system

Abstract

We provide the system. [Solution] Means for collecting user behavior information, A means for analyzing user interests based on the aforementioned behavioral information, Based on the aforementioned analysis results, a means for selecting and presenting information according to the user's interests, A means for receiving and reflecting evaluations of the aforementioned information in the analysis, 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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Modern travelers have limited means to obtain appropriate and personalized information in new destinations, and it is difficult to select appropriate tourist spots, stores, and services. Also, there is no guarantee that the acquired information matches their interests, and often a satisfactory experience cannot be obtained. Furthermore, the reliability of the acquired information and the protection of privacy are also important issues for users.

Means for Solving the Problems

[0005] This invention provides a system that collects user behavior information and analyzes user interests based on that information. It selects and presents personalized advertisements and travel information according to the analysis results, and further collects user evaluations of the presented information, reflecting them in the analysis. This provides individually tailored information. This enables a balance between reliable information delivery and privacy protection, thereby improving user satisfaction.

[0006] A "user" is a person who uses this system to receive information.

[0007] "Behavioral information" refers to data about a user's activities, including their location, past search history, and visit history.

[0008] "Interest" refers to the subjects or themes that users are interested in, and is inferred through the analysis of behavioral data.

[0009] "Analysis" is a data processing method used to identify users' interests based on their behavioral information.

[0010] "Information" includes content provided to users, such as advertisements, tourist destination-related information, ratings, and other related data.

[0011] "Evaluation" refers to the evaluation and feedback that users provide regarding the information they receive, and is used to improve the quality of information provided in the future.

[0012] Personalization refers to tailoring and providing information based on each user's individual interests and preferences.

[0013] "Privacy" refers to a system that protects users' personal data and behavioral information, and limits its use and sharing to the minimum necessary. [Brief explanation of the drawing]

[0014] [Figure 1]It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an 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 an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] 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.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention provides a method for constructing a system for providing individually tailored advertisements and tourist information to users while they are on the move. This system consists of terminal-side software that runs on the user's device and a server that processes and provides information.

[0036] First, the device collects user behavior information. This information includes location data, past search history, and visit history, as well as places and interests that the user has given prior permission to access. This reveals what kinds of places the user visits and what their interests are.

[0037] Next, the device securely transmits the collected information to the server. The server analyzes the received behavioral data and uses AI algorithms to identify the user's interests. This analysis process makes it possible to predict in advance what kind of information the user will want.

[0038] Based on the analysis results, the server generates personalized information for the user. This includes advertisements and information about tourist attractions that the user might be interested in. For example, a user who has previously shown interest in nature and outdoor activities will be given priority in receiving information about local nature parks.

[0039] The device provides this information to the user in real time. Users can receive information tailored to their interests in a timely manner, allowing them to smoothly select destinations and plan their activities.

[0040] Furthermore, users can provide feedback on the information provided. The device sends this feedback to the server, which then incorporates this information into subsequent analyses. This further improves the accuracy of the information and user satisfaction.

[0041] As a concrete example of its use, if a user visits an unfamiliar city, the device can provide information on city-specific tourist attractions and events, helping them to adjust their travel plans. Furthermore, if a user wishes to shop, the server can provide information on new products and sales tailored to their preferences, enabling an optimal shopping experience.

[0042] In this way, the present invention provides users with the most relevant information, making activities involving movement more meaningful and comfortable.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] With the user's consent, the device periodically collects behavioral information such as location data, search history, and visit history. This provides basic data to understand the user's interests and behavioral patterns.

[0046] Step 2:

[0047] The device encrypts the behavioral information it collects and sends it to the server using a secure communication protocol. This is a step to ensure efficient data transmission while maintaining data confidentiality.

[0048] Step 3:

[0049] The server stores the received behavioral information in storage. Simultaneously, it uses an AI algorithm to analyze the behavioral data and generate a profile to infer the user's interests and needs.

[0050] Step 4:

[0051] Based on the profile analyzed by the server, information on advertisements and tourist destinations that match the user's interests is selected. The selected information is retrieved from a highly reliable database.

[0052] Step 5:

[0053] The server distributes the selected information to the terminal. The terminal displays the received information on the user interface, making it easy for the user to access.

[0054] Step 6:

[0055] Based on the information provided by the user, they input ratings and feedback on the places and services they actually visited into their device.

[0056] Step 7:

[0057] The device sends user feedback back to the server, which then uses this information in the next analysis step. This improves the information provision algorithm and enables further personalization.

[0058] (Example 1)

[0059] 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."

[0060] Modern information delivery systems struggle to provide users with relevant information in a timely manner. Furthermore, there is a need to effectively utilize users' behavioral history to identify their interests and generate personalized information based on those findings. However, privacy protection and secure data handling are often not adequately considered. It is necessary to address these challenges and build an information delivery system that is both useful and secure for users.

[0061] 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.

[0062] In this invention, the server includes a device having the function of collecting user behavior information, a device having the function of encrypting and transmitting the behavior information, and a device performing intelligent processing to analyze the user's interests based on the behavior information. This makes it possible to safely and effectively generate and present information that is highly relevant to the user.

[0063] A "user" is an individual or group that uses the information provision system to share behavioral information.

[0064] "Behavioral information" refers to a collection of data that indicates a user's activities and interests, such as location data, past information search history, and visit history.

[0065] "Device" refers to a part of a system that includes hardware or software for processing, transmitting, and receiving information.

[0066] "Encryption" is the process of transforming data using special algorithms to protect it from unauthorized external access.

[0067] "Intelligent processing" is the process of using AI technology to analyze user behavior information and identify their interests and concerns.

[0068] "Customized information" refers to information content that is specially generated based on the analyzed interests and preferences of the user.

[0069] An "information provision system" is a combination of hardware and software designed to generate and provide information based on users' interests and preferences.

[0070] This invention realizes an information provision system that provides personalized information to users. This system collects and analyzes user behavior information and generates and provides highly relevant information based on that information.

[0071] The device first collects user behavior information. Specifically, it records location data using GPS functionality and extracts past information search history and visit history using specific software. This data is collected with the user's permission and with full consideration given to protecting privacy. This process requires the device to have a location sensor and a local database.

[0072] Next, the device encrypts this data and sends it to the server via a secure communication protocol (e.g., HTTPS). This reduces the risk of unauthorized external access to the data.

[0073] The server analyzes the received behavioral information using AI technologies, including machine learning. This analysis utilizes specific AI algorithms and generative AI models. For example, natural language processing technology is used to understand the trends in keywords that the user has shown interest in in the past, and based on that, areas of interest are identified.

[0074] Based on the analysis results, the server generates customized information for the user and provides it through the terminal. This information includes advertisements and tourist destination-related information tailored to the user's interests, helping them make more informed decisions regarding their choices and activities.

[0075] For example, when a user visits a new region, information about local attractions and events is automatically displayed on the device screen. Based on this information, the user can plan their visit.

[0076] An example of a prompt message would be, "I enjoy outdoor activities, so could you recommend some nature parks in a new area?"

[0077] In this way, the present invention realizes a system that provides users with useful, safe, and relevant information in a timely manner.

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

[0079] Step 1:

[0080] The device collects user behavior information. Specifically, it uses the device's GPS function to record the user's current location and retrieves past information search history and visit history from a local database. The inputs here are the device sensors and the database, and the output is a set of location data and history information.

[0081] Step 2:

[0082] The device encrypts the collected behavioral information. It uses an encryption algorithm to transform the data and ensure security during transmission. The input is the collected raw data, and the output is encrypted data. This protects the data from unauthorized access.

[0083] Step 3:

[0084] The terminal sends encrypted data to the server. A secure protocol (e.g., HTTPS) is used for this communication. The input is encrypted data, and the output is a secure data transfer to the server. This ensures that the data reaches the server without loss.

[0085] Step 4:

[0086] The server analyzes the received behavioral information. Using generative AI models, it identifies areas of interest and concern based on the user's past behavior. The input is the received data, and the output is the analysis results indicating the user's interests. This analysis process involves matching data with a database and applying AI algorithms.

[0087] Step 5:

[0088] The server generates customized information based on the analysis results. This information includes advertisements and tourist destinations that may be of interest to the user. The input is the analysis results, and the output is personalized information for the user. Information generation includes data acquisition from content platforms.

[0089] Step 6:

[0090] The terminal provides users with information retrieved from the server in real time. This information is notified through the terminal's display function, allowing users to access it immediately. The input is information from the server, and the output is information displayed on the user's terminal. Users can decide on their actions based on the information they receive.

[0091] Step 7:

[0092] The user provides feedback on the information provided. The terminal collects this feedback and prepares to send it back to the server. The input is evaluation data from the user, and the output is feedback data to be sent to the server. This will be used to improve future analyses.

[0093] (Application Example 1)

[0094] 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."

[0095] By providing users with timely advertisements and tourist information tailored to their interests upon arrival at their destination, we address the lack of means to facilitate an effective experience.

[0096] 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.

[0097] In this invention, the server includes means for collecting user behavior information, means for analyzing the user's interests based on the behavior information, and means for providing advertisements using location information. This makes it possible to efficiently provide information tailored to the user's interests in real time.

[0098] A "user" is an individual who uses this system and provides behavioral information.

[0099] "Behavioral information" refers to a set of data that includes the user's location information, past search history, and visit history.

[0100] "Interests" refers to the user's interests and preferences identified through analysis.

[0101] "Location information" refers to geographical data that indicates where a user is currently located.

[0102] "Analysis" is the process of identifying users' interests based on collected behavioral data.

[0103] "Advertisements" are commercial information displayed according to the user's interests and location.

[0104] A "notification" is a message that provides information to users in real time.

[0105] A "server" is a computer that is responsible for data processing and information provision for the entire system.

[0106] The system for realizing this invention consists of a communication terminal, such as the user's smartphone, and a server that works in conjunction with it. An application is installed on the user's communication terminal, which collects behavioral information such as the user's location and past search history. This information collection is carried out with the user's permission, utilizing GPS sensors and application history data.

[0107] The behavioral information collected by the device is securely transmitted to a server via the internet connection, where it is received and analyzed. The analysis uses AI algorithms to identify the user's interests. Machine learning frameworks such as TENSORFLOW® and PyTorch can be used. Based on the analysis results, the server provides users with personalized advertisements and travel information in real time. Information is delivered using push notifications, providing timely notifications tailored to the user's interests and current location.

[0108] For example, when a user traveling reaches a specific tourist attraction, the server selects coupon information for restaurants and event information related to that location and notifies the user via their smartphone app. This allows the user to enjoy a more fulfilling travel experience.

[0109] An example of a prompt might be: "When the user arrives in Tokyo and has previously shown interest in Japanese food, trigger a generative AI model that provides promotional information for nearby Japanese restaurants." This approach allows the server to provide information tailored to the user's preferences.

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The device uses its GPS sensor to obtain the user's current location. The input is GPS data from the user's device, and the output is the user's latitude and longitude information. This information is used in the next step.

[0113] Step 2:

[0114] The device collects user behavior information. This includes past search history and visit history. The input is historical information from the application database inside the device, and the output is a dataset of the collected behavior information.

[0115] Step 3:

[0116] The device sends collected behavioral information and current location information to the server. Input is the data from steps 1 and 2, and output is the status indicating successful transmission to the server. An internet connection is used for communication.

[0117] Step 4:

[0118] The server analyzes the behavioral information it receives and uses an AI algorithm to identify the user's interests. The input is a dataset sent from the terminal, and the output is the analyzed user's interests and predicted information needs. TensorFlow or PyTorch is used as the machine learning framework.

[0119] Step 5:

[0120] The server generates personalized advertisements and tourist information tailored to the user based on the analysis results. The input is the user's interests presented from step 4, and the output is the specific advertisements and tourist spot information to be provided.

