system

Abstract

We provide the system. [Solution] Means for obtaining user experience information, A means for generating an appropriate search query based on the user's experience information, A means for searching for related data sets using the aforementioned search query, Means for customizing the search results according to the user's experience information, Means of providing customized information to users, A means of optimizing predetermined learning content according to the user's skill level, 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 persona chatbot control method performed by at least one processor, the method 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] In the fields of information technology and communication, there is a lack of communication among stakeholders with different expertise, so there is a need for information provision means according to individual technical levels. Also, there is a problem that new information cannot be learned efficiently and quickly, which hinders the smooth performance of work and personal growth. As a result, there is a need for search results and information provision means optimized individually.

Means for Solving the Problems

[0005] This invention provides a means for acquiring user experience information and generating appropriate search queries based on it. Furthermore, it includes means for gathering relevant information by exploring relevant databases and external resources using these generated queries, and for providing the obtained data customized according to the user's knowledge level. This system improves the efficiency of information acquisition and supports user understanding. In addition, it is possible to continuously improve system performance through feedback.

[0006] "Means for acquiring user experience information" refers to functions for collecting information such as the user's knowledge level, skills, and background.

[0007] "Means for generating search queries" refers to a function that creates appropriate keywords and phrases to access relevant information based on collected user experience data.

[0008] "Means for exploring related databases" refers to the function of using generated search queries to search for and collect relevant information from internal or external databases.

[0009] "Means of customization" refers to a function that reorganizes collected information according to the user's knowledge level and requirements, and provides it in the most optimal format.

[0010] A "means of obtaining feedback" refers to a function that records how users react to the information they provide and identifies areas for improvement. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0017] In the following embodiments, the labeled 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.

[0018] 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."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0029] 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.

[0030] 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.

[0031] 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".

[0032] The system of this invention enables users to efficiently acquire customized information based on their own knowledge and skills. It operates through the coordinated efforts of three elements: a server, a terminal, and the user.

[0033] First, the user accesses the system through a terminal and logs into their account. The terminal sends data to the server to identify the user's experience and knowledge level. This information includes past work history and skill set.

[0034] The server generates appropriate search queries based on the user's experience. These search queries are customized to more accurately find the information the user needs. For example, if a user wants to learn about new technologies related to cloud infrastructure, the queries will be generated with a depth and scope that matches the user's experience.

[0035] Using the generated queries, the server searches relevant databases and external information resources to collect relevant information. The server then customizes this information based on the user's experience, providing basic explanations to less experienced users and detailed technical information to more knowledgeable users.

[0036] Next, the terminal displays customized information received from the server to the user. This information can be provided in various formats, such as text, visual aids, or videos, and is presented in a way that is easy for the user to understand. As a result, users can efficiently acquire content tailored to their skill level.

[0037] Furthermore, the device collects feedback on the user's reactions to and understanding of the information received, and sends it to the server. The server analyzes this feedback and uses generative AI to provide even more user-optimized information. This ensures that the overall system performance continues to improve.

[0038] For example, if a new employee wants to deepen their understanding of specific technical terms or technologies, this system automatically provides the most relevant information, streamlining self-study and supporting improved communication skills. Thus, this invention dramatically improves work efficiency and learning effectiveness by quickly and accurately providing information perfectly matched to each user's knowledge level.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user logs into the system via their device. The device sends the user's authentication information to the server, which retrieves the relevant information from the user's profile database.

[0042] Step 2:

[0043] Based on the acquired profile data, the server generates search queries tailored to the user's knowledge level and experience. The server then formats these queries appropriately and prepares them for the next search process.

[0044] Step 3:

[0045] The server uses the generated search query to explore relevant internal databases and external information resources. It aggregates the necessary data and filters it to best suit the user's needs.

[0046] Step 4:

[0047] The server customizes filtered information to suit the user's knowledge level. It generates basic content for beginners and more technical content for experienced users.

[0048] Step 5:

[0049] The terminal displays customized information received from the server to the user. The information is provided in a format that is easy for the user to understand, such as text, diagrams, or videos.

[0050] Step 6:

[0051] Users view the provided information and send feedback to the server via their device. This feedback may include comments on the usefulness of the information and additional questions.

[0052] Step 7:

[0053] The server analyzes user feedback and uses AI models to further improve future information delivery. This increases system accuracy and user satisfaction.

[0054] (Example 1)

[0055] 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."

[0056] The challenge lies in enabling the efficient acquisition and use of information tailored to individual skills and experience, thereby improving productivity in learning and work. In particular, finding the most relevant information from a vast amount of data is time-consuming and laborious, so an effective method is needed.

[0057] 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.

[0058] In this invention, the server includes means for acquiring user skill information, means for generating appropriate information retrieval commands based on the user skill information, and means for searching for internal and external information resources using the information retrieval commands. This makes it possible to efficiently retrieve information according to each user's skill level and present it in an appropriate format.

[0059] A "user" refers to an individual or organization that utilizes an information retrieval and provision system, and is the recipient of information customized based on their skills and information.

[0060] "Skills information" refers to data about a user's past work history and skill set, used to identify the user's knowledge level and experience.

[0061] An "information retrieval command" is a search query generated based on the user's skill information, and refers to a command used by the system to identify and obtain the information the user needs.

[0062] "Internal information resources" refer to databases and information libraries stored within the system, and include information that can be provided to users.

[0063] "External information resources" refer to databases and information sources outside the system, including information sources accessible via the internet.

[0064] "Adjustment" refers to the operation of appropriately filtering or sorting search results based on the user's skill information.

[0065] "Visualization" refers to methods of presenting information in formats such as text, visual aids, and videos in order to make the information easy for users to understand.

[0066] "Response" refers to the level of understanding and feedback that users provide regarding the information they are given, and it is data that the system collects and uses to improve the information it provides.

[0067] The system of this invention operates in cooperation with a server, a terminal, and a user, enabling the provision of customized information based on individual skill information.

[0068] The user first accesses the system using their own device and logs into their account. The device collects the user's skills information and sends it to the server. This information includes specific data about the user's past work history and skill set.

[0069] The server utilizes a generative AI model to generate appropriate information retrieval commands based on the user's skills. These commands are customized to make it easier for the user to identify the information they need. For example, if a user wants to learn about cloud infrastructure, the server will generate queries in a format that is easy for that user to understand.

[0070] Using the generated information retrieval commands, the server searches for internal and external information resources and collects relevant information. This collected information is tailored according to the user's skill level. Specifically, less experienced users are provided with basic information, while experienced users are provided with detailed technical information.

[0071] The terminal provides the user with refined information received from the server. This information is presented in various formats, such as text, visual explanations, or videos, and is displayed according to the user's preferences. Through this process, the user can efficiently learn at a level that suits their skill level. An example of a prompt might be, "Please explain the basic concepts of cloud infrastructure for beginners."

[0072] The system further collects user feedback from the terminal and sends it to the server. The server analyzes this data and uses a generative AI model to improve the information provided. This process allows the system to continuously provide information optimized for the user.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The user accesses the system using a terminal and logs into their account. As input, the user provides their login information along with their skill information. The terminal sends this information to the server. As output, the user's skill information is passed to the server and used in the next step.

[0076] Step 2:

[0077] The server generates appropriate information retrieval commands using a generative AI model based on the skills information received from the user. The input is the user's skills information, and the output is the generated search commands. As part of data processing, the skills information is analyzed to form commands for searching for highly relevant information. Specifically, the server designs the optimal search query based on the user's experience and skill set.

[0078] Step 3:

[0079] The server executes generated information retrieval commands and searches for internal and external information resources. As input, it uses the generated search commands to collect information from internal and external data sources. As output, the relevant information data is stored on the server. Data processing involves information collection and filtering. Specifically, the server scans multiple databases and collects information that matches the user's needs.

[0080] Step 4:

[0081] The server adjusts and customizes the collected information based on the user's skill level. Inputs include collected information and the user's skill level. The output is customized information. The data processing involves organizing the information in a format best suited to the user's understanding. Specifically, if the user is a beginner, basic information will be presented prominently.

[0082] Step 5:

[0083] The terminal displays customized information received from the server to the user. The input is customized information received from the server. The output is information provided to the user in visual or text format. Specifically, the user can view the information in their chosen format, enabling efficient learning.

[0084] Step 6:

[0085] The terminal collects user feedback and sends it to the server. The input is user feedback, and the output is aggregated feedback data sent to the server. Specifically, users input their understanding and evaluation of the provided information, which is then used to improve future information provision.

[0086] (Application Example 1)

[0087] 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."

[0088] Traditional online learning platforms have not adequately provided optimized educational content tailored to users' skill levels and learning speeds, failing to fully address individual learning needs. This has resulted in difficulties for users to learn efficiently and hindered improvements in learning effectiveness.

[0089] 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.

