that information.

[0512] A "user profile" is a collection of foundational data about a user, generated based on their personal data and preferences.

[0513] "External information sources" refer to external data sources or services used to collect relevant data based on user preference data.

[0514] A "generative model" refers to artificial intelligence technology used to generate suggestions tailored to the user's preferences.

[0515] A "suggestion" is a selection of recommended content or services presented to the user using a generative model.

[0516] "External resources" refer to the services and data linked to and accessible based on the proposal.

[0517] "Response" refers to the reaction or feedback that a user provides to a proposed suggestion.

[0518] "Model" refers to the learning algorithm in a generative model that is updated in response to user feedback.

[0519] "Viewing provision services" refer to video and audio content distribution services used to provide users with appropriate content.

[0520] The system for carrying out this invention has a configuration that combines a user terminal, a server, and a generation AI model. First, the user uses a user terminal such as a smartphone or tablet to launch a specific application. Here, the user can input personal information and preference information through the interface. This information is immediately transmitted from the terminal to a server for data processing.

[0521] The server generates a user profile based on the received user information. This profile is generated based on the user's interests and needs and forms the core for providing personalized suggestions. Next, the server uses this profile to collect necessary data through external sources and APIs.

[0522] Based on the collected data, the server inputs the data into a generative model and generates the most suitable suggestions for the user. This generative model uses technology such as OpenAI. The generated suggestions are presented to the user's terminal in a visually easy-to-understand format. By selecting the presented content, the user can smoothly access external resources. This system allows users to efficiently and accurately obtain information that matches their interests from a vast amount of information.

[0523] For example, if a user is interested in "action movies" and "Japanese culture," the server can search for relevant content from related streaming services and suggest titles such as "The Last Samurai" or "47 Ronin." If the user expresses interest, a link to immediately begin watching is also provided. An example of a prompt to input into the generating AI model would be, "Based on the user profile, please recommend content related to action movies and Japanese culture."

[0524] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0525] Step 1:

[0526] The device inputs user information via an application. The user enters personal and preference information into the interface, which the device converts into a digital format and sends to the server. The input information is output as personal data.

[0527] Step 2:

[0528] The server generates a user profile based on user information received from the terminal. This profile is stored in a database. During this process, the server analyzes the data and extracts specific patterns related to the user's interests and preferences. The profile is output as an analysis result generated from the user data.

[0529] Step 3:

[0530] The server collects relevant data from external sources and APIs based on the user profile. Specifically, it searches for and retrieves information on content that matches the user's preferences. The collected data is output as information obtained from external sources.

[0531] Step 4:

[0532] The server inputs the collected data into an AI model to generate suggestions. Here, the AI ​​model analyzes the data using a prompt to generate optimal suggestions based on the user's preferences. This prompt is: "Based on the user profile, please recommend action movies and content related to Japanese culture." The generated suggestions are output as the AI ​​analysis results.

[0533] Step 5:

[0534] The server sends the generated suggestions to the terminal and presents them to the user. The terminal displays these suggestions in a visually easy-to-understand format, allowing the user to make a selection. This information is output as a list of available content.

[0535] Step 6:

[0536] The user selects a suggested option and uses a link to an external resource, such as a viewing service. The device opens the selected link and begins providing the actual service. The action taken based on the user's selection is output.

[0537] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0538] The system implementing this invention acquires not only the user's personal information and preference information, but also the user's emotional state, and provides optimal recommendations based on this information. To achieve this, the terminal provides an input interface for user information and performs emotion recognition using an emotion engine. The server then comprehensively analyzes this information and provides the user with individualized and optimized suggestions.

[0539] Users open the application using their device and enter personal information, including their travel destination and entertainment preferences. Furthermore, devices equipped with an emotion engine recognize emotions in real time from the user's voice, facial expressions, and input actions, and send this data to a server. Emotion recognition is crucial for determining the optimal state of mind for users to enjoy their travel destination and content.

[0540] When the server receives information sent from the terminal, it creates a user profile in the database and also records sentiment information. Next, based on the profile information and sentiment data, it collects relevant data from external sources. This data includes information on tourist attractions and restaurants in travel destinations, as well as content from video streaming services.

[0541] The AI ​​analyzes this data and generates recommendations best suited to the user's current emotional state. For example, if the user wants to relax, it might suggest relaxing tourist destinations or heartwarming movies. These recommendations are sent to the device and presented to the user in an easy-to-understand visual format.

[0542] This system also includes a feedback function, allowing users to input their thoughts and opinions via their devices after a trip or using content. The server can then update its AI model based on this feedback, improving the accuracy of future recommendations.

[0543] For example, if a user is planning a trip to Scandinavia and is feeling stressed when using this system, the emotion engine will recognize this and the server may recommend a Scandinavian fjord cruise where the user can enjoy a peaceful natural environment. If the user is feeling down, the system can also recommend uplifting comedy movies from a streaming service.

[0544] Thus, the system according to the present invention provides comprehensive support that takes into account the user's emotions, thereby realizing a more fulfilling travel and entertainment experience.

[0545] The following describes the processing flow.

[0546] Step 1:

[0547] The user launches an application on their device and enters personal information and preferences regarding travel and entertainment. The device then activates an emotion engine that recognizes the user's current emotional state based on their voice, facial expressions, and input.

[0548] Step 2:

[0549] The device sends the recognized user's emotional data and entered personal information to the server. This allows the server to receive the basic data needed to create a comprehensive profile of the user.

[0550] Step 3:

[0551] The server creates a user profile based on the received user information and sentiment data. This profile records the user's preferences, interests, and current emotional state.

[0552] Step 4:

[0553] The server collects relevant travel information and content data from external sources based on the user's preferences and emotional state. It retrieves details about tourist attractions, restaurants, and video streaming services at the travel destination via an API.