[0121] Step 6:

[0122] The server generates information and sends it to the device, which then provides it to the user via push notifications. The input is the information generated in step 5, and the output is a real-time notification displayed on the device. This notification allows the user to receive information tailored to their interests.

[0123] Step 7:

[0124] The user provides feedback on the information they have provided. The input is the user's feedback, and the output is this feedback data. This data is then sent back to the server from the terminal and used for future data analysis.

[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] This invention provides a system that delivers personalized information to users while they are on the move, and in particular, incorporates an emotion engine to provide information that takes into account the user's emotional state. This system operates through cooperation between a terminal and a server, efficiently collecting, analyzing, and providing user behavior and emotional information.

[0127] First, the device collects user behavior information. This information includes location data, past search history, and visit history, as well as data that reads emotions from voice, facial expressions, and input actions. This data is collected using an emotion engine built into the device, based on the user's consent.

[0128] Next, the device sends the collected data to the server. A secure and encrypted protocol is applied to ensure data confidentiality and rapid delivery to the server.

[0129] The server analyzes the received data and uses an AI algorithm to identify the user's interests and emotional state. This analysis allows, for example, a user who wants to relax while traveling to be offered suggestions for quiet tourist destinations with calming music.

[0130] Furthermore, the server selects appropriate advertisements and tourist information based on the user's profile. Emotional state is also considered, and the content and tone are adjusted accordingly. This process results in more effective and user-friendly information delivery.

[0131] Finally, the device provides the selected information to the user in real time. The user can then react immediately and decide on an action based on the information provided.

[0132] For example, if a user seeks stress reduction during a trip, the emotional engine senses this state and suggests a relaxing environment. For instance, it might recommend a quiet garden or spa, making the trip more enjoyable and satisfying. Similarly, users experiencing positive emotions while shopping can be provided with emotionally relevant information on new brands and special sales, supporting their purchasing intent.

[0133] Thus, by combining emotion engines, this invention achieves advanced personalization that takes into account the user's emotions, thereby improving the travel experience.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] The device collects user behavior and emotional data. This includes location information, past search history, visit history, and an emotion engine that analyzes the user's tone of voice, facial expressions, and input actions during use.

[0137] Step 2:

[0138] The device encrypts this data before sending it to the server. Encryption ensures fast and secure data transmission while protecting user privacy.

[0139] Step 3:

[0140] The server receives the data and uses AI algorithms to analyze the user's interests and emotional state. Based on the information from the emotion engine, it gains a detailed understanding of the user's mental state and preferences.

[0141] Step 4:

[0142] Based on the analysis results, the server selects advertisements and tourist information considering the user's current emotional state. For example, if the user is detected as wanting to relax, the server will prioritize selecting places where they can enjoy calming music or relaxation facilities.

[0143] Step 5:

[0144] The server delivers this information to the terminal. The terminal displays the information on the user's screen and adjusts notifications and presentations as needed. Efforts are made to ensure easy access for the user.

[0145] Step 6:

[0146] The system helps users make decisions based on the information provided. For example, it assists users in making choices such as visiting suggested tourist destinations or facilities.

[0147] Step 7:

[0148] Users input feedback on the usefulness and content of the information provided into their device. The device then sends this collected feedback back to the server for use in future analyses.

[0149] Step 8:

[0150] The server improves its analysis algorithm based on feedback and uses it to provide more accurate information in the future. This enables more precise personalization and improves user satisfaction.

[0151] (Example 2)

[0152] 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".

[0153] Traditional personalized information systems have limitations in providing suggestions based on user behavior data, making it difficult to provide information that takes into account the user's emotional state. As a result, users may not receive information that matches their current emotions, potentially leading to dissatisfaction and negatively impacting the quality of their user experience. Furthermore, providing information that does not consider emotional aspects makes it difficult to accurately reflect user interests, limiting the effectiveness of the system.

[0154] 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.

[0155] In this invention, the server includes means for collecting user behavior information and emotional state, means for analyzing the user's interests and emotions based on the behavior information and emotional state, and means for selecting and presenting information according to the user's interests and emotions based on the analysis results. This enables advanced personalization according to the user's emotional state, making it possible to provide information that is more satisfying.

[0156] "User behavior information" refers to location information, search history, visit history, and related data, and is information used to understand user activities in detail.

[0157] "Emotional state" refers to the psychological and emotional state of a user, estimated based on their voice, facial expressions, and other physiological responses.

[0158] "Analysis means" refers to a technical process that uses collected behavioral information and emotional states to understand users' interests and emotions and to gain insights for providing information.

[0159] "Presentation means" refers to a method or device for providing users with information selected based on the analysis results, either visually or audibly.

[0160] A "profile" refers to a set of information that aggregates data about a user, such as their attributes, past behavior, and preferences, and is used to provide personalized information.

[0161] An "emotion engine" refers to a technology that combines voice analysis tools, facial recognition technology, and other elements to analyze input from various sensors and identify the user's emotions.

[0162] This invention is a system that collects user behavior information and emotional state and provides personalized information based on that information. Specifically, it uses terminals and servers to achieve this.

[0163] The device collects user behavior information. This collection includes obtaining location information using GPS functionality, and collecting search and visit history using browser and app records. Furthermore, it utilizes an emotion engine on the device to identify emotional states by analyzing voice and facial expressions. This engine uses voice analysis tools and facial recognition technology to understand the user's current psychological state.

[0164] Next, the device securely transmits the collected data to the server using an encrypted protocol. TLS (Transport Layer Security) is used for this communication to ensure data confidentiality.

[0165] The server analyzes the received data using AI algorithms. Here, natural language processing techniques and machine learning models are utilized to identify the user's interests and emotional state. Based on the analysis results, various types of information are selected according to the user's profile, and the information is provided to the user in an appropriate content and tone.

[0166] Ultimately, the device presents the user with information provided by the server in real time. Users can receive this information through push notifications or in-app interfaces and take the suggested action immediately.

[0167] For example, users who want to reduce stress while traveling are provided with information on nearby quiet tourist spots and cafes. This information is selected based on the user's emotional state, as identified by the emotion engine. As another example, users who are shopping and in a positive emotional state are presented with information on new products and special sales, helping to increase their purchasing intent.

[0168] By utilizing generative AI models, it is possible to continuously improve the provision of optimal information to users using prompts. Examples of prompts include, "Suggest how to provide appropriate information to a user who wants to relax while traveling," and "Please provide criteria for selecting personalized advertisements based on the user's emotional state." Based on such concrete examples, the system will improve the user's travel experience.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] The device collects user behavior information and emotional states. As input, the device obtains location information using GPS, retrieves search history from browser history, and collects visit history from applications. Furthermore, using the camera and microphone, an emotion engine extracts emotional data based on voice and facial expressions. By collecting this data, the device forms a framework of the user's overall behavioral patterns and emotional trends. As output, this data is ready to be sent to the next step.

[0172] Step 2:

[0173] The device sends the collected data to the server. The input consists of location information, search history, visit history, and sentiment data based on voice and facial expressions, collected in step 1. The data is securely transmitted using encryption protocols such as TLS. In actual operation, the data is batched and sent periodically (e.g., every 10 minutes). The output is the data arriving at the server in encrypted form.

[0174] Step 3:

[0175] The server analyzes the received data to identify the user's interests and emotional state. It receives location information, search history, visit history, and emotional data from the terminal as input. Data processing and computation apply natural language processing techniques and machine learning models to identify the user's current interests and emotional state. Specifically, emotional data is used for emotional level scoring, and interest data is classified using clustering algorithms. The output is the analysis result based on the identified interests and emotional state.

[0176] Step 4:

[0177] The server selects information based on the analysis results and generates optimized content. The analysis results obtained in step 3 are used as input. The selection process considers the target user's profile, choosing information that is highly relevant and appropriate to their emotional state. Specifically, it selects information such as relaxing places and special sale information, and adjusts the suggestions according to the user's emotional state. The output is a set of information to be presented to the user, such as navigation information and advertising information.

[0178] Step 5:

[0179] The device provides optimized information to the user in real time. The input is a set of information sent from the server. This is provided through specific UI activities, such as displaying it as a push notification on the user's device interface. The user can review the information and decide on an action based on the suggested information. The output is the user's action, for example, deciding which tourist destination to visit.

[0180] (Application Example 2)

[0181] 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".

[0182] Modern consumers are surrounded by a wealth of information and expect services tailored to their individual preferences and emotions. However, traditional systems struggle to provide information that responds to users' instantaneous emotional states, leading to challenges such as decreased purchasing intent and difficulty in improving the quality of the user experience.

[0183] 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.

[0184] In this invention, the server includes means for collecting user behavior information and emotional information, means for analyzing the user's interests and emotional state, and means for selecting and presenting information according to the user's interests and emotional state. This enables the real-time provision of personalized information that is appropriate to the user's instantaneous emotions.

[0185] "User behavior information" refers to data that indicates user behavior, obtained from location information, past search history, visit history, etc.

[0186] "Emotional information" refers to data that indicates the emotional state of a user, obtained through their facial expressions, voice, and other means.

[0187] "Means of analysis" refers to technologies that analyze collected behavioral and emotional information to identify users' interests and emotional states.

[0188] "Means of selection and presentation" refers to technologies for appropriately selecting information that matches the user's interests and emotional state, and providing it to the user visually or aurally.

[0189] "Means for receiving evaluations and reflecting them in analysis" refers to technologies that receive feedback from users, utilize it in subsequent analyses, and aim to provide more accurate information.

[0190] To implement this invention, a smart pair of glasses that can be worn by the user and a server for analyzing data are used.

[0191] The server collects and analyzes behavioral and emotional information in real time. Specifically, location information, past search history, visit history, and facial and voice data acquired by the smart glasses are sent from the device to the server via a secure protocol (e.g., HTTPS). The server uses an emotion analysis engine and AI algorithms to analyze the user's current interests and emotional state.

[0192] Based on the analysis results obtained, product information and service recommendations tailored to the user's interests and emotional state are generated and presented to the user through smart glasses. In this process, the server overlays the recommendation information onto the user's visual display, allowing them to intuitively receive the information.

[0193] For example, if a user is smiling while looking at an item they're interested in in a store, the smart glasses will display detailed information and sale information about that item in real time. Furthermore, if a user voice-initiates a prompt such as "Tell me what's on sale," a generative AI model will select and present the most relevant information. This allows users to instantly obtain information that aligns with their actions and emotions, enhancing their shopping experience.

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The device collects user behavior and emotional information in real time. This includes location information, past search history, visit history, and facial and voice data obtained via smart glasses. It takes raw data as input, processes it to infer emotional states using an emotion engine, and outputs the data ready for analysis.

[0197] Step 2:

[0198] The terminal securely transmits the collected data to the server. Here, the HTTPS encryption protocol is used to protect the data from interception, while outputting it to the server-side analysis module. This output includes all the data points necessary for analysis.

[0199] Step 3:

[0200] The server receives the transmitted data and activates its sentiment analysis engine and AI algorithms. This identifies the user's interests and emotional state. Based on the input data, it outputs analysis results with identified interest and emotion values. In this analysis process, a machine learning model identifies data patterns, and a generative AI model predicts the next information that is relevant to the user.

[0201] Step 4:

[0202] The server generates recommendation information tailored to the user's interests and emotional state based on the analysis results. Here, it searches the database for appropriate product and service information and outputs the selected information. This generated information includes the content and format in which it is displayed.

[0203] Step 5:

[0204] The server sends the recommended information back to the terminal, which then presents it to the user. In the case of smart glasses, the information is overlaid on the visual display, allowing the user to intuitively understand the recommendations. Here, the recommended information is displayed visually as digital content. The goal is to display the outputted information in real time and reflect it in the user interface.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] [Second Embodiment]

[0209] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0210] 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.