[0090] In this invention, the server includes means for acquiring user experience information, means for generating appropriate search queries based on the user experience information, and means for optimizing predetermined learning content according to the user's skill level. This provides users with customized learning content, enabling effective learning tailored to their individual needs.

[0091] "User experience information" refers to information about a user's past work history and skill set, and is data used to identify an individual's knowledge level and experience.

[0092] A "search query" is a command generated to explore a relevant data set, and is text or code that contains conditions for precisely retrieving specific information.

[0093] A "relevant data set" refers to a collection of data accessed based on specified search criteria, and is a database or information source used to provide the information the user is seeking.

[0094] "Customization" is the process of adjusting information to suit the individual user's needs and skill level, and providing it in the most appropriate form.

[0095] A "generative AI model" is a type of artificial intelligence that learns patterns from large amounts of data and generates appropriate output based on the input, which is used to optimize information provision and analyze feedback.

[0096] "External information sources" refer not only to databases within the system, but also to additional information resources obtained from the internet or other systems.

[0097] The system for implementing this invention consists of a user terminal, a central server for processing information, and an external information source. The user first accesses the system through the terminal and logs into an account for skill improvement. The terminal utilizes React Native to achieve cross-platform compatibility, enabling smooth operation on smartphones and tablets.

[0098] The terminal sends user experience information, specifically past work history and evaluation information, to the server. Based on this information, the server generates appropriate search queries. These search queries use GOOGLE FI® rebase to search a database in the cloud and aggregate the necessary information. During this process, optimization is performed according to the user's skill level, and predetermined learning content is adjusted accordingly.

[0099] Furthermore, it utilizes generative AI models (such as the Hugging Face AI model) to determine whether the information provided matches the user's needs. The data obtained as feedback is reflected in subsequent search queries, enabling continuous optimization. The server performs these calculations using the AWS® platform, ensuring fast and secure information delivery.

[0100] As a concrete example, when a newly hired employee needs to acquire specialized knowledge in a particular field, this system can be used to recommend learning materials tailored to their knowledge level. For instance, a prompt to the generative AI model might be: "Please provide recommended learning content tailored to each user's current level, with the aim of improving sales skills. In particular, please include content that will help strengthen negotiation techniques."

[0101] Therefore, this invention is designed to enable users to quickly and efficiently acquire content, dramatically improving learning effectiveness by providing information perfectly matched to each user's knowledge level.

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The terminal provides an interface for users to log in to the system. It receives the user's ID and password as input and sends them to the authentication server. The server compares the authentication information with the database to verify that the user is legitimate. Once authentication is complete, it retrieves the user's past experience information from the database and sends it to the terminal.

[0105] Step 2:

[0106] The server generates appropriate search queries based on the user's experience information. This process uses data mining techniques to derive search criteria that match the user's knowledge level and areas of interest. The output is a search query optimized for the user.

[0107] Step 3:

[0108] The server uses the generated search query to explore relevant data sets. Here, it filters the information on Google® Firebase and selects relevant learning content. The search query is used as input, and the filtered information is obtained as output.

[0109] Step 4:

[0110] The server customizes the acquired information according to the user's skill level. It utilizes a generative AI model to analyze the user's learning history and feedback, adjusting the display format and content of the information. This ensures that information is provided in a way that is easy for the user to understand.

[0111] Step 5:

[0112] The terminal provides customized information to the user. This information is displayed in text, visual, or video format. Input is customized information from the server, and output is the content displayed on the user's screen.

[0113] Step 6:

[0114] Users learn from the information provided and send feedback through their devices. This feedback includes their assessment of their understanding and the relevance of the content.

[0115] Step 7:

[0116] The device sends user feedback to the server. The server analyzes this information and further optimizes the next information delivery through a generative AI model. In this way, the system can continuously improve its learning efficiency.

[0117] 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.

[0118] The system of the present invention not only provides customized information based on the user's knowledge and skills, but also enables more adaptive information delivery that takes into account the user's emotions. It comprises an advanced system based on the interaction between the server, terminal, and user.

[0119] When a user accesses the system through a terminal and requests specific information, the terminal incorporates sensors that recognize the user's experience information and emotional state. The emotional state is determined by an emotion engine based on the user's facial expressions, tone of voice, input patterns, and other factors.

[0120] The device combines the user's acquired experience information and emotional state data and sends it to the server. The server uses this information to generate search queries optimized for the user and explore relevant internal databases and external resources. Depending on the emotional state, for example, if the user is stressed, the information can be simplified or content with a relaxing effect can be prioritized.

[0121] The collected information is customized to be most effectively communicated based on the user's current emotional state. When relaxed, a detailed, technical explanation is provided, while when emotionally unstable, concise and easy-to-understand content is offered. The device presents the customized information to the user, delivering it in a format that is easily accepted by the user.

[0122] Users provide feedback through their devices on how they receive and use information. This feedback, along with the user's emotional state supplemented by an emotion engine, is sent to the server and used to improve the information delivery process in the future. Thus, the present invention is a system that takes into account the individual emotional state of each user, enabling more personalized information delivery.

[0123] For example, if a user is feeling stressed while trying to learn new technical information, this system recognizes that emotion and provides the information in a less burdensome, visually easy-to-understand format. This allows the user to reduce stress while increasing learning efficiency.

[0124] The following describes the processing flow.

[0125] Step 1:

[0126] The user logs into the system via a terminal. The terminal uses sensors to analyze the user's facial expressions and voice tone, and uses an emotion engine to recognize their emotional state. The terminal then sends the emotional state and experience information to the server.

[0127] Step 2:

[0128] Based on the received experience information, the server generates search queries appropriate to the user's skill level. Depending on the emotional state, it adjusts the queries and selects keywords to search for information best suited to the user's current mental state.

[0129] Step 3:

[0130] The server searches relevant databases and external information resources based on the generated query. The sentiment engine selects content considering the user's emotions and collects high-priority information.

[0131] Step 4:

[0132] The server customizes the collected information and organizes it in a format best suited to the user's emotional state. The information is adjusted according to the user's needs, ranging from detailed technical data to simplified versions with extensive use of visual aids.

[0133] Step 5:

[0134] The device provides the user with customized information received from the server. It presents the information in the most easily understandable format, tailored to the user's emotional state, ensuring they receive the information without experiencing stress.

[0135] Step 6:

[0136] The user reviews the displayed information and provides feedback on their emotional response and level of understanding via the device. The device then sends this feedback to the server.

[0137] Step 7:

[0138] The server analyzes the feedback and uses an emotion engine to improve the information delivery mechanism. This feedback loop allows the system to provide even more personalized information in the future.

[0139] (Example 2)

[0140] 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 will be referred to as the "terminal."

[0141] While existing information delivery systems can provide information based on the user's experience and knowledge level, they fail to consider the user's emotional state. This can lead to user stress and affect the ease with which information is received. This invention proposes a system that appropriately grasps the user's emotional state and provides information accordingly quickly and effectively.

[0142] 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.

[0143] In this invention, the server includes means for acquiring user experience information and emotional information, means for evaluating the user's emotional state based on the information, and means for generating an optimal search query based on the evaluation. This makes it possible to provide information tailored to the user's emotional state.

[0144] "User experience information" refers to information about the knowledge and skills that a user has acquired to date.

[0145] "Emotional information" refers to information that indicates the user's current mental state, and includes data obtained from facial expressions, tone of voice, input patterns, etc.

[0146] "Assessing emotional state" means analyzing acquired emotional information to determine what emotions the user is experiencing.

[0147] "Generating search queries" means creating search criteria to retrieve the most relevant information based on the user's experience and emotional state.

[0148] "External and internal information sources" refer to all information storage locations that the server can access to retrieve information, including databases on the internet and internal company databases.

[0149] "Adjusting and customizing" is the process of transforming explored information into a format appropriate to the user's specific needs and emotional state.

[0150] "To present" means to ultimately display information obtained from the server to the user.

[0151] This invention is an information provision system that customizes information according to the user's emotional state. The system includes a terminal, a server, and sensors for collecting emotional information.

[0152] Users access the system via a terminal. The terminal incorporates cameras and microphones to recognize the user's facial expressions, voice tone, and input patterns. Using the data collected from these sensors, the system acquires the user's emotional information and uses an emotion engine to determine their emotional state. The emotion engine is based on a generative AI model and performs real-time emotional evaluation.

[0153] User sentiment and experience information transmitted from the device is received by the server. Based on this information, the server creates the optimal search query. The search query is used to explore relevant information through access to external and internal information sources. The server adjusts and customizes the data obtained from the search according to the user's sentiment state and converts it into a format that can be presented to the user.

[0154] For example, if a user is trying to learn technical content but their emotion sensor detects that they are experiencing stress, the server will convert the learning content into an easily understandable infographic or video format and provide it to them.

[0155] An example of a prompt message generated in this case would be: "The user is trying to search for technical information but is feeling stressed. Please suggest ways to present the information visually in a simplified manner so that he can understand it in a relaxed state."