[0554] Step 5:

[0555] Using generative AI, the server generates recommendations best suited to the user's emotional state from the collected data. Based on this emotional data, it analyzes what kinds of experiences and content the user enjoys most.

[0556] Step 6:

[0557] The server sends the generated recommendations to the device. The recommendations are presented visually and clearly on the device, designed to make it easy for the user to select them.

[0558] Step 7:

[0559] Users can use the provided recommendations to plan their trips or watch video content. They can also select recommendations that interest them and immediately book or start watching them via their device.

[0560] Step 8:

[0561] After a trip or entertainment experience, users enter feedback such as their impressions and ratings via their device. This feedback is also sent to the server.

[0562] Step 9:

[0563] The server analyzes user feedback and updates the AI ​​model. This update improves the accuracy and relevance of future recommendations. The feedback is used to improve the user experience in the future.

[0564] (Example 2)

[0565] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0566] Traditional information systems primarily rely on recommendations based on users' personal information and preferences, but they fail to consider the user's emotional state. Therefore, the challenge lies in enabling users to enjoy travel destinations and entertainment that best suit their mood at any given time.

[0567] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0568] In this invention, the server includes means for acquiring user emotional information and analyzing it using emotional recognition technology, means for collecting relevant data from external sources based on user preference information and emotional information, and means for generating recommendations that correspond to the user's preferences and emotions using generative AI technology. This enables optimal recommendations that correspond to the user's emotional state.

[0569] "User information" refers to a collection of data that includes user attribute information, preference information, and emotional information.

[0570] A "terminal" is a device used by a user to input information and to review the recommendations they receive.

[0571] A "server" is a central processing unit that receives and processes user information, generates recommendations, and sends them to the terminal.

[0572] "Emotion recognition technology" is a technology that analyzes a user's voice, facial expressions, input actions, etc., to infer the user's emotional state.

[0573] "Generative AI technology" is an artificial intelligence technology that generates optimal recommendations based on user preference and emotional information.

[0574] A "prompt" is an instruction or question used when generating recommendations for a generative AI.

[0575] "External information sources" refer to information services and databases used to collect relevant data based on user preferences and sentiments.

[0576] "Recommendations" refer to suggestions for travel destinations and content generated based on the user's preferences and emotional information.

[0577] "Feedback" refers to comments and opinions from users regarding recommendations, and is information used to improve the system.

[0578] The system implementing this invention aims to acquire not only user attribute information and preference information, but also emotional state, and to provide optimal recommendations based on these. To achieve this, hardware and software are used in combination as follows.

[0579] First, the terminal functions as a device for the user to input information. Smartphones and tablet devices fall into this category. Through the terminal, the user inputs attribute information and preference information, such as travel destination preferences and movie genres. The terminal is equipped with an emotion engine that recognizes the user's emotional state by analyzing their voice, facial expressions, and input actions in real time. The data thus obtained is securely transmitted to the server via a communication protocol.

[0580] As a central processing unit, the server receives data transmitted from terminals and creates or updates user profiles in the database. User profiles include attribute information, preference information, and the latest sentiment information. Based on this profile, the server accesses external information sources and collects highly relevant data. Specifically, this includes tourist information for travel destinations, food information, and content from video streaming services.

[0581] The generative AI model analyzes this information and generates recommendations best suited to the user's current emotional state. For example, if the user is seeking relaxation, it might suggest a travel plan that allows them to enjoy tranquil natural scenery. Or, if they need a boost of energy, it might recommend a cheerful comedy movie.

[0582] The generated recommendations are sent to the device and presented visually to the user. The user can review the recommendations and find more detailed information about topics that interest them. For example, a prompt might ask, "Please recommend a relaxing travel destination that suits my current mood."

[0583] Furthermore, after experiencing the provided recommendations, users can send feedback to the server via their device. The server analyzes this feedback and updates the generating AI model, thereby further improving the accuracy of future recommendations. In this way, the system of the present invention realizes comprehensive information provision that takes user emotions into consideration.

[0584] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0585] Step 1:

[0586] The user operates the terminal to input attribute and preference information. The terminal is equipped with an information input interface, where the user selects preferences such as travel destinations and movie genres. The entered information is temporarily stored on the terminal as text data.

[0587] Step 2:

[0588] The device uses its built-in emotion engine to recognize the user's emotional state in real time. The emotion engine analyzes voice and facial expressions using a voice analysis module and facial recognition software, calculating the user's emotions as numerical data. This emotion data is prepared as packet data along with the input information.

[0589] Step 3:

[0590] The terminal sends packet data containing user attribute information, preference information, and sentiment information to the server. A secure communication protocol is used to ensure data integrity and confidentiality. Upon arrival at the server, the transmitted data is decoded and used for further processing.

[0591] Step 4:

[0592] The server creates or updates user profiles based on the received information. Profile creation involves saving user attribute information, preference information, and sentiment information to a database. Once the database update is complete, the profile is used as the basis for subsequent data collection and analysis.

[0593] Step 5:

[0594] The server analyzes the user's profile and collects relevant data from external sources. Specifically, it obtains tourist information about travel destinations and content information from video streaming services from the internet. Web crawling technology and API access are used for this collection, and the collected data is temporarily stored.

[0595] Step 6:

[0596] The server analyzes collected data using a generative AI model and generates recommendations based on user preferences and emotions. The AI ​​model uses machine learning algorithms to determine the optimal travel plan or movie list, and the generated results are prepared as text and image data.

[0597] Step 7:

[0598] The server sends the generated recommendations to the device. The device visually displays the received recommendations, and the user reviews the content. The recommendations include links to more information, and the user can click on suggestions that interest them to learn more.