[0211] 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).

[0212] 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.

[0213] 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.

[0214] 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).

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] 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".

[0221] This invention provides a method for constructing a system for providing individually tailored advertisements and tourist information to users while they are on the move. This system consists of terminal-side software that runs on the user's device and a server that processes and provides information.

[0222] First, the device collects user behavior information. This information includes location data, past search history, and visit history, as well as places and interests that the user has given prior permission to access. This reveals what kinds of places the user visits and what their interests are.

[0223] Next, the device securely transmits the collected information to the server. The server analyzes the received behavioral data and uses AI algorithms to identify the user's interests. This analysis process makes it possible to predict in advance what kind of information the user will want.

[0224] Based on the analysis results, the server generates personalized information for the user. This includes advertisements and information about tourist attractions that the user might be interested in. For example, a user who has previously shown interest in nature and outdoor activities will be given priority in receiving information about local nature parks.

[0225] The device provides this information to the user in real time. Users can receive information tailored to their interests in a timely manner, allowing them to smoothly select destinations and plan their activities.

[0226] Furthermore, users can provide feedback on the information provided. The device sends this feedback to the server, which then incorporates this information into subsequent analyses. This further improves the accuracy of the information and user satisfaction.

[0227] As a concrete example of its use, if a user visits an unfamiliar city, the device can provide information on city-specific tourist attractions and events, helping them to adjust their travel plans. Furthermore, if a user wishes to shop, the server can provide information on new products and sales tailored to their preferences, enabling an optimal shopping experience.

[0228] In this way, the present invention provides users with the most relevant information, making activities involving movement more meaningful and comfortable.

[0229] The following describes the processing flow.

[0230] Step 1:

[0231] With the user's consent, the device periodically collects behavioral information such as location data, search history, and visit history. This provides basic data to understand the user's interests and behavioral patterns.

[0232] Step 2:

[0233] The device encrypts the behavioral information it collects and sends it to the server using a secure communication protocol. This is a step to ensure efficient data transmission while maintaining data confidentiality.

[0234] Step 3:

[0235] The server stores the received behavioral information in storage. Simultaneously, it uses an AI algorithm to analyze the behavioral data and generate a profile to infer the user's interests and needs.

[0236] Step 4:

[0237] Based on the profile analyzed by the server, information on advertisements and tourist destinations that match the user's interests is selected. The selected information is retrieved from a highly reliable database.

[0238] Step 5:

[0239] The server distributes the selected information to the terminal. The terminal displays the received information on the user interface, making it easy for the user to access.

[0240] Step 6:

[0241] Based on the information provided by the user, they input ratings and feedback on the places and services they actually visited into their device.

[0242] Step 7:

[0243] The device sends user feedback back to the server, which then uses this information in the next analysis step. This improves the information provision algorithm and enables further personalization.

[0244] (Example 1)

[0245] 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."

[0246] Modern information delivery systems struggle to provide users with relevant information in a timely manner. Furthermore, there is a need to effectively utilize users' behavioral history to identify their interests and generate personalized information based on those findings. However, privacy protection and secure data handling are often not adequately considered. It is necessary to address these challenges and build an information delivery system that is both useful and secure for users.

[0247] 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.

[0248] In this invention, the server includes a device having the function of collecting user behavior information, a device having the function of encrypting and transmitting the behavior information, and a device performing intelligent processing to analyze the user's interests based on the behavior information. This makes it possible to safely and effectively generate and present information that is highly relevant to the user.

[0249] A "user" is an individual or group that uses the information provision system to share behavioral information.

[0250] "Behavioral information" refers to a collection of data that indicates a user's activities and interests, such as location data, past information search history, and visit history.

[0251] "Device" refers to a part of a system that includes hardware or software for processing, transmitting, and receiving information.

[0252] "Encryption" is the process of transforming data using special algorithms to protect it from unauthorized external access.

[0253] "Intelligent processing" is the process of using AI technology to analyze user behavior information and identify their interests and concerns.

[0254] "Customized information" refers to information content that is specially generated based on the analyzed interests and preferences of the user.

[0255] An "information provision system" is a combination of hardware and software designed to generate and provide information based on users' interests and preferences.

[0256] This invention realizes an information provision system that provides personalized information to users. This system collects and analyzes user behavior information and generates and provides highly relevant information based on that information.

[0257] The device first collects user behavior information. Specifically, it records location data using GPS functionality and extracts past information search history and visit history using specific software. This data is collected with the user's permission and with full consideration given to protecting privacy. This process requires the device to have a location sensor and a local database.

[0258] Next, the device encrypts this data and sends it to the server via a secure communication protocol (e.g., HTTPS). This reduces the risk of unauthorized external access to the data.

[0259] The server analyzes the received behavioral information using AI technologies, including machine learning. This analysis utilizes specific AI algorithms and generative AI models. For example, natural language processing technology is used to understand the trends in keywords that the user has shown interest in in the past, and based on that, areas of interest are identified.

[0260] Based on the analysis results, the server generates customized information for the user and provides it through the terminal. This information includes advertisements and tourist destination-related information tailored to the user's interests, helping them make more informed decisions regarding their choices and activities.

[0261] For example, when a user visits a new region, information about local attractions and events is automatically displayed on the device screen. Based on this information, the user can plan their visit.

[0262] An example of a prompt message would be, "I enjoy outdoor activities, so could you recommend some nature parks in a new area?"

[0263] In this way, the present invention realizes a system that provides users with useful, safe, and relevant information in a timely manner.

[0264] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0265] Step 1:

[0266] The device collects user behavior information. Specifically, it uses the device's GPS function to record the user's current location and retrieves past information search history and visit history from a local database. The inputs here are the device sensors and the database, and the output is a set of location data and history information.

[0267] Step 2:

[0268] The device encrypts the collected behavioral information. It uses an encryption algorithm to transform the data and ensure security during transmission. The input is the collected raw data, and the output is encrypted data. This protects the data from unauthorized access.

[0269] Step 3:

[0270] The terminal sends encrypted data to the server. A secure protocol (e.g., HTTPS) is used for this communication. The input is encrypted data, and the output is a secure data transfer to the server. This ensures that the data reaches the server without loss.

[0271] Step 4:

[0272] The server analyzes the received behavioral information. Using generative AI models, it identifies areas of interest and concern based on the user's past behavior. The input is the received data, and the output is the analysis results indicating the user's interests. This analysis process involves matching data with a database and applying AI algorithms.

[0273] Step 5:

[0274] The server generates customized information based on the analysis results. This information includes advertisements and tourist destinations that may be of interest to the user. The input is the analysis results, and the output is personalized information for the user. Information generation includes data acquisition from content platforms.

[0275] Step 6:

[0276] The terminal provides users with information retrieved from the server in real time. This information is notified through the terminal's display function, allowing users to access it immediately. The input is information from the server, and the output is information displayed on the user's terminal. Users can decide on their actions based on the information they receive.

[0277] Step 7:

[0278] The user inputs feedback on the provided information. The terminal prepares to collect this feedback and send it back to the server. The input is evaluation data from the user, and the output is feedback data for transmission to the server. This can be used for subsequent analysis.

[0279] (Application Example 1)

[0280] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0281] By timely providing advertisements and tourism information according to the interests of users who have arrived at the local area, it solves the shortage of means to promote an effective experience.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0283] In this invention, the server includes means for collecting the behavior information of the user, means for analyzing the interests of the user based on the behavior information, and means for providing advertisements using the location information. This makes it possible to efficiently provide information in real time according to the interests of the user.

[0284] The "user" is an individual who uses this system and provides behavior information.

[0285] The "behavior information" is a data group including the location information of the user, past search history, visit history, etc.

[0286] "Interest" refers to the concerns and preferences of the user identified by analysis.

[0287] The "location information" is geographical data indicating where the user is currently located.

[0288] "Analysis" is the process of identifying users' interests based on collected behavioral data.

[0289] "Advertisements" are commercial information displayed according to the user's interests and location.

[0290] A "notification" is a message that provides information to users in real time.

[0291] A "server" is a computer that is responsible for data processing and information provision for the entire system.

[0292] The system for realizing this invention consists of a communication terminal, such as the user's smartphone, and a server that works in conjunction with it. An application is installed on the user's communication terminal, which collects behavioral information such as the user's location and past search history. This information collection is carried out with the user's permission, utilizing GPS sensors and application history data.

[0293] The behavioral information collected by the device is securely transmitted to a server via the internet connection, where it is received and analyzed. The analysis uses AI algorithms to identify the user's interests. Machine learning frameworks such as TensorFlow and PyTorch can be used. Based on the analysis results, the server provides users with personalized advertisements and travel information in real time. Information is delivered using push notifications, providing timely notifications tailored to the user's interests and current location.

[0294] For example, when a user traveling reaches a specific tourist attraction, the server selects coupon information for restaurants and event information related to that location and notifies the user via their smartphone app. This allows the user to enjoy a more fulfilling travel experience.

[0295] An example of a prompt might be: "When the user arrives in Tokyo and has previously shown interest in Japanese food, trigger a generative AI model that provides promotional information for nearby Japanese restaurants." This approach allows the server to provide information tailored to the user's preferences.

[0296] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0297] Step 1:

[0298] The device uses its GPS sensor to obtain the user's current location. The input is GPS data from the user's device, and the output is the user's latitude and longitude information. This information is used in the next step.

[0299] Step 2:

[0300] The device collects user behavior information. This includes past search history and visit history. The input is historical information from the application database inside the device, and the output is a dataset of the collected behavior information.

[0301] Step 3:

[0302] The device sends collected behavioral information and current location information to the server. Input is the data from steps 1 and 2, and output is the status indicating successful transmission to the server. An internet connection is used for communication.

[0303] Step 4:

[0304] The server analyzes the behavioral information it receives and uses an AI algorithm to identify the user's interests. The input is a dataset sent from the terminal, and the output is the analyzed user's interests and predicted information needs. TensorFlow or PyTorch is used as the machine learning framework.

[0305] Step 5:

[0306] Based on the analysis results, the server generates personalized advertisements and tourism information suitable for the user. The input is the user's interests presented in Step 4, and the output is the specific advertisements and tourism spot information to be provided.

[0307] Step 6:

[0308] The server transmits the information generated to the terminal, and the terminal provides it to the user using push notifications. The input is the information generated in Step 5, and the output is the real-time notification displayed on the terminal. Through this notification, the user can receive information in line with their interests.

[0309] Step 7:

[0310] The user gives feedback on the provided information. The input is the feedback from the user, and the output is this feedback data. It is transmitted from the terminal back to the server and reflected in future data analysis.

[0311] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions.

[0312] The present invention is a system that provides personalized information to users while they are on the move, and in particular, is configured to provide information considering the user's emotional state by incorporating an emotion engine. This system is established through the cooperation between the terminal and the server, and efficiently collects, analyzes, and provides the user's behavior information and emotional information.

[0313] First, the terminal collects the user's behavior information. This information includes location information, past search history, visit history, as well as data for reading emotions from voice, expressions, and input operations. These data are collected based on the user's consent, utilizing the emotion engine incorporated in the terminal.

[0314] Next, the device sends the collected data to the server. A secure and encrypted protocol is applied to ensure data confidentiality and rapid delivery to the server.

[0315] The server analyzes the received data and uses an AI algorithm to identify the user's interests and emotional state. This analysis allows, for example, a user who wants to relax while traveling to be offered suggestions for quiet tourist destinations with calming music.

[0316] Furthermore, the server selects appropriate advertisements and tourist information based on the user's profile. Emotional state is also considered, and the content and tone are adjusted accordingly. This process results in more effective and user-friendly information delivery.

[0317] Finally, the device provides the selected information to the user in real time. The user can then react immediately and decide on an action based on the information provided.