[0156] This system allows users to receive information in a way that suits their emotional state, resulting in more efficient and effective information acquisition.

[0157] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0158] Step 1:

[0159] The user activates the device and accesses the information provision system. Input includes the user's basic information and the purpose or keywords they are searching for. The device uses emotion sensors such as a camera and microphone to collect the user's facial expressions and voice tone in real time. This allows the user's emotional information to be obtained. The output is a set of the user's emotional information and experience information.

[0160] Step 2:

[0161] The device sends acquired emotional and experiential information to the server. The input is the data collected in step 1. The server receives this data and uses an emotion engine to evaluate the user's emotional state. A generative AI model analyzes the emotional information to output a detailed emotional status. As a result, the evaluation of the emotional state and the priority of information to be presented to the user are determined.

[0162] Step 3:

[0163] The server generates the optimal search query based on the user's emotional state and the requested information. The input consists of the emotional state assessment and the search keywords received from the user. The generative AI model creates an appropriate search query and explores both external and internal information sources. The output is a list of highly relevant information.

[0164] Step 4:

[0165] The server adjusts and customizes information obtained from external and internal sources based on the user's emotional state. The input is the list of information obtained in step 3. The server adjusts the visual elements and language difficulty and converts the information into a format suitable for the user's state. The output is the customized set of information.

[0166] Step 5:

[0167] The terminal presents the user with customized information received from the server. The input is the customized information set generated in step 4. The terminal displays or delivers the information via audio in a format easily understood by the user, using its screen or audio device. The output is the information presented to the user.

[0168] Step 6:

[0169] Users review the information provided and offer feedback on how they received it and its effects. Input consists of the user's comments and evaluations. The device collects this data and sends it to the server. Output is feedback data used to improve future data collection and information presentation.

[0170] (Application Example 2)

[0171] 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".

[0172] When users acquire information, especially when they require information customized according to their emotional state, conventional systems struggle to provide information that adequately considers the user's emotional state. As a result, users have difficulty properly understanding and utilizing the information they receive, leading to a decrease in information utilization efficiency. Furthermore, the lack of emotionally responsive content prevents the system from maximizing the user experience.

[0173] 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.

[0174] In this invention, the server includes means for generating appropriate search queries based on the user's experience information and emotional state, means for searching relevant databases and external knowledge, and means for recognizing and determining the user's emotions. This makes it possible to provide content optimized based on the emotional state.

[0175] "User experience information" refers to information about the knowledge and skills that users have acquired to date, and is used to optimize information provision services.

[0176] "Emotional state" refers to the user's psychological state and is determined from factors such as facial expressions, tone of voice, and input patterns.

[0177] A "search query" is a command generated to find specific information, and it is created based on the user's experience and emotional state.

[0178] A "related database" is a collection of data where the information to be provided is stored, and it is searched based on search queries.

[0179] "External knowledge" refers to knowledge obtained from information sources outside of the system's database, and is used to improve the quality of information provided.

[0180] "Content" refers to the information and entertainment provided to users, and is selected with consideration for the user's emotional state.

[0181] "Emotion recognition functionality" is a technology that analyzes a user's facial expressions and voice to determine their emotional state, and is used to optimize information delivery.

[0182] "Feedback" refers to users' reactions and evaluations of the information and services provided, and is used to improve future services.

[0183] This invention relates to a system that optimizes information delivery by utilizing user experience information and emotional states.

[0184] This system primarily consists of interactions between a server, a terminal, and the user. The terminal is equipped with sensors to detect the user's facial expressions, voice tone, and input patterns. This activates an emotion recognition function that determines the user's emotional state. The terminal is responsible for collecting this data and transmitting it to the server.

[0185] The server generates an optimal search query based on the user's received experience information and emotional state. This search query is used to explore relevant databases and external knowledge. The server integrates this information, selects content that matches the user's current emotional state, and presents customized information to the user through the device.

[0186] For example, when a user is feeling tired from work, the system can recommend relaxing music. Similarly, when a user is feeling active, it can provide new recipes or educational videos.

[0187] This system also collects user feedback to help improve future information delivery. The feedback is sent to the server and analyzed to improve the effectiveness of information delivery and help provide a more personalized experience.

[0188] (Example of a prompt message)

[0189] An example of a prompt might be, "Analyze the user's face and voice, and generate optimal relaxation content tailored to their emotional state." Through such prompts, the system utilizes a generative AI model to provide content optimized for the user.

[0190] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0191] Step 1:

[0192] The device uses sensors to acquire data on the user's facial expressions and voice tone. This data is input into the emotion recognition function and used as basic information to determine the user's emotional state. By analyzing changes in facial expressions and pitch, the emotion engine outputs specific emotional states such as "tired" or "energetic."

[0193] Step 2:

[0194] The terminal sends acquired user experience information and emotional state data to the server. The server receives this information as input and processes the data to generate appropriate search queries. Here, data calculations are performed to determine which information the system should prioritize based on information about the user's skills and emotional state. The generated queries become commands for information retrieval.

[0195] Step 3:

[0196] The server uses the generated search query to explore relevant databases and external knowledge sources. It filters the information within the database and selects information that matches the user's emotional state. For example, for a user who needs to relax, it selects upbeat music or visually pleasing images as output. On the other hand, users who are highly motivated to learn are presented with learning videos and technical materials.

[0197] Step 4:

[0198] The device receives customized information from the server and presents it in an appropriate format according to the user's emotional state. Here, data processing is performed to display the selected content in an easy-to-understand manner for the user. For example, a summary is displayed for text, and a preview is displayed for video, ensuring that the user can effectively receive the information.

[0199] Step 5:

[0200] Users receive the provided information and send feedback to the system via their device. This feedback is used to improve the information provision process in the future. The feedback data is aggregated on the server and processed to serve as a reference when reviewing the criteria for selecting the information provided. This process further personalizes the user experience and improves the accuracy of the information provided.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] [Second Embodiment]

[0205] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0206] 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.

[0207] 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).

[0208] 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.

[0209] 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.

[0210] 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).

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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".

[0217] The system of this invention enables users to efficiently acquire customized information based on their own knowledge and skills. It operates through the coordinated efforts of three elements: a server, a terminal, and the user.

[0218] First, the user accesses the system through a terminal and logs into their account. The terminal sends data to the server to identify the user's experience and knowledge level. This information includes past work history and skill set.

[0219] The server generates appropriate search queries based on the user's experience. These search queries are customized to more accurately find the information the user needs. For example, if a user wants to learn about new technologies related to cloud infrastructure, the queries will be generated with a depth and scope that matches the user's experience.

[0220] Using the generated queries, the server searches relevant databases and external information resources to collect relevant information. The server then customizes this information based on the user's experience, providing basic explanations to less experienced users and detailed technical information to more knowledgeable users.

[0221] Next, the terminal displays customized information received from the server to the user. This information can be provided in various formats, such as text, visual aids, or videos, and is presented in a way that is easy for the user to understand. As a result, users can efficiently acquire content tailored to their skill level.

[0222] Furthermore, the device collects feedback on the user's reactions to and understanding of the information received, and sends it to the server. The server analyzes this feedback and uses generative AI to provide even more user-optimized information. This ensures that the overall system performance continues to improve.

[0223] For example, if a new employee wants to deepen their understanding of specific technical terms or technologies, this system automatically provides the most relevant information, streamlining self-study and supporting improved communication skills. Thus, this invention dramatically improves work efficiency and learning effectiveness by quickly and accurately providing information perfectly matched to each user's knowledge level.

[0224] The following describes the processing flow.

[0225] Step 1:

[0226] The user logs into the system via their device. The device sends the user's authentication information to the server, which retrieves the relevant information from the user's profile database.

[0227] Step 2:

[0228] Based on the acquired profile data, the server generates search queries tailored to the user's knowledge level and experience. The server then formats these queries appropriately and prepares them for the next search process.

[0229] Step 3:

[0230] The server uses the generated search query to explore relevant internal databases and external information resources. It aggregates the necessary data and filters it to best suit the user's needs.

[0231] Step 4:

[0232] The server customizes filtered information to suit the user's knowledge level. It generates basic content for beginners and more technical content for experienced users.

[0233] Step 5:

[0234] The terminal displays customized information received from the server to the user. The information is provided in a format that is easy for the user to understand, such as text, diagrams, or videos.

[0235] Step 6:

[0236] Users view the provided information and send feedback to the server via their device. This feedback may include comments on the usefulness of the information and additional questions.

[0237] Step 7:

[0238] The server analyzes user feedback and uses AI models to further improve future information delivery. This increases system accuracy and user satisfaction.

[0239] (Example 1)

[0240] 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".

[0241] The challenge lies in enabling the efficient acquisition and use of information tailored to individual skills and experience, thereby improving productivity in learning and work. In particular, finding the most relevant information from a vast amount of data is time-consuming and laborious, so an effective method is needed.