[0599] Step 8:

[0600] After experiencing the provided recommendations, users send their thoughts and opinions as feedback to the server via their device. This feedback may include text or selected data, which the server receives and stores.

[0601] Step 9:

[0602] The server analyzes collected user feedback and updates the generated AI model. This AI model update involves parameter adjustments based on feedback data to improve recommendation performance in subsequent uses. This feedback loop enhances the overall system adaptability and user satisfaction.

[0603] (Application Example 2)

[0604] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0605] Providing personalized content suggestions tailored to each user's individual preferences and emotions is not easy. In particular, there is a need to provide more accurate recommendations by taking into account the user's real-time emotional state. Traditional systems have struggled to fully meet users' current needs because they do not adequately utilize emotional information.

[0606] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0607] In this invention, the server includes means for operating a device that provides an interface for inputting user information to acquire the user's personal data and preference data; means for acquiring the user's emotional state using the device's emotion recognition sensor and transmitting the emotional information to a data processing device; and means for selecting relevant multimedia content from external information sources based on the emotional information and generating recommendations appropriate to the emotional state. This makes it possible to provide personalized recommendations that reflect the user's emotional state in real time.

[0608] "User information" refers to information that includes a user's personal data and preference data, and indicates the characteristics and preferences of an individual user.

[0609] An "interface" refers to the point of contact between a device or software that allows a user to input information into a system.

[0610] A "data processing device" refers to an electronic computer that receives and analyzes user input and emotional information.

[0611] An "emotion recognition sensor" refers to a device or technology that analyzes a user's voice and facial expressions to identify their emotional state.

[0612] "External information sources" refer to internet resources and databases from which the server obtains additional information for use in making recommendations.

[0613] "Multimedia content" refers to information that combines multiple media formats, such as video, audio, and text, and is intended to be presented to users as recommendations.

[0614] "Recommendation" refers to suggestions and recommendations generated based on the user's preferences and emotional state.

[0615] A system for carrying out this invention includes a terminal equipped with an interface for inputting user information. The user operates this terminal to input personal data and preference data. The terminal is equipped with an emotion recognition sensor that analyzes voice and facial expressions, thereby enabling the identification of the user's emotional state in real time. This acquired user information and emotion information is transmitted to a server using a data processing device.

[0616] The server creates a user profile based on the received information and generates personalized recommendations using generative AI. It collects and analyzes necessary multimedia content from external sources based on the user's preferences and emotions. For example, if the user wants to relax, it will recommend movies or music with relaxation effects.

[0617] The technologies used include emotion recognition software equipped with machine learning models that enable facial recognition and voice analysis, as well as application programming interfaces (APIs) implemented in Python and JavaScript to process information in conjunction with databases.

[0618] As a concrete example, if a user is experiencing stress, an emotion recognition sensor detects this, and the server sends a corresponding prompt to the AI. For instance, a possible prompt might read, "For a user whose current emotional state is 'relaxed,' please suggest some soothing video content." This makes it possible to suggest content that best matches the user's emotions.

[0619] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0620] Step 1:

[0621] The device acquires the user's personal and preference data through its interface. This input is done through text input and checkbox selection. The data is temporarily stored in local storage.

[0622] Step 2:

[0623] The device's emotion recognition sensor operates, analyzing the user's voice and facial expressions to recognize their emotional state. The acquired sensor data is processed by an algorithm to identify the user's emotional state in real time. The output is a defined emotion label such as "relaxed" or "stressed."

[0624] Step 3:

[0625] User input data and recognized emotional states are sent from the terminal to the server. Here, the data is transferred via a secure communication protocol (e.g., HTTPS). The server analyzes the received data and creates or updates the user profile.

[0626] Step 4:

[0627] The server uses a generative AI model to collect multimedia content from relevant external sources based on the user's preferences and emotional state. The input is the user profile and emotional labels, and the output is a list of recommended content.

[0628] Step 5:

[0629] The server analyzes multimedia content collected from external sources and generates recommendations best suited to the user's emotional state. Here, a generative AI model organizes the data based on prompt text and lists appropriate content.

[0630] Step 6:

[0631] The server sends the generated recommendations to the device and presents them to the user. The recommendations are displayed in the user interface so that the user can visually select them.

[0632] Step 7:

[0633] Users select from the presented recommendations, experience the content, and then send their feedback to the server via their device. The input consists of user feedback and evaluation information, while the output is an improved version of the AI ​​model.

[0634] Step 8:

[0635] The server collects user feedback and updates the AI ​​model to improve the accuracy of future recommendations. This ensures a continuous improvement in the user experience.

[0636] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0637] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0638] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0639] [Fourth Embodiment]

[0640] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0641] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0642] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0643] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0644] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0645] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0646] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0647] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0648] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0649] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0650] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0651] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0652] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0653] A system for carrying out the present invention includes a terminal that provides an interface for inputting user information, a server that receives and analyzes the acquired information, and a communication means for presenting the results to the user.

[0654] Users launch the application using a smartphone or tablet and input personal information, travel destinations, preferred entertainment categories, and other details through the interface. The device immediately transmits the information entered by the user to the server. The server receives this information and creates a user profile in its database. This profile reflects the user's preferences and interests and serves as foundational data necessary for future recommendation generation.

[0655] Next, the server collects relevant information based on the user's profile information through the internet and APIs of partner services. This includes information on tourist attractions and public Wi-Fi in travel destinations, restaurant reservation status, and even content information from video streaming services. The server analyzes this information and uses AI to create recommendations tailored to the user's preferences.

[0656] The generated recommendations are returned to the device and presented to the user in a visually easy-to-understand format. Users can use this information to plan their travel schedules or select movies and anime. Furthermore, the device provides links to external websites for the user's chosen options, supporting them in immediately starting reservations or viewing.