[0318] For example, if a user seeks stress reduction during a trip, the emotional engine senses this state and suggests a relaxing environment. For instance, it might recommend a quiet garden or spa, making the trip more enjoyable and satisfying. Similarly, users experiencing positive emotions while shopping can be provided with emotionally relevant information on new brands and special sales, supporting their purchasing intent.

[0319] Thus, by combining emotion engines, this invention achieves advanced personalization that takes into account the user's emotions, thereby improving the travel experience.

[0320] The following describes the processing flow.

[0321] Step 1:

[0322] The device collects user behavior and emotional data. This includes location information, past search history, visit history, and an emotion engine that analyzes the user's tone of voice, facial expressions, and input actions during use.

[0323] Step 2:

[0324] The device encrypts this data before sending it to the server. Encryption ensures fast and secure data transmission while protecting user privacy.

[0325] Step 3:

[0326] The server receives the data and uses AI algorithms to analyze the user's interests and emotional state. Based on the information from the emotion engine, it gains a detailed understanding of the user's mental state and preferences.

[0327] Step 4:

[0328] Based on the analysis results, the server selects advertisements and tourist information considering the user's current emotional state. For example, if the user is detected as wanting to relax, the server will prioritize selecting places where they can enjoy calming music or relaxation facilities.

[0329] Step 5:

[0330] The server delivers this information to the terminal. The terminal displays the information on the user's screen and adjusts notifications and presentations as needed. Efforts are made to ensure easy access for the user.

[0331] Step 6:

[0332] The system helps users make decisions based on the information provided. For example, it assists users in making choices such as visiting suggested tourist destinations or facilities.

[0333] Step 7:

[0334] Users input feedback on the usefulness and content of the information provided into their device. The device then sends this collected feedback back to the server for use in future analyses.

[0335] Step 8:

[0336] The server improves its analysis algorithm based on feedback and uses it to provide more accurate information in the future. This enables more precise personalization and improves user satisfaction.

[0337] (Example 2)

[0338] 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".

[0339] Traditional personalized information systems have limitations in providing suggestions based on user behavior data, making it difficult to provide information that takes into account the user's emotional state. As a result, users may not receive information that matches their current emotions, potentially leading to dissatisfaction and negatively impacting the quality of their user experience. Furthermore, providing information that does not consider emotional aspects makes it difficult to accurately reflect user interests, limiting the effectiveness of the system.

[0340] 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.

[0341] In this invention, the server includes means for collecting user behavior information and emotional state, means for analyzing the user's interests and emotions based on the behavior information and emotional state, and means for selecting and presenting information according to the user's interests and emotions based on the analysis results. This enables advanced personalization according to the user's emotional state, making it possible to provide information that is more satisfying.

[0342] "User behavior information" refers to location information, search history, visit history, and related data, and is information used to understand user activities in detail.

[0343] "Emotional state" refers to the psychological and emotional state of a user, estimated based on their voice, facial expressions, and other physiological responses.

[0344] "Analysis means" refers to a technical process that uses collected behavioral information and emotional states to understand users' interests and emotions and to gain insights for providing information.

[0345] "Presentation means" refers to a method or device for providing users with information selected based on the analysis results, either visually or audibly.

[0346] A "profile" refers to a set of information that aggregates data about a user, such as their attributes, past behavior, and preferences, and is used to provide personalized information.

[0347] An "emotion engine" refers to a technology that combines voice analysis tools, facial recognition technology, and other elements to analyze input from various sensors and identify the user's emotions.

[0348] This invention is a system that collects user behavior information and emotional state and provides personalized information based on that information. Specifically, it uses terminals and servers to achieve this.

[0349] The device collects user behavior information. This collection includes obtaining location information using GPS functionality, and collecting search and visit history using browser and app records. Furthermore, it utilizes an emotion engine on the device to identify emotional states by analyzing voice and facial expressions. This engine uses voice analysis tools and facial recognition technology to understand the user's current psychological state.

[0350] Next, the device securely transmits the collected data to the server using an encrypted protocol. TLS (Transport Layer Security) is used for this communication to ensure data confidentiality.

[0351] The server analyzes the received data using AI algorithms. Here, natural language processing techniques and machine learning models are utilized to identify the user's interests and emotional state. Based on the analysis results, various types of information are selected according to the user's profile, and the information is provided to the user in an appropriate content and tone.

[0352] Ultimately, the device presents the user with information provided by the server in real time. Users can receive this information through push notifications or in-app interfaces and take the suggested action immediately.

[0353] For example, users who want to reduce stress while traveling are provided with information on nearby quiet tourist spots and cafes. This information is selected based on the user's emotional state, as identified by the emotion engine. As another example, users who are shopping and in a positive emotional state are presented with information on new products and special sales, helping to increase their purchasing intent.

[0354] By utilizing generative AI models, it is possible to continuously improve the provision of optimal information to users using prompts. Examples of prompts include, "Suggest how to provide appropriate information to a user who wants to relax while traveling," and "Please provide criteria for selecting personalized advertisements based on the user's emotional state." Based on such concrete examples, the system will improve the user's travel experience.

[0355] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0356] Step 1:

[0357] The device collects user behavior information and emotional states. As input, the device obtains location information using GPS, retrieves search history from browser history, and collects visit history from applications. Furthermore, using the camera and microphone, an emotion engine extracts emotional data based on voice and facial expressions. By collecting this data, the device forms a framework of the user's overall behavioral patterns and emotional trends. As output, this data is ready to be sent to the next step.

[0358] Step 2:

[0359] The device sends the collected data to the server. The input consists of location information, search history, visit history, and sentiment data based on voice and facial expressions, collected in step 1. The data is securely transmitted using encryption protocols such as TLS. In actual operation, the data is batched and sent periodically (e.g., every 10 minutes). The output is the data arriving at the server in encrypted form.

[0360] Step 3:

[0361] The server analyzes the received data to identify the user's interests and emotional state. It receives location information, search history, visit history, and emotional data from the terminal as input. Data processing and computation apply natural language processing techniques and machine learning models to identify the user's current interests and emotional state. Specifically, emotional data is used for emotional level scoring, and interest data is classified using clustering algorithms. The output is the analysis result based on the identified interests and emotional state.

[0362] Step 4:

[0363] The server selects information based on the analysis results and generates optimized content. The analysis results obtained in step 3 are used as input. The selection process considers the target user's profile, choosing information that is highly relevant and appropriate to their emotional state. Specifically, it selects information such as relaxing places and special sale information, and adjusts the suggestions according to the user's emotional state. The output is a set of information to be presented to the user, such as navigation information and advertising information.

[0364] Step 5:

[0365] The device provides optimized information to the user in real time. The input is a set of information sent from the server. This is provided through specific UI activities, such as displaying it as a push notification on the user's device interface. The user can review the information and decide on an action based on the suggested information. The output is the user's action, for example, deciding which tourist destination to visit.

[0366] (Application Example 2)

[0367] 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."

[0368] Modern consumers are surrounded by a wealth of information and expect services tailored to their individual preferences and emotions. However, traditional systems struggle to provide information that responds to users' instantaneous emotional states, leading to challenges such as decreased purchasing intent and difficulty in improving the quality of the user experience.

[0369] 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.

[0370] In this invention, the server includes means for collecting user behavior information and emotional information, means for analyzing the user's interests and emotional state, and means for selecting and presenting information according to the user's interests and emotional state. This enables the real-time provision of personalized information that is appropriate to the user's instantaneous emotions.

[0371] "User behavior information" refers to data that indicates user behavior, obtained from location information, past search history, visit history, etc.

[0372] "Emotional information" refers to data that indicates the emotional state of a user, obtained through their facial expressions, voice, and other means.

[0373] "Means of analysis" refers to technologies that analyze collected behavioral and emotional information to identify users' interests and emotional states.

[0374] "Means of selection and presentation" refers to technologies for appropriately selecting information that matches the user's interests and emotional state, and providing it to the user visually or aurally.

[0375] "Means for receiving evaluations and reflecting them in analysis" refers to technologies that receive feedback from users, utilize it in subsequent analyses, and aim to provide more accurate information.

[0376] To implement this invention, a smart pair of glasses that can be worn by the user and a server for analyzing data are used.

[0377] The server collects and analyzes behavioral and emotional information in real time. Specifically, location information, past search history, visit history, and facial and voice data acquired by the smart glasses are sent from the device to the server via a secure protocol (e.g., HTTPS). The server uses an emotion analysis engine and AI algorithms to analyze the user's current interests and emotional state.

[0378] Based on the analysis results obtained, product information and service recommendations tailored to the user's interests and emotional state are generated and presented to the user through smart glasses. In this process, the server overlays the recommendation information onto the user's visual display, allowing them to intuitively receive the information.

[0379] For example, if a user is smiling while looking at an item they're interested in in a store, the smart glasses will display detailed information and sale information about that item in real time. Furthermore, if a user voice-initiates a prompt such as "Tell me what's on sale," a generative AI model will select and present the most relevant information. This allows users to instantly obtain information that aligns with their actions and emotions, enhancing their shopping experience.

[0380] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0381] Step 1:

[0382] The device collects user behavior and emotional information in real time. This includes location information, past search history, visit history, and facial and voice data obtained via smart glasses. It takes raw data as input, processes it to infer emotional states using an emotion engine, and outputs the data ready for analysis.

[0383] Step 2:

[0384] The terminal securely transmits the collected data to the server. Here, the HTTPS encryption protocol is used to protect the data from interception, while outputting it to the server-side analysis module. This output includes all the data points necessary for analysis.

[0385] Step 3:

[0386] The server receives the transmitted data and activates its sentiment analysis engine and AI algorithms. This identifies the user's interests and emotional state. Based on the input data, it outputs analysis results with identified interest and emotion values. In this analysis process, a machine learning model identifies data patterns, and a generative AI model predicts the next information that is relevant to the user.

[0387] Step 4:

[0388] The server generates recommendation information tailored to the user's interests and emotional state based on the analysis results. Here, it searches the database for appropriate product and service information and outputs the selected information. This generated information includes the content and format in which it is displayed.

[0389] Step 5:

[0390] The server sends the recommended information back to the terminal, which then presents it to the user. In the case of smart glasses, the information is overlaid on the visual display, allowing the user to intuitively understand the recommendations. Here, the recommended information is displayed visually as digital content. The goal is to display the outputted information in real time and reflect it in the user interface.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] [Third Embodiment]

[0395] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0396] 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.

[0397] 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).

[0398] 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.

[0399] 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.

[0400] 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).

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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".

[0407] This invention provides a method for constructing a system for providing individually tailored advertisements and tourist information to users while they are on the move. This system consists of terminal-side software that runs on the user's device and a server that processes and provides information.

[0408] First, the device collects user behavior information. This information includes location data, past search history, and visit history, as well as places and interests that the user has given prior permission to access. This reveals what kinds of places the user visits and what their interests are.

[0409] Next, the device securely transmits the collected information to the server. The server analyzes the received behavioral data and uses AI algorithms to identify the user's interests. This analysis process makes it possible to predict in advance what kind of information the user will want.

[0410] Based on the analysis results, the server generates personalized information for the user. This includes advertisements and information about tourist attractions that the user might be interested in. For example, a user who has previously shown interest in nature and outdoor activities will be given priority in receiving information about local nature parks.

[0411] The device provides this information to the user in real time. Users can receive information tailored to their interests in a timely manner, allowing them to smoothly select destinations and plan their activities.

[0412] Furthermore, users can provide feedback on the information provided. The device sends this feedback to the server, which then incorporates this information into subsequent analyses. This further improves the accuracy of the information and user satisfaction.

[0413] As a concrete example of its use, if a user visits an unfamiliar city, the device can provide information on city-specific tourist attractions and events, helping them to adjust their travel plans. Furthermore, if a user wishes to shop, the server can provide information on new products and sales tailored to their preferences, enabling an optimal shopping experience.