[0242] 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.

[0243] In this invention, the server includes means for acquiring user skill information, means for generating appropriate information retrieval commands based on the user skill information, and means for searching for internal and external information resources using the information retrieval commands. This makes it possible to efficiently retrieve information according to each user's skill level and present it in an appropriate format.

[0244] A "user" refers to an individual or organization that utilizes an information retrieval and provision system, and is the recipient of information customized based on their skills and information.

[0245] "Skills information" refers to data about a user's past work history and skill set, used to identify the user's knowledge level and experience.

[0246] An "information retrieval command" is a search query generated based on the user's skill information, and refers to a command used by the system to identify and obtain the information the user needs.

[0247] "Internal information resources" refer to databases and information libraries stored within the system, and include information that can be provided to users.

[0248] "External information resources" refer to databases and information sources outside the system, including information sources accessible via the internet.

[0249] "Adjustment" refers to the operation of appropriately filtering or sorting search results based on the user's skill information.

[0250] "Visualization" refers to methods of presenting information in formats such as text, visual aids, and videos in order to make the information easy for users to understand.

[0251] "Response" refers to the level of understanding and feedback that users provide regarding the information they are given, and it is data that the system collects and uses to improve the information it provides.

[0252] The system of this invention operates in cooperation with a server, a terminal, and a user, enabling the provision of customized information based on individual skill information.

[0253] The user first accesses the system using their own device and logs into their account. The device collects the user's skills information and sends it to the server. This information includes specific data about the user's past work history and skill set.

[0254] The server utilizes a generative AI model to generate appropriate information retrieval commands based on the user's skills. These commands are customized to make it easier for the user to identify the information they need. For example, if a user wants to learn about cloud infrastructure, the server will generate queries in a format that is easy for that user to understand.

[0255] Using the generated information retrieval commands, the server searches for internal and external information resources and collects relevant information. This collected information is tailored according to the user's skill level. Specifically, less experienced users are provided with basic information, while experienced users are provided with detailed technical information.

[0256] The terminal provides the user with refined information received from the server. This information is presented in various formats, such as text, visual explanations, or videos, and is displayed according to the user's preferences. Through this process, the user can efficiently learn at a level that suits their skill level. An example of a prompt might be, "Please explain the basic concepts of cloud infrastructure for beginners."

[0257] The system further collects user feedback from the terminal and sends it to the server. The server analyzes this data and uses a generative AI model to improve the information provided. This process allows the system to continuously provide information optimized for the user.

[0258] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0259] Step 1:

[0260] The user accesses the system using a terminal and logs into their account. As input, the user provides their login information along with their skill information. The terminal sends this information to the server. As output, the user's skill information is passed to the server and used in the next step.

[0261] Step 2:

[0262] The server generates appropriate information retrieval commands using a generative AI model based on the skills information received from the user. The input is the user's skills information, and the output is the generated search commands. As part of data processing, the skills information is analyzed to form commands for searching for highly relevant information. Specifically, the server designs the optimal search query based on the user's experience and skill set.

[0263] Step 3:

[0264] The server executes generated information retrieval commands and searches for internal and external information resources. As input, it uses the generated search commands to collect information from internal and external data sources. As output, the relevant information data is stored on the server. Data processing involves information collection and filtering. Specifically, the server scans multiple databases and collects information that matches the user's needs.

[0265] Step 4:

[0266] The server adjusts and customizes the collected information based on the user's skill level. Inputs include collected information and the user's skill level. The output is customized information. The data processing involves organizing the information in a format best suited to the user's understanding. Specifically, if the user is a beginner, basic information will be presented prominently.

[0267] Step 5:

[0268] The terminal displays customized information received from the server to the user. The input is customized information received from the server. The output is information provided to the user in visual or text format. Specifically, the user can view the information in their chosen format, enabling efficient learning.

[0269] Step 6:

[0270] The terminal collects user feedback and sends it to the server. The input is user feedback, and the output is aggregated feedback data sent to the server. Specifically, users input their understanding and evaluation of the provided information, which is then used to improve future information provision.

[0271] (Application Example 1)

[0272] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0273] Traditional online learning platforms have not adequately provided optimized educational content tailored to users' skill levels and learning speeds, failing to fully address individual learning needs. This has resulted in difficulties for users to learn efficiently and hindered improvements in learning effectiveness.

[0274] 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.

[0275] In this invention, the server includes means for acquiring user experience information, means for generating appropriate search queries based on the user experience information, and means for optimizing predetermined learning content according to the user's skill level. This provides users with customized learning content, enabling effective learning tailored to their individual needs.

[0276] "User experience information" refers to information about a user's past work history and skill set, and is data used to identify an individual's knowledge level and experience.

[0277] A "search query" is a command generated to explore a relevant data set, and is text or code that contains conditions for precisely retrieving specific information.

[0278] A "relevant data set" refers to a collection of data accessed based on specified search criteria, and is a database or information source used to provide the information the user is seeking.

[0279] "Customization" is the process of adjusting information to suit the individual user's needs and skill level, and providing it in the most appropriate form.

[0280] A "generative AI model" is a type of artificial intelligence that learns patterns from large amounts of data and generates appropriate output based on the input, which is used to optimize information provision and analyze feedback.

[0281] "External information sources" refer not only to databases within the system, but also to additional information resources obtained from the internet or other systems.

[0282] The system for implementing this invention consists of a user terminal, a central server for processing information, and an external information source. The user first accesses the system through the terminal and logs into an account for skill improvement. The terminal utilizes React Native to achieve cross-platform compatibility, enabling smooth operation on smartphones and tablets.

[0283] The terminal sends user experience information, specifically past work history and evaluation data, to the server. Based on this information, the server generates appropriate search queries. These queries utilize Google Firebase to search a cloud-based database and aggregate the necessary information. During this process, optimization is performed according to the user's skill level, and predetermined learning content is adjusted accordingly.

[0284] Furthermore, a generative AI model (e.g., an AI model from Hugging Face) is utilized to determine whether the provided information matches the user's needs. The data obtained as feedback is reflected in subsequent search queries, enabling continuous optimization. The server performs these calculations using the AWS platform to achieve fast and secure information provision.

[0285] As a specific example, when a newly hired employee acquires specialized knowledge in a particular field, using this system recommends teaching materials according to the individual's knowledge level. For example, a prompt sentence for the generative AI model such as "For the purpose of improving sales skills, please provide recommended learning content suitable for each user's current level. In particular, please include content that is useful for strengthening negotiation techniques." is used.

[0286] Therefore, this invention is designed so that users can acquire content quickly and efficiently, and by providing information that perfectly matches the knowledge level of each user, the learning effect is dramatically improved.

[0287] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0288] Step 1:

[0289] The terminal provides an interface for the user to log in to the system. It receives the user's ID and password as input and sends them to the authentication server. The server checks the authentication information against the database to confirm that the user is legitimate. When this authentication is completed, the user's past experience information is retrieved from the database and sent to the terminal.

[0290] Step 2:

[0291] The server generates appropriate search queries based on the user's experience information. This process uses data mining techniques to derive search criteria that match the user's knowledge level and areas of interest. The output is a search query optimized for the user.

[0292] Step 3:

[0293] The server uses the generated search query to explore relevant data sets. Here, it filters the information on Google Firebase and selects relevant learning content. The search query is used as input, and the filtered information is obtained as output.

[0294] Step 4:

[0295] The server customizes the acquired information according to the user's skill level. It utilizes a generative AI model to analyze the user's learning history and feedback, adjusting the display format and content of the information. This ensures that information is provided in a way that is easy for the user to understand.

[0296] Step 5:

[0297] The terminal provides customized information to the user. This information is displayed in text, visual, or video format. Input is customized information from the server, and output is the content displayed on the user's screen.

[0298] Step 6:

[0299] Users learn from the information provided and send feedback through their devices. This feedback includes their assessment of their understanding and the relevance of the content.

[0300] Step 7:

[0301] The device sends user feedback to the server. The server analyzes this information and further optimizes the next information delivery through a generative AI model. In this way, the system can continuously improve its learning efficiency.

[0302] 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.

[0303] The system of the present invention not only provides customized information based on the user's knowledge and skills, but also enables more adaptive information delivery that takes into account the user's emotions. It comprises an advanced system based on the interaction between the server, terminal, and user.

[0304] When a user accesses the system through a terminal and requests specific information, the terminal incorporates sensors that recognize the user's experience information and emotional state. The emotional state is determined by an emotion engine based on the user's facial expressions, tone of voice, input patterns, and other factors.

[0305] The device combines the user's acquired experience information and emotional state data and sends it to the server. The server uses this information to generate search queries optimized for the user and explore relevant internal databases and external resources. Depending on the emotional state, for example, if the user is stressed, the information can be simplified or content with a relaxing effect can be prioritized.