[0657] For example, if a user is planning a trip to Japan and wants to visit Kyoto, the server can recommend popular tourist spots in Kyoto, the best time to visit, and even highly-rated Japanese restaurants in Kyoto. Similarly, video streaming services can suggest documentaries and films related to Japanese culture that the user might find interesting.

[0658] Thus, the system according to the present invention makes it possible to streamline and enhance users' travel and entertainment experiences. By combining the analytical capabilities of the server with the power of generative AI to provide accurate recommendations, users are freed from cumbersome information searches and can enjoy a richer experience.

[0659] The following describes the processing flow.

[0660] Step 1:

[0661] The user launches the application on their device and enters personal information, travel destination, and preferred entertainment categories on the interface. The device retrieves this information and prepares to send it to the server.

[0662] Step 2:

[0663] The terminal sends the information entered by the user to the server. The server receives this information and creates a user profile in its database. This profile is a database entry that reflects the user's preferences and interests.

[0664] Step 3:

[0665] The server accesses external information sources to collect relevant information based on the user profile. Through API calls, it retrieves tourist information for travel destinations, restaurant reservation status, and content information for video streaming services. The results are then temporarily stored.

[0666] Step 4:

[0667] The server analyzes the collected information and uses generative AI to generate recommendations tailored to the user's preferences. The analysis includes a process of comparing user profile data with collected external information.

[0668] Step 5:

[0669] The device receives recommendations from the server and presents them to the user. The recommendations are formatted in a visually easy-to-understand format and include itineraries, sightseeing spots, and available content.

[0670] Step 6:

[0671] Users view the presented recommendations and select travel destinations or content that interest them. Based on the user's selection, the device provides links to external sites and assists with booking or viewing procedures.

[0672] Step 7:

[0673] After using a travel experience or content, users enter feedback via their device. The device then prepares to send this feedback to the server.

[0674] Step 8:

[0675] The server analyzes the feedback received and updates the AI ​​model to improve the accuracy of future recommendations. This data will be used to generate recommendations in the future.

[0676] (Example 1)

[0677] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0678] Existing information provision systems struggle to efficiently collect and provide personalized information tailored to users' diverse preferences and interests. Furthermore, there is a need to provide users with timely and accurate feedback on the information they desire, thereby improving convenience. Additionally, a mechanism is required to continuously improve the quality of the recommended information provided.

[0679] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0680] In this invention, the server includes means for creating a user profile, means for collecting and analyzing relevant information data based on the user's preference information, and means for generating recommendation information tailored to the user's preferences using generative artificial intelligence. This makes it possible to provide information tailored to the user's individual preferences very quickly and accurately, and furthermore, to realize a high-quality personalized experience by continuously improving the artificial intelligence model based on user evaluations.

[0681] "User information" refers to data that includes the user's personally identifiable information and preference information.

[0682] A "display device" is an electronic device used to provide information to users visually.

[0683] A "processing device" is a computer or server used to receive, analyze, and store data.

[0684] A "user profile" is recorded data that reflects a user's individual hobbies and interests.

[0685] "Information data" refers to all collectible information about people and things.

[0686] "External information resources" refer to information sources outside the system, including the internet and other data provision services.

[0687] "Generative artificial intelligence" is a technology that uses computer programs to automatically mimic human intellectual work.

[0688] "Recommended information" refers to suggestions and content generated based on user preferences.

[0689] A "path" is a link or connection that allows a user to reach the information or service they are looking for.

[0690] "Rating" refers to feedback or opinions from users regarding the information or services they receive.

[0691] An "artificial intelligence model" is a structure that uses machine learning algorithms to analyze and learn information.

[0692] This invention is a system that provides personalized recommendations based on user information, and is realized through the collaboration of the user, terminal, and server. The user launches an application using an information terminal such as a smartphone or tablet. This application provides an interface for the user to input personal information and preferences. The user inputs, for example, travel destinations or entertainment categories of interest. The terminal immediately sends the entered information to the server. This transmission ensures secure communication using the HTTPS protocol.

[0693] The server uses a database system to store received information and create user profiles. For this, database software such as MySQL can be used. Next, the server uses a generative AI model to collect information from external information resources. The collected data is then analyzed using libraries such as Scikit-learn and TensorFlow, which run in a Python environment.

[0694] The server generates and sends recommendation information to the device based on the user's preferences. This recommendation information includes tourist attractions at the travel destination, suitable times to visit, restaurant reservation availability, and content from video services. The device presents the information to the user in a visually easy-to-understand manner and, if necessary, provides a route to external information resources.

[0695] As a concrete example, consider a case where a user is planning a trip to Japan and is particularly interested in Kyoto. Based on this information, the server can create and present a list of Kyoto tourist spots, highly-rated Japanese restaurants, and even movies related to Japanese culture. An example of a prompt used might be, "Please suggest tourist spots that the user might be interested in."

[0696] This system enables the creation of an excellent user experience tailored to individual needs by providing users with information that is neither too much nor too little.

[0697] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0698] Step 1:

[0699] Users launch an application on their smartphone or tablet and enter personal and preference information through the interface. This information includes travel destinations and entertainment preferences. This information is formatted by the device and prepared for the next processing step. The entered information is then sent directly to the server and used as foundational data to understand the user's needs.

[0700] Step 2:

[0701] The terminal sends data entered by the user to the server using the HTTPS protocol. This input consists of the user's personal and preference data, which is sent to the server. This data reaches the server securely and is stored in a database. The output is then prepared as stored user data for use in subsequent processing.

[0702] Step 3:

[0703] The server creates a user profile in the database based on the received user information. During this profile creation process, the data is structured to reflect the user's personality and interests. The input is the stored user data, and the output is the constructed profile information. This profile is used for further analysis of the user's needs and for generating recommendations.