[0414] In this way, the present invention provides users with the most relevant information, making activities involving movement more meaningful and comfortable.

[0415] The following describes the processing flow.

[0416] Step 1:

[0417] With the user's consent, the device periodically collects behavioral information such as location data, search history, and visit history. This provides basic data to understand the user's interests and behavioral patterns.

[0418] Step 2:

[0419] The device encrypts the behavioral information it collects and sends it to the server using a secure communication protocol. This is a step to ensure efficient data transmission while maintaining data confidentiality.

[0420] Step 3:

[0421] The server stores the received behavioral information in storage. Simultaneously, it uses an AI algorithm to analyze the behavioral data and generate a profile to infer the user's interests and needs.

[0422] Step 4:

[0423] Based on the profile analyzed by the server, information on advertisements and tourist destinations that match the user's interests is selected. The selected information is retrieved from a highly reliable database.

[0424] Step 5:

[0425] The server distributes the selected information to the terminal. The terminal displays the received information on the user interface, making it easy for the user to access.

[0426] Step 6:

[0427] Based on the information provided by the user, they input ratings and feedback on the places and services they actually visited into their device.

[0428] Step 7:

[0429] The device sends user feedback back to the server, which then uses this information in the next analysis step. This improves the information provision algorithm and enables further personalization.

[0430] (Example 1)

[0431] 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."

[0432] Modern information delivery systems struggle to provide users with relevant information in a timely manner. Furthermore, there is a need to effectively utilize users' behavioral history to identify their interests and generate personalized information based on those findings. However, privacy protection and secure data handling are often not adequately considered. It is necessary to address these challenges and build an information delivery system that is both useful and secure for users.

[0433] 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.

[0434] In this invention, the server includes a device having the function of collecting user behavior information, a device having the function of encrypting and transmitting the behavior information, and a device performing intelligent processing to analyze the user's interests based on the behavior information. This makes it possible to safely and effectively generate and present information that is highly relevant to the user.

[0435] A "user" is an individual or group that uses the information provision system to share behavioral information.

[0436] "Behavioral information" refers to a collection of data that indicates a user's activities and interests, such as location data, past information search history, and visit history.

[0437] "Device" refers to a part of a system that includes hardware or software for processing, transmitting, and receiving information.

[0438] "Encryption" is the process of transforming data using special algorithms to protect it from unauthorized external access.

[0439] "Intelligent processing" is the process of using AI technology to analyze user behavior information and identify their interests and concerns.

[0440] "Customized information" refers to information content that is specially generated based on the analyzed interests and preferences of the user.

[0441] An "information provision system" is a combination of hardware and software designed to generate and provide information based on users' interests and preferences.

[0442] This invention realizes an information provision system that provides personalized information to users. This system collects and analyzes user behavior information and generates and provides highly relevant information based on that information.

[0443] The device first collects user behavior information. Specifically, it records location data using GPS functionality and extracts past information search history and visit history using specific software. This data is collected with the user's permission and with full consideration given to protecting privacy. This process requires the device to have a location sensor and a local database.

[0444] Next, the device encrypts this data and sends it to the server via a secure communication protocol (e.g., HTTPS). This reduces the risk of unauthorized external access to the data.

[0445] The server analyzes the received behavioral information using AI technologies, including machine learning. This analysis utilizes specific AI algorithms and generative AI models. For example, natural language processing technology is used to understand the trends in keywords that the user has shown interest in in the past, and based on that, areas of interest are identified.

[0446] Based on the analysis results, the server generates customized information for the user and provides it through the terminal. This information includes advertisements and tourist destination-related information tailored to the user's interests, helping them make more informed decisions regarding their choices and activities.

[0447] For example, when a user visits a new region, information about local attractions and events is automatically displayed on the device screen. Based on this information, the user can plan their visit.

[0448] An example of a prompt message would be, "I enjoy outdoor activities, so could you recommend some nature parks in a new area?"

[0449] In this way, the present invention realizes a system that provides users with useful, safe, and relevant information in a timely manner.

[0450] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0451] Step 1:

[0452] The device collects user behavior information. Specifically, it uses the device's GPS function to record the user's current location and retrieves past information search history and visit history from a local database. The inputs here are the device sensors and the database, and the output is a set of location data and history information.

[0453] Step 2:

[0454] The device encrypts the collected behavioral information. It uses an encryption algorithm to transform the data and ensure security during transmission. The input is the collected raw data, and the output is encrypted data. This protects the data from unauthorized access.

[0455] Step 3:

[0456] The terminal sends encrypted data to the server. A secure protocol (e.g., HTTPS) is used for this communication. The input is encrypted data, and the output is a secure data transfer to the server. This ensures that the data reaches the server without loss.

[0457] Step 4:

[0458] The server analyzes the received behavioral information. Using generative AI models, it identifies areas of interest and concern based on the user's past behavior. The input is the received data, and the output is the analysis results indicating the user's interests. This analysis process involves matching data with a database and applying AI algorithms.

[0459] Step 5:

[0460] The server generates customized information based on the analysis results. This information includes advertisements and tourist destinations that may be of interest to the user. The input is the analysis results, and the output is personalized information for the user. Information generation includes data acquisition from content platforms.

[0461] Step 6:

[0462] The terminal provides users with information retrieved from the server in real time. This information is notified through the terminal's display function, allowing users to access it immediately. The input is information from the server, and the output is information displayed on the user's terminal. Users can decide on their actions based on the information they receive.

[0463] Step 7:

[0464] The user provides feedback on the information provided. The terminal collects this feedback and prepares to send it back to the server. The input is evaluation data from the user, and the output is feedback data to be sent to the server. This will be used to improve future analyses.

[0465] (Application Example 1)

[0466] 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."

[0467] By providing users with timely advertisements and tourist information tailored to their interests upon arrival at their destination, we address the lack of means to facilitate an effective experience.

[0468] 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.

[0469] In this invention, the server includes means for collecting user behavior information, means for analyzing the user's interests based on the behavior information, and means for providing advertisements using location information. This makes it possible to efficiently provide information tailored to the user's interests in real time.

[0470] A "user" is an individual who uses this system and provides behavioral information.

[0471] "Behavioral information" refers to a set of data that includes the user's location information, past search history, and visit history.

[0472] "Interests" refers to the user's interests and preferences identified through analysis.

[0473] "Location information" refers to geographical data that indicates where a user is currently located.

[0474] "Analysis" is the process of identifying users' interests based on collected behavioral data.

[0475] "Advertisements" are commercial information displayed according to the user's interests and location.

[0476] A "notification" is a message that provides information to users in real time.

[0477] A "server" is a computer that is responsible for data processing and information provision for the entire system.

[0478] The system for realizing this invention consists of a communication terminal, such as the user's smartphone, and a server that works in conjunction with it. An application is installed on the user's communication terminal, which collects behavioral information such as the user's location and past search history. This information collection is carried out with the user's permission, utilizing GPS sensors and application history data.

[0479] The behavioral information collected by the device is securely transmitted to a server via the internet connection, where it is received and analyzed. The analysis uses AI algorithms to identify the user's interests. Machine learning frameworks such as TensorFlow and PyTorch can be used. Based on the analysis results, the server provides users with personalized advertisements and travel information in real time. Information is delivered using push notifications, providing timely notifications tailored to the user's interests and current location.

[0480] For example, when a user traveling reaches a specific tourist attraction, the server selects coupon information for restaurants and event information related to that location and notifies the user via their smartphone app. This allows the user to enjoy a more fulfilling travel experience.

[0481] An example of a prompt might be: "When the user arrives in Tokyo and has previously shown interest in Japanese food, trigger a generative AI model that provides promotional information for nearby Japanese restaurants." This approach allows the server to provide information tailored to the user's preferences.

[0482] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0483] Step 1:

[0484] The device uses its GPS sensor to obtain the user's current location. The input is GPS data from the user's device, and the output is the user's latitude and longitude information. This information is used in the next step.

[0485] Step 2:

[0486] The device collects user behavior information. This includes past search history and visit history. The input is historical information from the application database inside the device, and the output is a dataset of the collected behavior information.

[0487] Step 3:

[0488] The device sends collected behavioral information and current location information to the server. Input is the data from steps 1 and 2, and output is the status indicating successful transmission to the server. An internet connection is used for communication.

[0489] Step 4:

[0490] The server analyzes the behavioral information it receives and uses an AI algorithm to identify the user's interests. The input is a dataset sent from the terminal, and the output is the analyzed user's interests and predicted information needs. TensorFlow or PyTorch is used as the machine learning framework.

[0491] Step 5:

[0492] The server generates personalized advertisements and tourist information tailored to the user based on the analysis results. The input is the user's interests presented from step 4, and the output is the specific advertisements and tourist spot information to be provided.

[0493] Step 6:

[0494] The server generates information and sends it to the device, which then provides it to the user via push notifications. The input is the information generated in step 5, and the output is a real-time notification displayed on the device. This notification allows the user to receive information tailored to their interests.

[0495] Step 7:

[0496] The user provides feedback on the information they have provided. The input is the user's feedback, and the output is this feedback data. This data is then sent back to the server from the terminal and used for future data analysis.

[0497] 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.

[0498] This invention provides a system that delivers personalized information to users while they are on the move, and in particular, incorporates an emotion engine to provide information that takes into account the user's emotional state. This system operates through cooperation between a terminal and a server, efficiently collecting, analyzing, and providing user behavior and emotional information.

[0499] First, the device collects user behavior information. This information includes location data, past search history, and visit history, as well as data that reads emotions from voice, facial expressions, and input actions. This data is collected using an emotion engine built into the device, based on the user's consent.

[0500] Next, the device sends the collected data to the server. A secure and encrypted protocol is applied to ensure data confidentiality and rapid delivery to the server.

[0501] The server analyzes the received data and uses an AI algorithm to identify the user's interests and emotional state. This analysis allows, for example, a user who wants to relax while traveling to be offered suggestions for quiet tourist destinations with calming music.

[0502] Furthermore, the server selects appropriate advertisements and tourist information based on the user's profile. Emotional state is also considered, and the content and tone are adjusted accordingly. This process results in more effective and user-friendly information delivery.

[0503] Finally, the device provides the selected information to the user in real time. The user can then react immediately and decide on an action based on the information provided.

[0504] For example, if a user seeks stress reduction during a trip, the emotional engine senses this state and suggests a relaxing environment. For instance, it might recommend a quiet garden or spa, making the trip more enjoyable and satisfying. Similarly, users experiencing positive emotions while shopping can be provided with emotionally relevant information on new brands and special sales, supporting their purchasing intent.

[0505] Thus, by combining emotion engines, this invention achieves advanced personalization that takes into account the user's emotions, thereby improving the travel experience.

[0506] The following describes the processing flow.

[0507] Step 1:

[0508] The device collects user behavior and emotional data. This includes location information, past search history, visit history, and an emotion engine that analyzes the user's tone of voice, facial expressions, and input actions during use.

[0509] Step 2:

[0510] The device encrypts this data before sending it to the server. Encryption ensures fast and secure data transmission while protecting user privacy.

[0511] Step 3:

[0512] The server receives the data and uses AI algorithms to analyze the user's interests and emotional state. Based on the information from the emotion engine, it gains a detailed understanding of the user's mental state and preferences.

[0513] Step 4:

[0514] Based on the analysis results, the server selects advertisements and tourist information considering the user's current emotional state. For example, if the user is detected as wanting to relax, the server will prioritize selecting places where they can enjoy calming music or relaxation facilities.

[0515] Step 5:

[0516] The server delivers this information to the terminal. The terminal displays the information on the user's screen and adjusts notifications and presentations as needed. Efforts are made to ensure easy access for the user.