[0306] The collected information is customized to be most effectively communicated based on the user's current emotional state. When relaxed, a detailed, technical explanation is provided, while when emotionally unstable, concise and easy-to-understand content is offered. The device presents the customized information to the user, delivering it in a format that is easily accepted by the user.

[0307] The user provides feedback through the terminal on how to receive and utilize information. This feedback is sent to the server along with the user's emotional state complemented by the emotion engine, and is used to improve the information provision process for subsequent times. Thus, the present invention is a system that takes into account the individual emotional states of users and enables more personalized information provision.

[0308] As a specific example, when a user is trying to learn new technical information while feeling stressed, this system recognizes the emotion and provides the information in a less burdensome and more visually communicable form. Thereby, the user can enhance the learning efficiency while reducing stress.

[0309] The processing flow will be described below.

[0310] Step 1:

[0311] The user logs in to the system through the terminal. The terminal uses sensors to analyze the user's facial expressions and voice tones, and recognizes the emotional state using the emotion engine. The terminal transmits the emotional state and experience information to the server.

[0312] Step 2:

[0313] Based on the received experience information, the server generates a search query suitable for the user's skill level. Depending on the emotional state, the query is adjusted and keywords for searching for the information most suitable for the user's current mental state are selected.

[0314] Step 3:

[0315] Based on the generated query, the server searches the relevant database and external information resources. The emotion engine selects the content considering the user's emotion and collects the information with high priority.

[0316] Step 4:

[0317] The server customizes the collected information and organizes it in a format best suited to the user's emotional state. The information is adjusted according to the user's needs, ranging from detailed technical data to simplified versions with extensive use of visual aids.

[0318] Step 5:

[0319] The device provides the user with customized information received from the server. It presents the information in the most easily understandable format, tailored to the user's emotional state, ensuring they receive the information without experiencing stress.

[0320] Step 6:

[0321] The user reviews the displayed information and provides feedback on their emotional response and level of understanding via the device. The device then sends this feedback to the server.

[0322] Step 7:

[0323] The server analyzes the feedback and uses an emotion engine to improve the information delivery mechanism. This feedback loop allows the system to provide even more personalized information in the future.

[0324] (Example 2)

[0325] 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".

[0326] While existing information delivery systems can provide information based on the user's experience and knowledge level, they fail to consider the user's emotional state. This can lead to user stress and affect the ease with which information is received. This invention proposes a system that appropriately grasps the user's emotional state and provides information accordingly quickly and effectively.

[0327] 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.

[0328] In this invention, the server includes means for acquiring user experience information and emotional information, means for evaluating the user's emotional state based on the information, and means for generating an optimal search query based on the evaluation. This makes it possible to provide information tailored to the user's emotional state.

[0329] "User experience information" refers to information about the knowledge and skills that a user has acquired to date.

[0330] "Emotional information" refers to information that indicates the user's current mental state, and includes data obtained from facial expressions, tone of voice, input patterns, etc.

[0331] "Assessing emotional state" means analyzing acquired emotional information to determine what emotions the user is experiencing.

[0332] "Generating search queries" means creating search criteria to retrieve the most relevant information based on the user's experience and emotional state.

[0333] "External and internal information sources" refer to all information storage locations that the server can access to retrieve information, including databases on the internet and internal company databases.

[0334] "Adjusting and customizing" is the process of transforming explored information into a format appropriate to the user's specific needs and emotional state.

[0335] "To present" means to ultimately display information obtained from the server to the user.

[0336] This invention is an information provision system that customizes information according to the user's emotional state. The system includes a terminal, a server, and sensors for collecting emotional information.

[0337] Users access the system via a terminal. The terminal incorporates cameras and microphones to recognize the user's facial expressions, voice tone, and input patterns. Using the data collected from these sensors, the system acquires the user's emotional information and uses an emotion engine to determine their emotional state. The emotion engine is based on a generative AI model and performs real-time emotional evaluation.

[0338] User sentiment and experience information transmitted from the device is received by the server. Based on this information, the server creates the optimal search query. The search query is used to explore relevant information through access to external and internal information sources. The server adjusts and customizes the data obtained from the search according to the user's sentiment state and converts it into a format that can be presented to the user.

[0339] For example, if a user is trying to learn technical content but their emotion sensor detects that they are experiencing stress, the server will convert the learning content into an easily understandable infographic or video format and provide it to them.

[0340] An example of a prompt message generated in this case would be: "The user is trying to search for technical information but is feeling stressed. Please suggest ways to present the information visually in a simplified manner so that he can understand it in a relaxed state."

[0341] This system allows users to receive information in a way that suits their emotional state, resulting in more efficient and effective information acquisition.

[0342] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0343] Step 1:

[0344] The user activates the device and accesses the information provision system. Input includes the user's basic information and the purpose or keywords they are searching for. The device uses emotion sensors such as a camera and microphone to collect the user's facial expressions and voice tone in real time. This allows the user's emotional information to be obtained. The output is a set of the user's emotional information and experience information.

[0345] Step 2:

[0346] The device sends acquired emotional and experiential information to the server. The input is the data collected in step 1. The server receives this data and uses an emotion engine to evaluate the user's emotional state. A generative AI model analyzes the emotional information to output a detailed emotional status. As a result, the evaluation of the emotional state and the priority of information to be presented to the user are determined.

[0347] Step 3:

[0348] The server generates the optimal search query based on the user's emotional state and the requested information. The input consists of the emotional state assessment and the search keywords received from the user. The generative AI model creates an appropriate search query and explores both external and internal information sources. The output is a list of highly relevant information.

[0349] Step 4:

[0350] The server adjusts and customizes information obtained from external and internal sources based on the user's emotional state. The input is the list of information obtained in step 3. The server adjusts the visual elements and language difficulty and converts the information into a format suitable for the user's state. The output is the customized set of information.

[0351] Step 5:

[0352] The terminal presents the user with customized information received from the server. The input is the customized information set generated in step 4. The terminal displays or delivers the information via audio in a format easily understood by the user, using its screen or audio device. The output is the information presented to the user.

[0353] Step 6:

[0354] Users review the information provided and offer feedback on how they received it and its effects. Input consists of the user's comments and evaluations. The device collects this data and sends it to the server. Output is feedback data used to improve future data collection and information presentation.

[0355] (Application Example 2)

[0356] 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 as the "terminal".

[0357] When users acquire information, especially when they require information customized according to their emotional state, conventional systems struggle to provide information that adequately considers the user's emotional state. As a result, users have difficulty properly understanding and utilizing the information they receive, leading to a decrease in information utilization efficiency. Furthermore, the lack of emotionally responsive content prevents the system from maximizing the user experience.

[0358] 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.

[0359] In this invention, the server includes means for generating appropriate search queries based on the user's experience information and emotional state, means for searching relevant databases and external knowledge, and means for recognizing and determining the user's emotions. This makes it possible to provide content optimized based on the emotional state.

[0360] "User experience information" refers to information about the knowledge and skills that users have acquired to date, and is used to optimize information provision services.

[0361] "Emotional state" refers to the user's psychological state and is determined from factors such as facial expressions, tone of voice, and input patterns.

[0362] A "search query" is a command generated to find specific information, and it is created based on the user's experience and emotional state.

[0363] A "related database" is a collection of data where the information to be provided is stored, and it is searched based on search queries.

[0364] "External knowledge" refers to knowledge obtained from information sources outside of the system's database, and is used to improve the quality of information provided.

[0365] "Content" refers to the information and entertainment provided to users, and is selected with consideration for the user's emotional state.

[0366] "Emotion recognition functionality" is a technology that analyzes a user's facial expressions and voice to determine their emotional state, and is used to optimize information delivery.

[0367] "Feedback" refers to users' reactions and evaluations of the information and services provided, and is used to improve future services.

[0368] This invention relates to a system that optimizes information delivery by utilizing user experience information and emotional states.

[0369] This system primarily consists of interactions between a server, a terminal, and the user. The terminal is equipped with sensors to detect the user's facial expressions, voice tone, and input patterns. This activates an emotion recognition function that determines the user's emotional state. The terminal is responsible for collecting this data and transmitting it to the server.

[0370] The server generates an optimal search query based on the user's received experience information and emotional state. This search query is used to explore relevant databases and external knowledge. The server integrates this information, selects content that matches the user's current emotional state, and presents customized information to the user through the device.

[0371] For example, when a user is feeling tired from work, the system can recommend relaxing music. Similarly, when a user is feeling active, it can provide new recipes or educational videos.

[0372] This system also collects user feedback to help improve future information delivery. The feedback is sent to the server and analyzed to improve the effectiveness of information delivery and help provide a more personalized experience.

[0373] (Example of a prompt message)

[0374] An example of a prompt might be, "Analyze the user's face and voice, and generate optimal relaxation content tailored to their emotional state." Through such prompts, the system utilizes a generative AI model to provide content optimized for the user.