[0704] Step 4:

[0705] The server collects relevant information from external sources based on the user profile. This process utilizes the internet and various APIs to obtain data on tourist attractions, restaurants, and video content. The server uses the profile as input and obtains relevant information as output. This information is then prepared for further advanced analysis using generative AI.

[0706] Step 5:

[0707] The server analyzes the collected data using generative AI to generate recommendations tailored to the user's preferences. Specifically, it runs machine learning models using Python and libraries such as Scikit-learn and TensorFlow to identify the most relevant information for the user. The input consists of external information and the user profile, and the output is specific recommendations. These recommendations are then formatted for presentation to the user.

[0708] Step 6:

[0709] The server sends generated recommendations to the device. The device receives this information and presents it to the user in a visually easy-to-understand format. The input here is the recommended information generated by the server, and the output is the on-screen display to the user. Furthermore, the device provides routes to external sites as needed, supporting the user in taking immediate action.

[0710] (Application Example 1)

[0711] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0712] In today's world, users find it difficult to select content and services that match their preferences and needs from a vast amount of information. Furthermore, as user preferences diversify, there is a need for technology that can efficiently provide individually tailored recommendations. To solve this problem, a system is needed that appropriately utilizes users' personal data and provides information quickly and accurately based on that data.

[0713] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0714] In this invention, the server includes means for operating a device that provides an interface for inputting user information to acquire the user's personal data and preference data; means for transmitting the acquired user information to a data processing device and generating a user profile; and means for collecting relevant data from external sources based on the user's preference data and analyzing it. This makes it possible for users to easily select content that suits their interests.

[0715] "User information" refers to personal data and preference data obtained by users through their devices.

[0716] An "interface" is a means of interaction between a user and a device for inputting user information.

[0717] "Device" refers to electronic equipment used for inputting and displaying user information.

[0718] A "data processing device" is a device that receives user information and generates a user profile based on that information.

[0719] A "user profile" is a collection of foundational data about a user, generated based on their personal data and preferences.

[0720] "External information sources" refer to external data sources or services used to collect relevant data based on user preference data.

[0721] A "generative model" refers to artificial intelligence technology used to generate suggestions tailored to the user's preferences.

[0722] A "suggestion" is a selection of recommended content or services presented to the user using a generative model.

[0723] "External resources" refer to the services and data linked to and accessible based on the proposal.

[0724] "Response" refers to the reaction or feedback that a user provides to a proposed suggestion.

[0725] "Model" refers to the learning algorithm in a generative model that is updated in response to user feedback.

[0726] "Viewing provision services" refer to video and audio content distribution services used to provide users with appropriate content.

[0727] The system for carrying out this invention has a configuration that combines a user terminal, a server, and a generation AI model. First, the user uses a user terminal such as a smartphone or tablet to launch a specific application. Here, the user can input personal information and preference information through the interface. This information is immediately transmitted from the terminal to a server for data processing.

[0728] The server generates a user profile based on the received user information. This profile is generated based on the user's interests and needs and forms the core for providing personalized suggestions. Next, the server uses this profile to collect necessary data through external sources and APIs.

[0729] Based on the collected data, the server inputs the data into a generative model and generates the most suitable suggestions for the user. This generative model uses technology such as OpenAI. The generated suggestions are presented to the user's terminal in a visually easy-to-understand format. By selecting the presented content, the user can smoothly access external resources. This system allows users to efficiently and accurately obtain information that matches their interests from a vast amount of information.

[0730] For example, if a user is interested in "action movies" and "Japanese culture," the server can search for relevant content from related streaming services and suggest titles such as "The Last Samurai" or "47 Ronin." If the user expresses interest, a link to immediately begin watching is also provided. An example of a prompt to input into the generating AI model would be, "Based on the user profile, please recommend content related to action movies and Japanese culture."

[0731] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0732] Step 1:

[0733] The device inputs user information via an application. The user enters personal and preference information into the interface, which the device converts into a digital format and sends to the server. The input information is output as personal data.

[0734] Step 2:

[0735] The server generates a user profile based on user information received from the terminal. This profile is stored in a database. During this process, the server analyzes the data and extracts specific patterns related to the user's interests and preferences. The profile is output as an analysis result generated from the user data.

[0736] Step 3:

[0737] The server collects relevant data from external sources and APIs based on the user profile. Specifically, it searches for and retrieves information on content that matches the user's preferences. The collected data is output as information obtained from external sources.

[0738] Step 4:

[0739] The server inputs the collected data into an AI model to generate suggestions. Here, the AI ​​model analyzes the data using a prompt to generate optimal suggestions based on the user's preferences. This prompt is: "Based on the user profile, please recommend action movies and content related to Japanese culture." The generated suggestions are output as the AI ​​analysis results.

[0740] Step 5:

[0741] The server sends the generated suggestions to the terminal and presents them to the user. The terminal displays these suggestions in a visually easy-to-understand format, allowing the user to make a selection. This information is output as a list of available content.

[0742] Step 6:

[0743] The user selects a suggested option and uses a link to an external resource, such as a viewing service. The device opens the selected link and begins providing the actual service. The action taken based on the user's selection is output.

[0744] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0745] The system implementing this invention acquires not only the user's personal information and preference information, but also the user's emotional state, and provides optimal recommendations based on this information. To achieve this, the terminal provides an input interface for user information and performs emotion recognition using an emotion engine. The server then comprehensively analyzes this information and provides the user with individualized and optimized suggestions.

[0746] Users open the application using their device and enter personal information, including their travel destination and entertainment preferences. Furthermore, devices equipped with an emotion engine recognize emotions in real time from the user's voice, facial expressions, and input actions, and send this data to a server. Emotion recognition is crucial for determining the optimal state of mind for users to enjoy their travel destination and content.