[0517] Step 6:

[0518] The system helps users make decisions based on the information provided. For example, it assists users in making choices such as visiting suggested tourist destinations or facilities.

[0519] Step 7:

[0520] Users input feedback on the usefulness and content of the information provided into their device. The device then sends this collected feedback back to the server for use in future analyses.

[0521] Step 8:

[0522] The server improves its analysis algorithm based on feedback and uses it to provide more accurate information in the future. This enables more precise personalization and improves user satisfaction.

[0523] (Example 2)

[0524] 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."

[0525] Traditional personalized information systems have limitations in providing suggestions based on user behavior data, making it difficult to provide information that takes into account the user's emotional state. As a result, users may not receive information that matches their current emotions, potentially leading to dissatisfaction and negatively impacting the quality of their user experience. Furthermore, providing information that does not consider emotional aspects makes it difficult to accurately reflect user interests, limiting the effectiveness of the system.

[0526] 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.

[0527] In this invention, the server includes means for collecting user behavior information and emotional state, means for analyzing the user's interests and emotions based on the behavior information and emotional state, and means for selecting and presenting information according to the user's interests and emotions based on the analysis results. This enables advanced personalization according to the user's emotional state, making it possible to provide information that is more satisfying.

[0528] "User behavior information" refers to location information, search history, visit history, and related data, and is information used to understand user activities in detail.

[0529] "Emotional state" refers to the psychological and emotional state of a user, estimated based on their voice, facial expressions, and other physiological responses.

[0530] "Analysis means" refers to a technical process that uses collected behavioral information and emotional states to understand users' interests and emotions and to gain insights for providing information.

[0531] "Presentation means" refers to a method or device for providing users with information selected based on the analysis results, either visually or audibly.

[0532] A "profile" refers to a set of information that aggregates data about a user, such as their attributes, past behavior, and preferences, and is used to provide personalized information.

[0533] An "emotion engine" refers to a technology that combines voice analysis tools, facial recognition technology, and other elements to analyze input from various sensors and identify the user's emotions.

[0534] This invention is a system that collects user behavior information and emotional state and provides personalized information based on that information. Specifically, it uses terminals and servers to achieve this.

[0535] The device collects user behavior information. This collection includes obtaining location information using GPS functionality, and collecting search and visit history using browser and app records. Furthermore, it utilizes an emotion engine on the device to identify emotional states by analyzing voice and facial expressions. This engine uses voice analysis tools and facial recognition technology to understand the user's current psychological state.

[0536] Next, the device securely transmits the collected data to the server using an encrypted protocol. TLS (Transport Layer Security) is used for this communication to ensure data confidentiality.

[0537] The server analyzes the received data using AI algorithms. Here, natural language processing techniques and machine learning models are utilized to identify the user's interests and emotional state. Based on the analysis results, various types of information are selected according to the user's profile, and the information is provided to the user in an appropriate content and tone.

[0538] Ultimately, the device presents the user with information provided by the server in real time. Users can receive this information through push notifications or in-app interfaces and take the suggested action immediately.

[0539] For example, users who want to reduce stress while traveling are provided with information on nearby quiet tourist spots and cafes. This information is selected based on the user's emotional state, as identified by the emotion engine. As another example, users who are shopping and in a positive emotional state are presented with information on new products and special sales, helping to increase their purchasing intent.

[0540] By utilizing generative AI models, it is possible to continuously improve the provision of optimal information to users using prompts. Examples of prompts include, "Suggest how to provide appropriate information to a user who wants to relax while traveling," and "Please provide criteria for selecting personalized advertisements based on the user's emotional state." Based on such concrete examples, the system will improve the user's travel experience.

[0541] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0542] Step 1:

[0543] The device collects user behavior information and emotional states. As input, the device obtains location information using GPS, retrieves search history from browser history, and collects visit history from applications. Furthermore, using the camera and microphone, an emotion engine extracts emotional data based on voice and facial expressions. By collecting this data, the device forms a framework of the user's overall behavioral patterns and emotional trends. As output, this data is ready to be sent to the next step.

[0544] Step 2:

[0545] The device sends the collected data to the server. The input consists of location information, search history, visit history, and sentiment data based on voice and facial expressions, collected in step 1. The data is securely transmitted using encryption protocols such as TLS. In actual operation, the data is batched and sent periodically (e.g., every 10 minutes). The output is the data arriving at the server in encrypted form.

[0546] Step 3:

[0547] The server analyzes the received data to identify the user's interests and emotional state. It receives location information, search history, visit history, and emotional data from the terminal as input. Data processing and computation apply natural language processing techniques and machine learning models to identify the user's current interests and emotional state. Specifically, emotional data is used for emotional level scoring, and interest data is classified using clustering algorithms. The output is the analysis result based on the identified interests and emotional state.

[0548] Step 4:

[0549] The server selects information based on the analysis results and generates optimized content. The analysis results obtained in step 3 are used as input. The selection process considers the target user's profile, choosing information that is highly relevant and appropriate to their emotional state. Specifically, it selects information such as relaxing places and special sale information, and adjusts the suggestions according to the user's emotional state. The output is a set of information to be presented to the user, such as navigation information and advertising information.

[0550] Step 5:

[0551] The device provides optimized information to the user in real time. The input is a set of information sent from the server. This is provided through specific UI activities, such as displaying it as a push notification on the user's device interface. The user can review the information and decide on an action based on the suggested information. The output is the user's action, for example, deciding which tourist destination to visit.

[0552] (Application Example 2)

[0553] 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."

[0554] Modern consumers are surrounded by a wealth of information and expect services tailored to their individual preferences and emotions. However, traditional systems struggle to provide information that responds to users' instantaneous emotional states, leading to challenges such as decreased purchasing intent and difficulty in improving the quality of the user experience.

[0555] 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.

[0556] In this invention, the server includes means for collecting user behavior information and emotional information, means for analyzing the user's interests and emotional state, and means for selecting and presenting information according to the user's interests and emotional state. This enables the real-time provision of personalized information that is appropriate to the user's instantaneous emotions.

[0557] "User behavior information" refers to data that indicates user behavior, obtained from location information, past search history, visit history, etc.

[0558] "Emotional information" refers to data that indicates the emotional state of a user, obtained through their facial expressions, voice, and other means.

[0559] "Means of analysis" refers to technologies that analyze collected behavioral and emotional information to identify users' interests and emotional states.

[0560] "Means of selection and presentation" refers to technologies for appropriately selecting information that matches the user's interests and emotional state, and providing it to the user visually or aurally.

[0561] "Means for receiving evaluations and reflecting them in analysis" refers to technologies that receive feedback from users, utilize it in subsequent analyses, and aim to provide more accurate information.

[0562] To implement this invention, a smart pair of glasses that can be worn by the user and a server for analyzing data are used.

[0563] The server collects and analyzes behavioral and emotional information in real time. Specifically, location information, past search history, visit history, and facial and voice data acquired by the smart glasses are sent from the device to the server via a secure protocol (e.g., HTTPS). The server uses an emotion analysis engine and AI algorithms to analyze the user's current interests and emotional state.

[0564] Based on the analysis results obtained, product information and service recommendations tailored to the user's interests and emotional state are generated and presented to the user through smart glasses. In this process, the server overlays the recommendation information onto the user's visual display, allowing them to intuitively receive the information.

[0565] For example, if a user is smiling while looking at an item they're interested in in a store, the smart glasses will display detailed information and sale information about that item in real time. Furthermore, if a user voice-initiates a prompt such as "Tell me what's on sale," a generative AI model will select and present the most relevant information. This allows users to instantly obtain information that aligns with their actions and emotions, enhancing their shopping experience.

[0566] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0567] Step 1:

[0568] The device collects user behavior and emotional information in real time. This includes location information, past search history, visit history, and facial and voice data obtained via smart glasses. It takes raw data as input, processes it to infer emotional states using an emotion engine, and outputs the data ready for analysis.

[0569] Step 2:

[0570] The terminal securely transmits the collected data to the server. Here, the HTTPS encryption protocol is used to protect the data from interception, while outputting it to the server-side analysis module. This output includes all the data points necessary for analysis.

[0571] Step 3:

[0572] The server receives the transmitted data and activates its sentiment analysis engine and AI algorithms. This identifies the user's interests and emotional state. Based on the input data, it outputs analysis results with identified interest and emotion values. In this analysis process, a machine learning model identifies data patterns, and a generative AI model predicts the next information that is relevant to the user.

[0573] Step 4:

[0574] The server generates recommendation information tailored to the user's interests and emotional state based on the analysis results. Here, it searches the database for appropriate product and service information and outputs the selected information. This generated information includes the content and format in which it is displayed.

[0575] Step 5:

[0576] The server sends the recommended information back to the terminal, which then presents it to the user. In the case of smart glasses, the information is overlaid on the visual display, allowing the user to intuitively understand the recommendations. Here, the recommended information is displayed visually as digital content. The goal is to display the outputted information in real time and reflect it in the user interface.

[0577] 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.

[0578] 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.

[0579] 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.

[0580] [Fourth Embodiment]

[0581] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0582] 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.

[0583] 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).

[0584] 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.

[0585] 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.

[0586] 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).

[0587] 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.

[0588] 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.

[0589] 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.

[0590] 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.

[0591] 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.

[0592] 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.

[0593] 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".

[0594] This invention provides a method for constructing a system for providing individually tailored advertisements and tourist information to users while they are on the move. This system consists of terminal-side software that runs on the user's device and a server that processes and provides information.

[0595] First, the device collects user behavior information. This information includes location data, past search history, and visit history, as well as places and interests that the user has given prior permission to access. This reveals what kinds of places the user visits and what their interests are.

[0596] Next, the device securely transmits the collected information to the server. The server analyzes the received behavioral data and uses AI algorithms to identify the user's interests. This analysis process makes it possible to predict in advance what kind of information the user will want.

[0597] Based on the analysis results, the server generates personalized information for the user. This includes advertisements and information about tourist attractions that the user might be interested in. For example, a user who has previously shown interest in nature and outdoor activities will be given priority in receiving information about local nature parks.

[0598] The device provides this information to the user in real time. Users can receive information tailored to their interests in a timely manner, allowing them to smoothly select destinations and plan their activities.

[0599] Furthermore, users can provide feedback on the information provided. The device sends this feedback to the server, which then incorporates this information into subsequent analyses. This further improves the accuracy of the information and user satisfaction.

[0600] As a concrete example of its use, if a user visits an unfamiliar city, the device can provide information on city-specific tourist attractions and events, helping them to adjust their travel plans. Furthermore, if a user wishes to shop, the server can provide information on new products and sales tailored to their preferences, enabling an optimal shopping experience.

[0601] In this way, the present invention provides users with the most relevant information, making activities involving movement more meaningful and comfortable.

[0602] The following describes the processing flow.

[0603] Step 1:

[0604] With the user's consent, the device periodically collects behavioral information such as location data, search history, and visit history. This provides basic data to understand the user's interests and behavioral patterns.

[0605] Step 2:

[0606] The device encrypts the behavioral information it collects and sends it to the server using a secure communication protocol. This is a step to ensure efficient data transmission while maintaining data confidentiality.

[0607] Step 3:

[0608] The server stores the received behavioral information in storage. Simultaneously, it uses an AI algorithm to analyze the behavioral data and generate a profile to infer the user's interests and needs.

[0609] Step 4:

[0610] Based on the profile analyzed by the server, information on advertisements and tourist destinations that match the user's interests is selected. The selected information is retrieved from a highly reliable database.

[0611] Step 5:

[0612] The server distributes the selected information to the terminal. The terminal displays the received information on the user interface, making it easy for the user to access.

[0613] Step 6:

[0614] Based on the information provided by the user, they input ratings and feedback on the places and services they actually visited into their device.