[0375] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0376] Step 1:

[0377] The device uses sensors to acquire data on the user's facial expressions and voice tone. This data is input into the emotion recognition function and used as basic information to determine the user's emotional state. By analyzing changes in facial expressions and pitch, the emotion engine outputs specific emotional states such as "tired" or "energetic."

[0378] Step 2:

[0379] The terminal sends acquired user experience information and emotional state data to the server. The server receives this information as input and processes the data to generate appropriate search queries. Here, data calculations are performed to determine which information the system should prioritize based on information about the user's skills and emotional state. The generated queries become commands for information retrieval.

[0380] Step 3:

[0381] The server uses the generated search query to explore relevant databases and external knowledge sources. It filters the information within the database and selects information that matches the user's emotional state. For example, for a user who needs to relax, it selects upbeat music or visually pleasing images as output. On the other hand, users who are highly motivated to learn are presented with learning videos and technical materials.

[0382] Step 4:

[0383] The device receives customized information from the server and presents it in an appropriate format according to the user's emotional state. Here, data processing is performed to display the selected content in an easy-to-understand manner for the user. For example, a summary is displayed for text, and a preview is displayed for video, ensuring that the user can effectively receive the information.

[0384] Step 5:

[0385] Users receive the provided information and send feedback to the system via their device. This feedback is used to improve the information provision process in the future. The feedback data is aggregated on the server and processed to serve as a reference when reviewing the criteria for selecting the information provided. This process further personalizes the user experience and improves the accuracy of the information provided.

[0386] 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.

[0387] 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.

[0388] 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.

[0389] [Third Embodiment]

[0390] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0391] 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.

[0392] 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).

[0393] 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.

[0394] 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.

[0395] 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).

[0396] 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.

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] 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".

[0402] The system of this invention enables users to efficiently acquire customized information based on their own knowledge and skills. It operates through the coordinated efforts of three elements: a server, a terminal, and the user.

[0403] First, the user accesses the system through a terminal and logs into their account. The terminal sends data to the server to identify the user's experience and knowledge level. This information includes past work history and skill set.

[0404] The server generates appropriate search queries based on the user's experience. These search queries are customized to more accurately find the information the user needs. For example, if a user wants to learn about new technologies related to cloud infrastructure, the queries will be generated with a depth and scope that matches the user's experience.

[0405] Using the generated queries, the server searches relevant databases and external information resources to collect relevant information. The server then customizes this information based on the user's experience, providing basic explanations to less experienced users and detailed technical information to more knowledgeable users.

[0406] Next, the terminal displays customized information received from the server to the user. This information can be provided in various formats, such as text, visual aids, or videos, and is presented in a way that is easy for the user to understand. As a result, users can efficiently acquire content tailored to their skill level.

[0407] Furthermore, the device collects feedback on the user's reactions to and understanding of the information received, and sends it to the server. The server analyzes this feedback and uses generative AI to provide even more user-optimized information. This ensures that the overall system performance continues to improve.

[0408] For example, if a new employee wants to deepen their understanding of specific technical terms or technologies, this system automatically provides the most relevant information, streamlining self-study and supporting improved communication skills. Thus, this invention dramatically improves work efficiency and learning effectiveness by quickly and accurately providing information perfectly matched to each user's knowledge level.

[0409] The following describes the processing flow.

[0410] Step 1:

[0411] The user logs into the system via their device. The device sends the user's authentication information to the server, which retrieves the relevant information from the user's profile database.

[0412] Step 2:

[0413] Based on the acquired profile data, the server generates search queries tailored to the user's knowledge level and experience. The server then formats these queries appropriately and prepares them for the next search process.

[0414] Step 3:

[0415] The server uses the generated search query to explore relevant internal databases and external information resources. It aggregates the necessary data and filters it to best suit the user's needs.

[0416] Step 4:

[0417] The server customizes filtered information to suit the user's knowledge level. It generates basic content for beginners and more technical content for experienced users.

[0418] Step 5:

[0419] The terminal displays customized information received from the server to the user. The information is provided in a format that is easy for the user to understand, such as text, diagrams, or videos.

[0420] Step 6:

[0421] Users view the provided information and send feedback to the server via their device. This feedback may include comments on the usefulness of the information and additional questions.

[0422] Step 7:

[0423] The server analyzes user feedback and uses AI models to further improve future information delivery. This increases system accuracy and user satisfaction.

[0424] (Example 1)

[0425] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0426] The challenge lies in enabling the efficient acquisition and use of information tailored to individual skills and experience, thereby improving productivity in learning and work. In particular, finding the most relevant information from a vast amount of data is time-consuming and laborious, so an effective method is needed.

[0427] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0428] In this invention, the server includes means for acquiring user skill information, means for generating appropriate information retrieval commands based on the user skill information, and means for searching for internal and external information resources using the information retrieval commands. This makes it possible to efficiently retrieve information according to each user's skill level and present it in an appropriate format.

[0429] A "user" refers to an individual or organization that utilizes an information retrieval and provision system, and is the recipient of information customized based on their skills and information.

[0430] "Skills information" refers to data about a user's past work history and skill set, used to identify the user's knowledge level and experience.

[0431] An "information retrieval command" is a search query generated based on the user's skill information, and refers to a command used by the system to identify and obtain the information the user needs.

[0432] "Internal information resources" refer to databases and information libraries stored within the system, and include information that can be provided to users.

[0433] "External information resources" refer to databases and information sources outside the system, including information sources accessible via the internet.

[0434] "Adjustment" refers to the operation of appropriately filtering or sorting search results based on the user's skill information.

[0435] "Visualization" refers to methods of presenting information in formats such as text, visual aids, and videos in order to make the information easy for users to understand.

[0436] "Response" refers to the level of understanding and feedback that users provide regarding the information they are given, and it is data that the system collects and uses to improve the information it provides.

[0437] The system of this invention operates in cooperation with a server, a terminal, and a user, enabling the provision of customized information based on individual skill information.

[0438] The user first accesses the system using their own device and logs into their account. The device collects the user's skills information and sends it to the server. This information includes specific data about the user's past work history and skill set.

[0439] The server utilizes a generative AI model to generate appropriate information retrieval commands based on the user's skills. These commands are customized to make it easier for the user to identify the information they need. For example, if a user wants to learn about cloud infrastructure, the server will generate queries in a format that is easy for that user to understand.

[0440] Using the generated information retrieval commands, the server searches for internal and external information resources and collects relevant information. This collected information is tailored according to the user's skill level. Specifically, less experienced users are provided with basic information, while experienced users are provided with detailed technical information.

[0441] The terminal provides the user with refined information received from the server. This information is presented in various formats, such as text, visual explanations, or videos, and is displayed according to the user's preferences. Through this process, the user can efficiently learn at a level that suits their skill level. An example of a prompt might be, "Please explain the basic concepts of cloud infrastructure for beginners."

[0442] The system further collects user feedback from the terminal and sends it to the server. The server analyzes this data and uses a generative AI model to improve the information provided. This process allows the system to continuously provide information optimized for the user.

[0443] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0444] Step 1:

[0445] The user accesses the system using a terminal and logs into their account. As input, the user provides their login information along with their skill information. The terminal sends this information to the server. As output, the user's skill information is passed to the server and used in the next step.

[0446] Step 2:

[0447] The server generates appropriate information retrieval commands using a generative AI model based on the skills information received from the user. The input is the user's skills information, and the output is the generated search commands. As part of data processing, the skills information is analyzed to form commands for searching for highly relevant information. Specifically, the server designs the optimal search query based on the user's experience and skill set.

[0448] Step 3:

[0449] The server executes generated information retrieval commands and searches for internal and external information resources. As input, it uses the generated search commands to collect information from internal and external data sources. As output, the relevant information data is stored on the server. Data processing involves information collection and filtering. Specifically, the server scans multiple databases and collects information that matches the user's needs.

[0450] Step 4:

[0451] The server adjusts and customizes the collected information based on the user's skill level. Inputs include collected information and the user's skill level. The output is customized information. The data processing involves organizing the information in a format best suited to the user's understanding. Specifically, if the user is a beginner, basic information will be presented prominently.

[0452] Step 5:

[0453] The terminal displays customized information received from the server to the user. The input is customized information received from the server. The output is information provided to the user in visual or text format. Specifically, the user can view the information in their chosen format, enabling efficient learning.

[0454] Step 6:

[0455] The terminal collects user feedback and sends it to the server. The input is user feedback, and the output is aggregated feedback data sent to the server. Specifically, users input their understanding and evaluation of the provided information, which is then used to improve future information provision.

[0456] (Application Example 1)

[0457] 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."

[0458] Traditional online learning platforms have not adequately provided optimized educational content tailored to users' skill levels and learning speeds, failing to fully address individual learning needs. This has resulted in difficulties for users to learn efficiently and hindered improvements in learning effectiveness.

[0459] 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.