[0747] When the server receives information sent from the terminal, it creates a user profile in the database and also records sentiment information. Next, based on the profile information and sentiment data, it collects relevant data from external sources. This data includes information on tourist attractions and restaurants in travel destinations, as well as content from video streaming services.

[0748] The AI ​​analyzes this data and generates recommendations best suited to the user's current emotional state. For example, if the user wants to relax, it might suggest relaxing tourist destinations or heartwarming movies. These recommendations are sent to the device and presented to the user in an easy-to-understand visual format.

[0749] This system also includes a feedback function, allowing users to input their thoughts and opinions via their devices after a trip or using content. The server can then update its AI model based on this feedback, improving the accuracy of future recommendations.

[0750] For example, if a user is planning a trip to Scandinavia and is feeling stressed when using this system, the emotion engine will recognize this and the server may recommend a Scandinavian fjord cruise where the user can enjoy a peaceful natural environment. If the user is feeling down, the system can also recommend uplifting comedy movies from a streaming service.

[0751] Thus, the system according to the present invention provides comprehensive support that takes into account the user's emotions, thereby realizing a more fulfilling travel and entertainment experience.

[0752] The following describes the processing flow.

[0753] Step 1:

[0754] The user launches an application on their device and enters personal information and preferences regarding travel and entertainment. The device then activates an emotion engine that recognizes the user's current emotional state based on their voice, facial expressions, and input.

[0755] Step 2:

[0756] The device sends the recognized user's emotional data and entered personal information to the server. This allows the server to receive the basic data needed to create a comprehensive profile of the user.

[0757] Step 3:

[0758] The server creates a user profile based on the received user information and sentiment data. This profile records the user's preferences, interests, and current emotional state.

[0759] Step 4:

[0760] The server collects relevant travel information and content data from external sources based on the user's preferences and emotional state. It retrieves details about tourist attractions, restaurants, and video streaming services at the travel destination via an API.

[0761] Step 5:

[0762] Using generative AI, the server generates recommendations best suited to the user's emotional state from the collected data. Based on this emotional data, it analyzes what kinds of experiences and content the user enjoys most.

[0763] Step 6:

[0764] The server sends the generated recommendations to the device. The recommendations are presented visually and clearly on the device, designed to make it easy for the user to select them.

[0765] Step 7:

[0766] Users can use the provided recommendations to plan their trips or watch video content. They can also select recommendations that interest them and immediately book or start watching them via their device.

[0767] Step 8:

[0768] After a trip or entertainment experience, users enter feedback such as their impressions and ratings via their device. This feedback is also sent to the server.

[0769] Step 9:

[0770] The server analyzes user feedback and updates the AI ​​model. This update improves the accuracy and relevance of future recommendations. The feedback is used to improve the user experience in the future.

[0771] (Example 2)

[0772] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0773] Traditional information systems primarily rely on recommendations based on users' personal information and preferences, but they fail to consider the user's emotional state. Therefore, the challenge lies in enabling users to enjoy travel destinations and entertainment that best suit their mood at any given time.

[0774] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0775] In this invention, the server includes means for acquiring user emotional information and analyzing it using emotional recognition technology, means for collecting relevant data from external sources based on user preference information and emotional information, and means for generating recommendations that correspond to the user's preferences and emotions using generative AI technology. This enables optimal recommendations that correspond to the user's emotional state.

[0776] "User information" refers to a collection of data that includes user attribute information, preference information, and emotional information.

[0777] A "terminal" is a device used by a user to input information and to review the recommendations they receive.

[0778] A "server" is a central processing unit that receives and processes user information, generates recommendations, and sends them to the terminal.

[0779] "Emotion recognition technology" is a technology that analyzes a user's voice, facial expressions, input actions, etc., to infer the user's emotional state.

[0780] "Generative AI technology" is an artificial intelligence technology that generates optimal recommendations based on user preference and emotional information.

[0781] A "prompt" is an instruction or question used when generating recommendations for a generative AI.

[0782] "External information sources" refer to information services and databases used to collect relevant data based on user preferences and sentiments.

[0783] "Recommendations" refer to suggestions for travel destinations and content generated based on the user's preferences and emotional information.

[0784] "Feedback" refers to comments and opinions from users regarding recommendations, and is information used to improve the system.

[0785] The system implementing this invention aims to acquire not only user attribute information and preference information, but also emotional state, and to provide optimal recommendations based on these. To achieve this, hardware and software are used in combination as follows.

[0786] First, the terminal functions as a device for the user to input information. Smartphones and tablet devices fall into this category. Through the terminal, the user inputs attribute information and preference information, such as travel destination preferences and movie genres. The terminal is equipped with an emotion engine that recognizes the user's emotional state by analyzing their voice, facial expressions, and input actions in real time. The data thus obtained is securely transmitted to the server via a communication protocol.

[0787] As a central processing unit, the server receives data transmitted from terminals and creates or updates user profiles in the database. User profiles include attribute information, preference information, and the latest sentiment information. Based on this profile, the server accesses external information sources and collects highly relevant data. Specifically, this includes tourist information for travel destinations, food information, and content from video streaming services.

[0788] The generative AI model analyzes this information and generates recommendations best suited to the user's current emotional state. For example, if the user is seeking relaxation, it might suggest a travel plan that allows them to enjoy tranquil natural scenery. Or, if they need a boost of energy, it might recommend a cheerful comedy movie.

[0789] The generated recommendations are sent to the device and presented visually to the user. The user can review the recommendations and find more detailed information about topics that interest them. For example, a prompt might ask, "Please recommend a relaxing travel destination that suits my current mood."

[0790] Furthermore, after experiencing the provided recommendations, users can send feedback to the server via their device. The server analyzes this feedback and updates the generating AI model, thereby further improving the accuracy of future recommendations. In this way, the system of the present invention realizes comprehensive information provision that takes user emotions into consideration.