[0615] Step 7:

[0616] The device sends user feedback back to the server, which then uses this information in the next analysis step. This improves the information provision algorithm and enables further personalization.

[0617] (Example 1)

[0618] 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".

[0619] Modern information delivery systems struggle to provide users with relevant information in a timely manner. Furthermore, there is a need to effectively utilize users' behavioral history to identify their interests and generate personalized information based on those findings. However, privacy protection and secure data handling are often not adequately considered. It is necessary to address these challenges and build an information delivery system that is both useful and secure for users.

[0620] 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.

[0621] In this invention, the server includes a device having the function of collecting user behavior information, a device having the function of encrypting and transmitting the behavior information, and a device performing intelligent processing to analyze the user's interests based on the behavior information. This makes it possible to safely and effectively generate and present information that is highly relevant to the user.

[0622] A "user" is an individual or group that uses the information provision system to share behavioral information.

[0623] "Behavioral information" refers to a collection of data that indicates a user's activities and interests, such as location data, past information search history, and visit history.

[0624] "Device" refers to a part of a system that includes hardware or software for processing, transmitting, and receiving information.

[0625] "Encryption" is the process of transforming data using special algorithms to protect it from unauthorized external access.

[0626] "Intelligent processing" is the process of using AI technology to analyze user behavior information and identify their interests and concerns.

[0627] "Customized information" refers to information content that is specially generated based on the analyzed interests and preferences of the user.

[0628] An "information provision system" is a combination of hardware and software designed to generate and provide information based on users' interests and preferences.

[0629] This invention realizes an information provision system that provides personalized information to users. This system collects and analyzes user behavior information and generates and provides highly relevant information based on that information.

[0630] The device first collects user behavior information. Specifically, it records location data using GPS functionality and extracts past information search history and visit history using specific software. This data is collected with the user's permission and with full consideration given to protecting privacy. This process requires the device to have a location sensor and a local database.

[0631] Next, the device encrypts this data and sends it to the server via a secure communication protocol (e.g., HTTPS). This reduces the risk of unauthorized external access to the data.

[0632] The server analyzes the received behavioral information using AI technologies, including machine learning. This analysis utilizes specific AI algorithms and generative AI models. For example, natural language processing technology is used to understand the trends in keywords that the user has shown interest in in the past, and based on that, areas of interest are identified.

[0633] Based on the analysis results, the server generates customized information for the user and provides it through the terminal. This information includes advertisements and tourist destination-related information tailored to the user's interests, helping them make more informed decisions regarding their choices and activities.

[0634] For example, when a user visits a new region, information about local attractions and events is automatically displayed on the device screen. Based on this information, the user can plan their visit.

[0635] An example of a prompt message would be, "I enjoy outdoor activities, so could you recommend some nature parks in a new area?"

[0636] In this way, the present invention realizes a system that provides users with useful, safe, and relevant information in a timely manner.

[0637] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0638] Step 1:

[0639] The device collects user behavior information. Specifically, it uses the device's GPS function to record the user's current location and retrieves past information search history and visit history from a local database. The inputs here are the device sensors and the database, and the output is a set of location data and history information.

[0640] Step 2:

[0641] The device encrypts the collected behavioral information. It uses an encryption algorithm to transform the data and ensure security during transmission. The input is the collected raw data, and the output is encrypted data. This protects the data from unauthorized access.

[0642] Step 3:

[0643] The terminal sends encrypted data to the server. A secure protocol (e.g., HTTPS) is used for this communication. The input is encrypted data, and the output is a secure data transfer to the server. This ensures that the data reaches the server without loss.

[0644] Step 4:

[0645] The server analyzes the received behavioral information. Using generative AI models, it identifies areas of interest and concern based on the user's past behavior. The input is the received data, and the output is the analysis results indicating the user's interests. This analysis process involves matching data with a database and applying AI algorithms.

[0646] Step 5:

[0647] The server generates customized information based on the analysis results. This information includes advertisements and tourist destinations that may be of interest to the user. The input is the analysis results, and the output is personalized information for the user. Information generation includes data acquisition from content platforms.

[0648] Step 6:

[0649] The terminal provides users with information retrieved from the server in real time. This information is notified through the terminal's display function, allowing users to access it immediately. The input is information from the server, and the output is information displayed on the user's terminal. Users can decide on their actions based on the information they receive.

[0650] Step 7:

[0651] The user provides feedback on the information provided. The terminal collects this feedback and prepares to send it back to the server. The input is evaluation data from the user, and the output is feedback data to be sent to the server. This will be used to improve future analyses.

[0652] (Application Example 1)

[0653] 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".

[0654] By providing users with timely advertisements and tourist information tailored to their interests upon arrival at their destination, we address the lack of means to facilitate an effective experience.

[0655] 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.

[0656] In this invention, the server includes means for collecting user behavior information, means for analyzing the user's interests based on the behavior information, and means for providing advertisements using location information. This makes it possible to efficiently provide information tailored to the user's interests in real time.

[0657] A "user" is an individual who uses this system and provides behavioral information.

[0658] "Behavioral information" refers to a set of data that includes the user's location information, past search history, and visit history.

[0659] "Interests" refers to the user's interests and preferences identified through analysis.

[0660] "Location information" refers to geographical data that indicates where a user is currently located.

[0661] "Analysis" is the process of identifying users' interests based on collected behavioral data.

[0662] "Advertisements" are commercial information displayed according to the user's interests and location.

[0663] A "notification" is a message that provides information to users in real time.

[0664] A "server" is a computer that is responsible for data processing and information provision for the entire system.

[0665] The system for realizing this invention consists of a communication terminal, such as the user's smartphone, and a server that works in conjunction with it. An application is installed on the user's communication terminal, which collects behavioral information such as the user's location and past search history. This information collection is carried out with the user's permission, utilizing GPS sensors and application history data.

[0666] The behavioral information collected by the device is securely transmitted to a server via the internet connection, where it is received and analyzed. The analysis uses AI algorithms to identify the user's interests. Machine learning frameworks such as TensorFlow and PyTorch can be used. Based on the analysis results, the server provides users with personalized advertisements and travel information in real time. Information is delivered using push notifications, providing timely notifications tailored to the user's interests and current location.

[0667] For example, when a user traveling reaches a specific tourist attraction, the server selects coupon information for restaurants and event information related to that location and notifies the user via their smartphone app. This allows the user to enjoy a more fulfilling travel experience.

[0668] An example of a prompt might be: "When the user arrives in Tokyo and has previously shown interest in Japanese food, trigger a generative AI model that provides promotional information for nearby Japanese restaurants." This approach allows the server to provide information tailored to the user's preferences.

[0669] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0670] Step 1:

[0671] The device uses its GPS sensor to obtain the user's current location. The input is GPS data from the user's device, and the output is the user's latitude and longitude information. This information is used in the next step.

[0672] Step 2:

[0673] The device collects user behavior information. This includes past search history and visit history. The input is historical information from the application database inside the device, and the output is a dataset of the collected behavior information.

[0674] Step 3:

[0675] The device sends collected behavioral information and current location information to the server. Input is the data from steps 1 and 2, and output is the status indicating successful transmission to the server. An internet connection is used for communication.

[0676] Step 4:

[0677] The server analyzes the behavioral information it receives and uses an AI algorithm to identify the user's interests. The input is a dataset sent from the terminal, and the output is the analyzed user's interests and predicted information needs. TensorFlow or PyTorch is used as the machine learning framework.

[0678] Step 5:

[0679] The server generates personalized advertisements and tourist information tailored to the user based on the analysis results. The input is the user's interests presented from step 4, and the output is the specific advertisements and tourist spot information to be provided.

[0680] Step 6:

[0681] The server generates information and sends it to the device, which then provides it to the user via push notifications. The input is the information generated in step 5, and the output is a real-time notification displayed on the device. This notification allows the user to receive information tailored to their interests.

[0682] Step 7:

[0683] The user provides feedback on the information they have provided. The input is the user's feedback, and the output is this feedback data. This data is then sent back to the server from the terminal and used for future data analysis.

[0684] 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.

[0685] This invention provides a system that delivers personalized information to users while they are on the move, and in particular, incorporates an emotion engine to provide information that takes into account the user's emotional state. This system operates through cooperation between a terminal and a server, efficiently collecting, analyzing, and providing user behavior and emotional information.

[0686] First, the device collects user behavior information. This information includes location data, past search history, and visit history, as well as data that reads emotions from voice, facial expressions, and input actions. This data is collected using an emotion engine built into the device, based on the user's consent.

[0687] Next, the device sends the collected data to the server. A secure and encrypted protocol is applied to ensure data confidentiality and rapid delivery to the server.

[0688] The server analyzes the received data and uses an AI algorithm to identify the user's interests and emotional state. This analysis allows, for example, a user who wants to relax while traveling to be offered suggestions for quiet tourist destinations with calming music.

[0689] Furthermore, the server selects appropriate advertisements and tourist information based on the user's profile. Emotional state is also considered, and the content and tone are adjusted accordingly. This process results in more effective and user-friendly information delivery.

[0690] Finally, the device provides the selected information to the user in real time. The user can then react immediately and decide on an action based on the information provided.

[0691] For example, if a user seeks stress reduction during a trip, the emotional engine senses this state and suggests a relaxing environment. For instance, it might recommend a quiet garden or spa, making the trip more enjoyable and satisfying. Similarly, users experiencing positive emotions while shopping can be provided with emotionally relevant information on new brands and special sales, supporting their purchasing intent.

[0692] Thus, by combining emotion engines, this invention achieves advanced personalization that takes into account the user's emotions, thereby improving the travel experience.

[0693] The following describes the processing flow.

[0694] Step 1:

[0695] The device collects user behavior and emotional data. This includes location information, past search history, visit history, and an emotion engine that analyzes the user's tone of voice, facial expressions, and input actions during use.

[0696] Step 2:

[0697] The device encrypts this data before sending it to the server. Encryption ensures fast and secure data transmission while protecting user privacy.

[0698] Step 3:

[0699] The server receives the data and uses AI algorithms to analyze the user's interests and emotional state. Based on the information from the emotion engine, it gains a detailed understanding of the user's mental state and preferences.

[0700] Step 4:

[0701] Based on the analysis results, the server selects advertisements and tourist information considering the user's current emotional state. For example, if the user is detected as wanting to relax, the server will prioritize selecting places where they can enjoy calming music or relaxation facilities.

[0702] Step 5:

[0703] The server delivers this information to the terminal. The terminal displays the information on the user's screen and adjusts notifications and presentations as needed. Efforts are made to ensure easy access for the user.

[0704] Step 6:

[0705] The system helps users make decisions based on the information provided. For example, it assists users in making choices such as visiting suggested tourist destinations or facilities.

[0706] Step 7:

[0707] Users input feedback on the usefulness and content of the information provided into their device. The device then sends this collected feedback back to the server for use in future analyses.

[0708] Step 8:

[0709] The server improves its analysis algorithm based on feedback and uses it to provide more accurate information in the future. This enables more precise personalization and improves user satisfaction.

[0710] (Example 2)

[0711] 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".

[0712] Traditional personalized information systems have limitations in providing suggestions based on user behavior data, making it difficult to provide information that takes into account the user's emotional state. As a result, users may not receive information that matches their current emotions, potentially leading to dissatisfaction and negatively impacting the quality of their user experience. Furthermore, providing information that does not consider emotional aspects makes it difficult to accurately reflect user interests, limiting the effectiveness of the system.

[0713] 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.

[0714] In this invention, the server includes means for collecting user behavior information and emotional state, means for analyzing the user's interests and emotions based on the behavior information and emotional state, and means for selecting and presenting information according to the user's interests and emotions based on the analysis results. This enables advanced personalization according to the user's emotional state, making it possible to provide information that is more satisfying.