[0460] In this invention, the server includes means for acquiring user experience information, means for generating appropriate search queries based on the user experience information, and means for optimizing predetermined learning content according to the user's skill level. This provides users with customized learning content, enabling effective learning tailored to their individual needs.

[0461] "User experience information" refers to information about a user's past work history and skill set, and is data used to identify an individual's knowledge level and experience.

[0462] A "search query" is a command generated to explore a relevant data set, and is text or code that contains conditions for precisely retrieving specific information.

[0463] A "relevant data set" refers to a collection of data accessed based on specified search criteria, and is a database or information source used to provide the information the user is seeking.

[0464] "Customization" is the process of adjusting information to suit the individual user's needs and skill level, and providing it in the most appropriate form.

[0465] A "generative AI model" is a type of artificial intelligence that learns patterns from large amounts of data and generates appropriate output based on the input, which is used to optimize information provision and analyze feedback.

[0466] "External information sources" refer not only to databases within the system, but also to additional information resources obtained from the internet or other systems.

[0467] The system for implementing this invention consists of a user terminal, a central server for processing information, and an external information source. The user first accesses the system through the terminal and logs into an account for skill improvement. The terminal utilizes React Native to achieve cross-platform compatibility, enabling smooth operation on smartphones and tablets.

[0468] The terminal sends user experience information, specifically past work history and evaluation data, to the server. Based on this information, the server generates appropriate search queries. These queries utilize Google Firebase to search a cloud-based database and aggregate the necessary information. During this process, optimization is performed according to the user's skill level, and predetermined learning content is adjusted accordingly.

[0469] Furthermore, it utilizes a generative AI model (for example, the AI ​​model used in Hugging Face) to determine whether the information provided matches the user's needs. The data obtained as feedback is reflected in subsequent search queries, enabling continuous optimization. The server performs these calculations using the AWS platform, ensuring fast and secure information delivery.

[0470] As a concrete example, when a newly hired employee needs to acquire specialized knowledge in a particular field, this system can be used to recommend learning materials tailored to their knowledge level. For instance, a prompt to the generative AI model might be: "Please provide recommended learning content tailored to each user's current level, with the aim of improving sales skills. In particular, please include content that will help strengthen negotiation techniques."

[0471] Therefore, this invention is designed to enable users to quickly and efficiently acquire content, dramatically improving learning effectiveness by providing information perfectly matched to each user's knowledge level.

[0472] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0473] Step 1:

[0474] The terminal provides an interface for users to log in to the system. It receives the user's ID and password as input and sends them to the authentication server. The server compares the authentication information with the database to verify that the user is legitimate. Once authentication is complete, it retrieves the user's past experience information from the database and sends it to the terminal.

[0475] Step 2:

[0476] The server generates appropriate search queries based on the user's experience information. This process uses data mining techniques to derive search criteria that match the user's knowledge level and areas of interest. The output is a search query optimized for the user.

[0477] Step 3:

[0478] The server uses the generated search query to explore relevant data sets. Here, it filters the information on Google Firebase and selects relevant learning content. The search query is used as input, and the filtered information is obtained as output.

[0479] Step 4:

[0480] The server customizes the acquired information according to the user's skill level. It utilizes a generative AI model to analyze the user's learning history and feedback, adjusting the display format and content of the information. This ensures that information is provided in a way that is easy for the user to understand.

[0481] Step 5:

[0482] The terminal provides customized information to the user. This information is displayed in text, visual, or video format. Input is customized information from the server, and output is the content displayed on the user's screen.

[0483] Step 6:

[0484] Users learn from the information provided and send feedback through their devices. This feedback includes their assessment of their understanding and the relevance of the content.

[0485] Step 7:

[0486] The device sends user feedback to the server. The server analyzes this information and further optimizes the next information delivery through a generative AI model. In this way, the system can continuously improve its learning efficiency.

[0487] 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.

[0488] The system of the present invention not only provides customized information based on the user's knowledge and skills, but also enables more adaptive information delivery that takes into account the user's emotions. It comprises an advanced system based on the interaction between the server, terminal, and user.

[0489] When a user accesses the system through a terminal and requests specific information, the terminal incorporates sensors that recognize the user's experience information and emotional state. The emotional state is determined by an emotion engine based on the user's facial expressions, tone of voice, input patterns, and other factors.

[0490] The device combines the user's acquired experience information and emotional state data and sends it to the server. The server uses this information to generate search queries optimized for the user and explore relevant internal databases and external resources. Depending on the emotional state, for example, if the user is stressed, the information can be simplified or content with a relaxing effect can be prioritized.

[0491] The collected information is customized to be most effectively communicated based on the user's current emotional state. When relaxed, a detailed, technical explanation is provided, while when emotionally unstable, concise and easy-to-understand content is offered. The device presents the customized information to the user, delivering it in a format that is easily accepted by the user.

[0492] Users provide feedback through their devices on how they receive and use information. This feedback, along with the user's emotional state supplemented by an emotion engine, is sent to the server and used to improve the information delivery process in the future. Thus, the present invention is a system that takes into account the individual emotional state of each user, enabling more personalized information delivery.

[0493] For example, if a user is feeling stressed while trying to learn new technical information, this system recognizes that emotion and provides the information in a less burdensome, visually easy-to-understand format. This allows the user to reduce stress while increasing learning efficiency.

[0494] The following describes the processing flow.

[0495] Step 1:

[0496] The user logs into the system via a terminal. The terminal uses sensors to analyze the user's facial expressions and voice tone, and uses an emotion engine to recognize their emotional state. The terminal then sends the emotional state and experience information to the server.

[0497] Step 2:

[0498] Based on the received experience information, the server generates search queries appropriate to the user's skill level. Depending on the emotional state, it adjusts the queries and selects keywords to search for information best suited to the user's current mental state.

[0499] Step 3:

[0500] The server searches relevant databases and external information resources based on the generated query. The sentiment engine selects content considering the user's emotions and collects high-priority information.

[0501] Step 4:

[0502] The server customizes the collected information and organizes it in a format best suited to the user's emotional state. The information is adjusted according to the user's needs, ranging from detailed technical data to simplified versions with extensive use of visual aids.

[0503] Step 5:

[0504] The device provides the user with customized information received from the server. It presents the information in the most easily understandable format, tailored to the user's emotional state, ensuring they receive the information without experiencing stress.

[0505] Step 6:

[0506] The user reviews the displayed information and provides feedback on their emotional response and level of understanding via the device. The device then sends this feedback to the server.

[0507] Step 7:

[0508] The server analyzes the feedback and uses an emotion engine to improve the information delivery mechanism. This feedback loop allows the system to provide even more personalized information in the future.

[0509] (Example 2)

[0510] 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."

[0511] While existing information delivery systems can provide information based on the user's experience and knowledge level, they fail to consider the user's emotional state. This can lead to user stress and affect the ease with which information is received. This invention proposes a system that appropriately grasps the user's emotional state and provides information accordingly quickly and effectively.

[0512] 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.

[0513] In this invention, the server includes means for acquiring user experience information and emotional information, means for evaluating the user's emotional state based on the information, and means for generating an optimal search query based on the evaluation. This makes it possible to provide information tailored to the user's emotional state.

[0514] "User experience information" refers to information about the knowledge and skills that a user has acquired to date.

[0515] "Emotional information" refers to information that indicates the user's current mental state, and includes data obtained from facial expressions, tone of voice, input patterns, etc.

[0516] "Assessing emotional state" means analyzing acquired emotional information to determine what emotions the user is experiencing.

[0517] "Generating search queries" means creating search criteria to retrieve the most relevant information based on the user's experience and emotional state.

[0518] "External and internal information sources" refer to all information storage locations that the server can access to retrieve information, including databases on the internet and internal company databases.

[0519] "Adjusting and customizing" is the process of transforming explored information into a format appropriate to the user's specific needs and emotional state.

[0520] "To present" means to ultimately display information obtained from the server to the user.

[0521] This invention is an information provision system that customizes information according to the user's emotional state. The system includes a terminal, a server, and sensors for collecting emotional information.

[0522] Users access the system via a terminal. The terminal incorporates cameras and microphones to recognize the user's facial expressions, voice tone, and input patterns. Using the data collected from these sensors, the system acquires the user's emotional information and uses an emotion engine to determine their emotional state. The emotion engine is based on a generative AI model and performs real-time emotional evaluation.

[0523] User sentiment and experience information transmitted from the device is received by the server. Based on this information, the server creates the optimal search query. The search query is used to explore relevant information through access to external and internal information sources. The server adjusts and customizes the data obtained from the search according to the user's sentiment state and converts it into a format that can be presented to the user.

[0524] For example, if a user is trying to learn technical content but their emotion sensor detects that they are experiencing stress, the server will convert the learning content into an easily understandable infographic or video format and provide it to them.

[0525] An example of a prompt message generated in this case would be: "The user is trying to search for technical information but is feeling stressed. Please suggest ways to present the information visually in a simplified manner so that he can understand it in a relaxed state."