[0791] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0792] Step 1:

[0793] The user operates the terminal to input attribute and preference information. The terminal is equipped with an information input interface, where the user selects preferences such as travel destinations and movie genres. The entered information is temporarily stored on the terminal as text data.

[0794] Step 2:

[0795] The device uses its built-in emotion engine to recognize the user's emotional state in real time. The emotion engine analyzes voice and facial expressions using a voice analysis module and facial recognition software, calculating the user's emotions as numerical data. This emotion data is prepared as packet data along with the input information.

[0796] Step 3:

[0797] The terminal sends packet data containing user attribute information, preference information, and sentiment information to the server. A secure communication protocol is used to ensure data integrity and confidentiality. Upon arrival at the server, the transmitted data is decoded and used for further processing.

[0798] Step 4:

[0799] The server creates or updates user profiles based on the received information. Profile creation involves saving user attribute information, preference information, and sentiment information to a database. Once the database update is complete, the profile is used as the basis for subsequent data collection and analysis.

[0800] Step 5:

[0801] The server analyzes the user's profile and collects relevant data from external sources. Specifically, it obtains tourist information about travel destinations and content information from video streaming services from the internet. Web crawling technology and API access are used for this collection, and the collected data is temporarily stored.

[0802] Step 6:

[0803] The server analyzes collected data using a generative AI model and generates recommendations based on user preferences and emotions. The AI ​​model uses machine learning algorithms to determine the optimal travel plan or movie list, and the generated results are prepared as text and image data.

[0804] Step 7:

[0805] The server sends the generated recommendations to the device. The device visually displays the received recommendations, and the user reviews the content. The recommendations include links to more information, and the user can click on suggestions that interest them to learn more.

[0806] Step 8:

[0807] After experiencing the provided recommendations, users send their thoughts and opinions as feedback to the server via their device. This feedback may include text or selected data, which the server receives and stores.

[0808] Step 9:

[0809] The server analyzes collected user feedback and updates the generated AI model. This AI model update involves parameter adjustments based on feedback data to improve recommendation performance in subsequent uses. This feedback loop enhances the overall system adaptability and user satisfaction.

[0810] (Application Example 2)

[0811] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0812] Providing personalized content suggestions tailored to each user's individual preferences and emotions is not easy. In particular, there is a need to provide more accurate recommendations by taking into account the user's real-time emotional state. Traditional systems have struggled to fully meet users' current needs because they do not adequately utilize emotional information.

[0813] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0814] In this invention, the server includes means for operating a device that provides an interface for inputting user information to acquire the user's personal data and preference data; means for acquiring the user's emotional state using the device's emotion recognition sensor and transmitting the emotional information to a data processing device; and means for selecting relevant multimedia content from external information sources based on the emotional information and generating recommendations appropriate to the emotional state. This makes it possible to provide personalized recommendations that reflect the user's emotional state in real time.

[0815] "User information" refers to information that includes a user's personal data and preference data, and indicates the characteristics and preferences of an individual user.

[0816] An "interface" refers to the point of contact between a device or software that allows a user to input information into a system.

[0817] A "data processing device" refers to an electronic computer that receives and analyzes user input and emotional information.

[0818] An "emotion recognition sensor" refers to a device or technology that analyzes a user's voice and facial expressions to identify their emotional state.

[0819] "External information sources" refer to internet resources and databases from which the server obtains additional information for use in making recommendations.

[0820] "Multimedia content" refers to information that combines multiple media formats, such as video, audio, and text, and is intended to be presented to users as recommendations.

[0821] "Recommendation" refers to suggestions and recommendations generated based on the user's preferences and emotional state.

[0822] A system for carrying out this invention includes a terminal equipped with an interface for inputting user information. The user operates this terminal to input personal data and preference data. The terminal is equipped with an emotion recognition sensor that analyzes voice and facial expressions, thereby enabling the identification of the user's emotional state in real time. This acquired user information and emotion information is transmitted to a server using a data processing device.

[0823] The server creates a user profile based on the received information and generates personalized recommendations using generative AI. It collects and analyzes necessary multimedia content from external sources based on the user's preferences and emotions. For example, if the user wants to relax, it will recommend movies or music with relaxation effects.

[0824] The technologies used include emotion recognition software equipped with machine learning models that enable facial recognition and voice analysis, as well as application programming interfaces (APIs) implemented in Python and JavaScript to process information in conjunction with databases.

[0825] As a concrete example, if a user is experiencing stress, an emotion recognition sensor detects this, and the server sends a corresponding prompt to the AI. For instance, a possible prompt might read, "For a user whose current emotional state is 'relaxed,' please suggest some soothing video content." This makes it possible to suggest content that best matches the user's emotions.

[0826] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0827] Step 1:

[0828] The device acquires the user's personal and preference data through its interface. This input is done through text input and checkbox selection. The data is temporarily stored in local storage.

[0829] Step 2:

[0830] The device's emotion recognition sensor operates, analyzing the user's voice and facial expressions to recognize their emotional state. The acquired sensor data is processed by an algorithm to identify the user's emotional state in real time. The output is a defined emotion label such as "relaxed" or "stressed."

[0831] Step 3:

[0832] User input data and recognized emotional states are sent from the terminal to the server. Here, the data is transferred via a secure communication protocol (e.g., HTTPS). The server analyzes the received data and creates or updates the user profile.

[0833] Step 4:

[0834] The server uses a generative AI model to collect multimedia content from relevant external sources based on the user's preferences and emotional state. The input is the user profile and emotional labels, and the output is a list of recommended content.

[0835] Step 5:

[0836] The server analyzes multimedia content collected from external sources and generates recommendations best suited to the user's emotional state. Here, a generative AI model organizes the data based on prompt text and lists appropriate content.