[0715] "User behavior information" refers to location information, search history, visit history, and related data, and is information used to understand user activities in detail.

[0716] "Emotional state" refers to the psychological and emotional state of a user, estimated based on their voice, facial expressions, and other physiological responses.

[0717] "Analysis means" refers to a technical process that uses collected behavioral information and emotional states to understand users' interests and emotions and to gain insights for providing information.

[0718] "Presentation means" refers to a method or device for providing users with information selected based on the analysis results, either visually or audibly.

[0719] A "profile" refers to a set of information that aggregates data about a user, such as their attributes, past behavior, and preferences, and is used to provide personalized information.

[0720] An "emotion engine" refers to a technology that combines voice analysis tools, facial recognition technology, and other elements to analyze input from various sensors and identify the user's emotions.

[0721] This invention is a system that collects user behavior information and emotional state and provides personalized information based on that information. Specifically, it uses terminals and servers to achieve this.

[0722] The device collects user behavior information. This collection includes obtaining location information using GPS functionality, and collecting search and visit history using browser and app records. Furthermore, it utilizes an emotion engine on the device to identify emotional states by analyzing voice and facial expressions. This engine uses voice analysis tools and facial recognition technology to understand the user's current psychological state.

[0723] Next, the device securely transmits the collected data to the server using an encrypted protocol. TLS (Transport Layer Security) is used for this communication to ensure data confidentiality.

[0724] The server analyzes the received data using AI algorithms. Here, natural language processing techniques and machine learning models are utilized to identify the user's interests and emotional state. Based on the analysis results, various types of information are selected according to the user's profile, and the information is provided to the user in an appropriate content and tone.

[0725] Ultimately, the device presents the user with information provided by the server in real time. Users can receive this information through push notifications or in-app interfaces and take the suggested action immediately.

[0726] For example, users who want to reduce stress while traveling are provided with information on nearby quiet tourist spots and cafes. This information is selected based on the user's emotional state, as identified by the emotion engine. As another example, users who are shopping and in a positive emotional state are presented with information on new products and special sales, helping to increase their purchasing intent.

[0727] By utilizing generative AI models, it is possible to continuously improve the provision of optimal information to users using prompts. Examples of prompts include, "Suggest how to provide appropriate information to a user who wants to relax while traveling," and "Please provide criteria for selecting personalized advertisements based on the user's emotional state." Based on such concrete examples, the system will improve the user's travel experience.

[0728] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0729] Step 1:

[0730] The device collects user behavior information and emotional states. As input, the device obtains location information using GPS, retrieves search history from browser history, and collects visit history from applications. Furthermore, using the camera and microphone, an emotion engine extracts emotional data based on voice and facial expressions. By collecting this data, the device forms a framework of the user's overall behavioral patterns and emotional trends. As output, this data is ready to be sent to the next step.

[0731] Step 2:

[0732] The device sends the collected data to the server. The input consists of location information, search history, visit history, and sentiment data based on voice and facial expressions, collected in step 1. The data is securely transmitted using encryption protocols such as TLS. In actual operation, the data is batched and sent periodically (e.g., every 10 minutes). The output is the data arriving at the server in encrypted form.

[0733] Step 3:

[0734] The server analyzes the received data to identify the user's interests and emotional state. It receives location information, search history, visit history, and emotional data from the terminal as input. Data processing and computation apply natural language processing techniques and machine learning models to identify the user's current interests and emotional state. Specifically, emotional data is used for emotional level scoring, and interest data is classified using clustering algorithms. The output is the analysis result based on the identified interests and emotional state.

[0735] Step 4:

[0736] The server selects information based on the analysis results and generates optimized content. The analysis results obtained in step 3 are used as input. The selection process considers the target user's profile, choosing information that is highly relevant and appropriate to their emotional state. Specifically, it selects information such as relaxing places and special sale information, and adjusts the suggestions according to the user's emotional state. The output is a set of information to be presented to the user, such as navigation information and advertising information.

[0737] Step 5:

[0738] The device provides optimized information to the user in real time. The input is a set of information sent from the server. This is provided through specific UI activities, such as displaying it as a push notification on the user's device interface. The user can review the information and decide on an action based on the suggested information. The output is the user's action, for example, deciding which tourist destination to visit.

[0739] (Application Example 2)

[0740] 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".

[0741] Modern consumers are surrounded by a wealth of information and expect services tailored to their individual preferences and emotions. However, traditional systems struggle to provide information that responds to users' instantaneous emotional states, leading to challenges such as decreased purchasing intent and difficulty in improving the quality of the user experience.

[0742] 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.

[0743] In this invention, the server includes means for collecting user behavior information and emotional information, means for analyzing the user's interests and emotional state, and means for selecting and presenting information according to the user's interests and emotional state. This enables the real-time provision of personalized information that is appropriate to the user's instantaneous emotions.

[0744] "User behavior information" refers to data that indicates user behavior, obtained from location information, past search history, visit history, etc.

[0745] "Emotional information" refers to data that indicates the emotional state of a user, obtained through their facial expressions, voice, and other means.

[0746] "Means of analysis" refers to technologies that analyze collected behavioral and emotional information to identify users' interests and emotional states.

[0747] "Means of selection and presentation" refers to technologies for appropriately selecting information that matches the user's interests and emotional state, and providing it to the user visually or aurally.

[0748] "Means for receiving evaluations and reflecting them in analysis" refers to technologies that receive feedback from users, utilize it in subsequent analyses, and aim to provide more accurate information.

[0749] To implement this invention, a smart pair of glasses that can be worn by the user and a server for analyzing data are used.

[0750] The server collects and analyzes behavioral and emotional information in real time. Specifically, location information, past search history, visit history, and facial and voice data acquired by the smart glasses are sent from the device to the server via a secure protocol (e.g., HTTPS). The server uses an emotion analysis engine and AI algorithms to analyze the user's current interests and emotional state.

[0751] Based on the analysis results obtained, product information and service recommendations tailored to the user's interests and emotional state are generated and presented to the user through smart glasses. In this process, the server overlays the recommendation information onto the user's visual display, allowing them to intuitively receive the information.

[0752] For example, if a user is smiling while looking at an item they're interested in in a store, the smart glasses will display detailed information and sale information about that item in real time. Furthermore, if a user voice-initiates a prompt such as "Tell me what's on sale," a generative AI model will select and present the most relevant information. This allows users to instantly obtain information that aligns with their actions and emotions, enhancing their shopping experience.

[0753] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0754] Step 1:

[0755] The device collects user behavior and emotional information in real time. This includes location information, past search history, visit history, and facial and voice data obtained via smart glasses. It takes raw data as input, processes it to infer emotional states using an emotion engine, and outputs the data ready for analysis.

[0756] Step 2:

[0757] The terminal securely transmits the collected data to the server. Here, the HTTPS encryption protocol is used to protect the data from interception, while outputting it to the server-side analysis module. This output includes all the data points necessary for analysis.

[0758] Step 3:

[0759] The server receives the transmitted data and activates its sentiment analysis engine and AI algorithms. This identifies the user's interests and emotional state. Based on the input data, it outputs analysis results with identified interest and emotion values. In this analysis process, a machine learning model identifies data patterns, and a generative AI model predicts the next information that is relevant to the user.

[0760] Step 4:

[0761] The server generates recommendation information tailored to the user's interests and emotional state based on the analysis results. Here, it searches the database for appropriate product and service information and outputs the selected information. This generated information includes the content and format in which it is displayed.

[0762] Step 5:

[0763] The server sends the recommended information back to the terminal, which then presents it to the user. In the case of smart glasses, the information is overlaid on the visual display, allowing the user to intuitively understand the recommendations. Here, the recommended information is displayed visually as digital content. The goal is to display the outputted information in real time and reflect it in the user interface.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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."

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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.

[0784] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0785] The following is further disclosed regarding the embodiments described above.

[0786] (Claim 1)

[0787] Means for collecting user behavior information,

[0788] A means for analyzing user interests based on the aforementioned behavioral information,

[0789] Based on the aforementioned analysis results, a means for selecting and presenting information according to the user's interests,

[0790] A means for receiving and reflecting evaluations of the aforementioned information in the analysis,

[0791] A system that includes this.

[0792] (Claim 2)

[0793] The system according to claim 1, wherein the behavioral information includes location information, past search history, and visit history.

[0794] (Claim 3)

[0795] The system according to claim 1, wherein the aforementioned information is advertising or tourist destination-related information.

[0796] "Example 1"

[0797] (Claim 1)

[0798] A device having a function to collect user behavior information,

[0799] A device having the function of encrypting and transmitting the aforementioned behavioral information,

[0800] A device for performing intelligent processing to analyze the user's interests based on the aforementioned behavioral information,

[0801] Based on the aforementioned analysis results, a device is provided that generates and presents information highly relevant to the user.

[0802] A device that receives user feedback on the information presented and incorporates it into subsequent analyses,

[0803] A system that includes this.

[0804] (Claim 2)

[0805] The system according to claim 1, wherein the behavioral information includes location data, past information search history, and visit history.

[0806] (Claim 3)

[0807] The system according to claim 1, wherein the generated information is information for promoting purchases or travel destination-related information.

[0808] "Application Example 1"

[0809] (Claim 1)

[0810] Means for collecting user behavior information,

[0811] A means for analyzing user interests based on the aforementioned behavioral information,

[0812] Based on the aforementioned analysis results, a means for selecting and presenting information according to the user's interests,

[0813] A means for receiving and reflecting evaluations of the aforementioned information in the analysis,

[0814] A means of providing advertisements using location information,

[0815] A means of notifying users of information that reflects their interests in real time,

[0816] A system that includes this.

[0817] (Claim 2)

[0818] The system according to claim 1, wherein the behavioral information includes location information, past search history, and visit history.

[0819] (Claim 3)

[0820] The system according to claim 1, wherein the information is an advertisement or tourist destination-related information, and is provided according to location.

[0821] "Example 2 of combining an emotion engine"

[0822] (Claim 1)

[0823] Means for collecting user behavior information and emotional state,

[0824] A means for analyzing the user's interests and emotions based on the aforementioned behavioral information and emotional state,

[0825] Based on the aforementioned analysis results, a means for selecting and presenting information according to interests and emotions,

[0826] When the aforementioned information is presented, a means is provided to consider the user's profile and adjust the content according to their emotional state.

[0827] A means for receiving and reflecting evaluations of the aforementioned information in the analysis,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, wherein the behavioral information includes location information, search history, visit history, voice, and emotion data based on facial expressions.

[0831] (Claim 3)

[0832] The system according to claim 1, wherein the information is general information or geographic location-related information.

[0833] "Application example 2 when combining with an emotional engine"

[0834] (Claim 1)

[0835] Means for collecting user behavioral information and emotional information,

[0836] A means for analyzing the user's interests and emotional state based on the aforementioned behavioral and emotional information,

[0837] Based on the aforementioned analysis results, a means for selecting and presenting information according to interests and emotional states,

[0838] A means of receiving evaluations of the aforementioned information, reflecting them in the analysis, and improving the user experience,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, wherein the behavioral information includes location information, past search history, visit history, and emotional data obtained from the user's facial expressions and voice.

[0842] (Claim 3)

[0843] The system according to claim 1, wherein the information is product recommendation information or service selection information, and includes content adjusted based on the user's emotions. [Explanation of Symbols]

[0844] 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. Means for collecting user behavior information, A means for analyzing user interests based on the aforementioned behavioral information, Based on the aforementioned analysis results, a means for selecting and presenting information according to the user's interests, A means for receiving and reflecting evaluations of the aforementioned information in the analysis, A system that includes this.

2. The system according to claim 1, wherein the behavioral information includes location information, past search history, and visit history.

3. The system according to claim 1, wherein the aforementioned information is advertising or tourist destination-related information.

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