[0837] Step 6:

[0838] The server sends the generated recommendations to the device and presents them to the user. The recommendations are displayed in the user interface so that the user can visually select them.

[0839] Step 7:

[0840] Users select from the presented recommendations, experience the content, and then send their feedback to the server via their device. The input consists of user feedback and evaluation information, while the output is an improved version of the AI ​​model.

[0841] Step 8:

[0842] The server collects user feedback and updates the AI ​​model to improve the accuracy of future recommendations. This ensures a continuous improvement in the user experience.

[0843] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0844] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0845] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0846] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0847] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0848] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0849] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0850] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0851] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0852] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0853] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0854] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0855] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0856] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0857] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0858] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0859] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0860] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0861] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0862] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0863] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0864] The following is further disclosed regarding the embodiments described above.

[0865] (Claim 1)

[0866] A means of obtaining a user's personal information and preference information by operating a terminal that provides an interface for inputting user information,

[0867] A means for sending the acquired user information to a server and creating a user profile,

[0868] A means of collecting relevant data from external sources based on user preference information and analyzing it,

[0869] A means of generating recommendations tailored to user preferences using generative AI,

[0870] A means of presenting recommendations to users and providing links to external sites,

[0871] A means of obtaining user feedback and updating the AI ​​model,

[0872] A system that includes this.

[0873] (Claim 2)

[0874] The system according to claim 1, comprising means for identifying and presenting information on a public wireless communication network at a travel destination based on information entered by the user.

[0875] (Claim 3)

[0876] The system according to claim 1, comprising means for selecting and presenting content from a contracted video streaming service based on the user's preferences.

[0877] "Example 1"

[0878] (Claim 1)

[0879] A means for operating a display device for inputting user information and obtaining the user's personal information and preference information,

[0880] A means for transmitting the acquired user information to a processing device and creating a user profile,

[0881] A means of collecting relevant information data from external sources based on user preference information and analyzing it,

[0882] A means for generating recommendation information tailored to user preferences using generative artificial intelligence,

[0883] A means of presenting generated recommendation information to the user and providing a path to external information resources,

[0884] A means of obtaining user ratings and updating the artificial intelligence model,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, comprising means for identifying public wireless communication network information at a travel destination based on information entered by the user and presenting it to the user.

[0888] (Claim 3)

[0889] The system according to claim 1, comprising means for presenting visual content selected from a contracted video streaming service based on the user's preferences.

[0890] "Application Example 1"

[0891] (Claim 1)

[0892] A means for obtaining a user's personal data and preference data by operating a device that provides an interface for inputting user information,

[0893] A means for transmitting the acquired user information to a data processing device and generating a user profile,

[0894] A means of collecting relevant data from external sources based on user preference data and analyzing it,

[0895] A means of generating suggestions tailored to user preferences using a generative model,

[0896] A means of presenting suggestions to users and providing links to external resources,

[0897] A means of obtaining user responses and updating the model,

[0898] A means of selecting and presenting content from viewing services based on the user's viewing interests,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, comprising means for identifying and presenting wireless communication network information of a destination based on user input information.

[0902] (Claim 3)

[0903] The system according to claim 1, comprising means for selecting and presenting content from viewing services based on user preferences.

[0904] "Example 2 of combining an emotion engine"

[0905] (Claim 1)

[0906] A means for operating a device for inputting user information to obtain user attribute information and preference information,

[0907] A means for transmitting the acquired user information to a processing device and creating a user profile,

[0908] A means of acquiring user emotional information and analyzing it using emotion recognition technology,

[0909] A means of collecting relevant data from external sources based on user preference information and sentiment information,

[0910] A means for generating recommendations that are tailored to the user's preferences and emotions using generative AI technology,

[0911] A means of presenting recommendations to users and providing links to external information,

[0912] A means of obtaining user feedback and updating the AI ​​model,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, comprising means for identifying and presenting destination network information based on user input.

[0916] (Claim 3)

[0917] The system according to claim 1, comprising means for selecting and presenting content from a video provision service based on the user's preferences and emotions.

[0918] "Application example 2 when combining with an emotional engine"

[0919] (Claim 1)

[0920] A means for obtaining a user's personal data and preference data by operating a device that provides an interface for inputting user information,

[0921] A means for transmitting the acquired user information to a data processing device and creating a user profile,

[0922] A means of collecting relevant data from external sources based on user preference data and analyzing it,

[0923] A means of generating recommendations tailored to user preferences using generative AI,

[0924] A means of presenting recommendations to users and providing links to external sites,

[0925] A means of obtaining user feedback and updating the AI ​​model,

[0926] A means for acquiring the user's emotional state using the device's emotion recognition sensor and transmitting the emotional information to a data processing device,

[0927] A means for selecting relevant multimedia content from external sources based on emotional information and generating recommendations appropriate to the emotional state,

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, comprising means for identifying and presenting telecommunications network information of a travel destination based on user input information and emotional state.

[0931] (Claim 3)

[0932] The system according to claim 1, comprising means for selecting and presenting visual content from a video streaming service being used, based on the user's preferences and emotional state. [Explanation of Symbols]

[0933] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining a user's personal information and preference information by operating a terminal that provides an interface for inputting user information, A means for sending the acquired user information to a server and creating a user profile, A means of collecting relevant data from external sources based on user preference information and analyzing it, A means of generating recommendations tailored to user preferences using generative AI, A means of presenting recommendations to users and providing links to external sites, A means of obtaining user feedback and updating the AI ​​model, A system that includes this.

2. The system according to claim 1, comprising means for identifying and presenting information on a public wireless communication network at a travel destination based on information entered by the user.

3. The system according to claim 1, comprising means for selecting and presenting content from a contracted video streaming service based on the user's preferences.

Images