[0526] This system allows users to receive information in a way that suits their emotional state, resulting in more efficient and effective information acquisition.

[0527] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0528] Step 1:

[0529] The user activates the device and accesses the information provision system. Input includes the user's basic information and the purpose or keywords they are searching for. The device uses emotion sensors such as a camera and microphone to collect the user's facial expressions and voice tone in real time. This allows the user's emotional information to be obtained. The output is a set of the user's emotional information and experience information.

[0530] Step 2:

[0531] The device sends acquired emotional and experiential information to the server. The input is the data collected in step 1. The server receives this data and uses an emotion engine to evaluate the user's emotional state. A generative AI model analyzes the emotional information to output a detailed emotional status. As a result, the evaluation of the emotional state and the priority of information to be presented to the user are determined.

[0532] Step 3:

[0533] The server generates the optimal search query based on the user's emotional state and the requested information. The input consists of the emotional state assessment and the search keywords received from the user. The generative AI model creates an appropriate search query and explores both external and internal information sources. The output is a list of highly relevant information.

[0534] Step 4:

[0535] The server adjusts and customizes information obtained from external and internal sources based on the user's emotional state. The input is the list of information obtained in step 3. The server adjusts the visual elements and language difficulty and converts the information into a format suitable for the user's state. The output is the customized set of information.

[0536] Step 5:

[0537] The terminal presents the user with customized information received from the server. The input is the customized information set generated in step 4. The terminal displays or delivers the information via audio in a format easily understood by the user, using its screen or audio device. The output is the information presented to the user.

[0538] Step 6:

[0539] Users review the information provided and offer feedback on how they received it and its effects. Input consists of the user's comments and evaluations. The device collects this data and sends it to the server. Output is feedback data used to improve future data collection and information presentation.

[0540] (Application Example 2)

[0541] 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."

[0542] When users acquire information, especially when they require information customized according to their emotional state, conventional systems struggle to provide information that adequately considers the user's emotional state. As a result, users have difficulty properly understanding and utilizing the information they receive, leading to a decrease in information utilization efficiency. Furthermore, the lack of emotionally responsive content prevents the system from maximizing the user experience.

[0543] 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.

[0544] In this invention, the server includes means for generating appropriate search queries based on the user's experience information and emotional state, means for searching relevant databases and external knowledge, and means for recognizing and determining the user's emotions. This makes it possible to provide content optimized based on the emotional state.

[0545] "User experience information" refers to information about the knowledge and skills that users have acquired to date, and is used to optimize information provision services.

[0546] "Emotional state" refers to the user's psychological state and is determined from factors such as facial expressions, tone of voice, and input patterns.

[0547] A "search query" is a command generated to find specific information, and it is created based on the user's experience and emotional state.

[0548] A "related database" is a collection of data where the information to be provided is stored, and it is searched based on search queries.

[0549] "External knowledge" refers to knowledge obtained from information sources outside of the system's database, and is used to improve the quality of information provided.

[0550] "Content" refers to the information and entertainment provided to users, and is selected with consideration for the user's emotional state.

[0551] "Emotion recognition functionality" is a technology that analyzes a user's facial expressions and voice to determine their emotional state, and is used to optimize information delivery.

[0552] "Feedback" refers to users' reactions and evaluations of the information and services provided, and is used to improve future services.

[0553] This invention relates to a system that optimizes information delivery by utilizing user experience information and emotional states.

[0554] This system primarily consists of interactions between a server, a terminal, and the user. The terminal is equipped with sensors to detect the user's facial expressions, voice tone, and input patterns. This activates an emotion recognition function that determines the user's emotional state. The terminal is responsible for collecting this data and transmitting it to the server.

[0555] The server generates an optimal search query based on the user's received experience information and emotional state. This search query is used to explore relevant databases and external knowledge. The server integrates this information, selects content that matches the user's current emotional state, and presents customized information to the user through the device.

[0556] For example, when a user is feeling tired from work, the system can recommend relaxing music. Similarly, when a user is feeling active, it can provide new recipes or educational videos.

[0557] This system also collects user feedback to help improve future information delivery. The feedback is sent to the server and analyzed to improve the effectiveness of information delivery and help provide a more personalized experience.

[0558] (Example of a prompt message)

[0559] An example of a prompt might be, "Analyze the user's face and voice, and generate optimal relaxation content tailored to their emotional state." Through such prompts, the system utilizes a generative AI model to provide content optimized for the user.

[0560] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0561] Step 1:

[0562] The device uses sensors to acquire data on the user's facial expressions and voice tone. This data is input into the emotion recognition function and used as basic information to determine the user's emotional state. By analyzing changes in facial expressions and pitch, the emotion engine outputs specific emotional states such as "tired" or "energetic."

[0563] Step 2:

[0564] The terminal sends acquired user experience information and emotional state data to the server. The server receives this information as input and processes the data to generate appropriate search queries. Here, data calculations are performed to determine which information the system should prioritize based on information about the user's skills and emotional state. The generated queries become commands for information retrieval.

[0565] Step 3:

[0566] The server uses the generated search query to explore relevant databases and external knowledge sources. It filters the information within the database and selects information that matches the user's emotional state. For example, for a user who needs to relax, it selects upbeat music or visually pleasing images as output. On the other hand, users who are highly motivated to learn are presented with learning videos and technical materials.

[0567] Step 4:

[0568] The device receives customized information from the server and presents it in an appropriate format according to the user's emotional state. Here, data processing is performed to display the selected content in an easy-to-understand manner for the user. For example, a summary is displayed for text, and a preview is displayed for video, ensuring that the user can effectively receive the information.

[0569] Step 5:

[0570] Users receive the provided information and send feedback to the system via their device. This feedback is used to improve the information provision process in the future. The feedback data is aggregated on the server and processed to serve as a reference when reviewing the criteria for selecting the information provided. This process further personalizes the user experience and improves the accuracy of the information provided.

[0571] 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.

[0572] 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.

[0573] 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.

[0574] [Fourth Embodiment]

[0575] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0576] 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.

[0577] 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).

[0578] 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.

[0579] 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.

[0580] 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).

[0581] 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.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] 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.

[0586] 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.

[0587] 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".

[0588] The system of this invention enables users to efficiently acquire customized information based on their own knowledge and skills. It operates through the coordinated efforts of three elements: a server, a terminal, and the user.

[0589] First, the user accesses the system through a terminal and logs into their account. The terminal sends data to the server to identify the user's experience and knowledge level. This information includes past work history and skill set.

[0590] The server generates appropriate search queries based on the user's experience. These search queries are customized to more accurately find the information the user needs. For example, if a user wants to learn about new technologies related to cloud infrastructure, the queries will be generated with a depth and scope that matches the user's experience.

[0591] Using the generated queries, the server searches relevant databases and external information resources to collect relevant information. The server then customizes this information based on the user's experience, providing basic explanations to less experienced users and detailed technical information to more knowledgeable users.

[0592] Next, the terminal displays customized information received from the server to the user. This information can be provided in various formats, such as text, visual aids, or videos, and is presented in a way that is easy for the user to understand. As a result, users can efficiently acquire content tailored to their skill level.

[0593] Furthermore, the device collects feedback on the user's reactions to and understanding of the information received, and sends it to the server. The server analyzes this feedback and uses generative AI to provide even more user-optimized information. This ensures that the overall system performance continues to improve.

[0594] For example, if a new employee wants to deepen their understanding of specific technical terms or technologies, this system automatically provides the most relevant information, streamlining self-study and supporting improved communication skills. Thus, this invention dramatically improves work efficiency and learning effectiveness by quickly and accurately providing information perfectly matched to each user's knowledge level.

[0595] The following describes the processing flow.

[0596] Step 1:

[0597] The user logs into the system via their device. The device sends the user's authentication information to the server, which retrieves the relevant information from the user's profile database.

[0598] Step 2:

[0599] Based on the acquired profile data, the server generates search queries tailored to the user's knowledge level and experience. The server then formats these queries appropriately and prepares them for the next search process.

[0600] Step 3:

[0601] The server uses the generated search query to explore relevant internal databases and external information resources. It aggregates the necessary data and filters it to best suit the user's needs.

[0602] Step 4:

[0603] The server customizes filtered information to suit the user's knowledge level. It generates basic content for beginners and more technical content for experienced users.

[0604] Step 5:

[0605] The terminal displays customized information received from the server to the user. The information is provided in a format that is easy for the user to understand, such as text, diagrams, or videos.

[0606] Step 6:

[0607] Users view the provided information and send feedback to the server via their device. This feedback may include comments on the usefulness of the information and additional questions.

[0608] Step 7:

[0609] The server analyzes user feedback and uses AI models to further improve future information delivery. This increases system accuracy and user satisfaction.

[0610] (Example 1)

[0611] 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".

[0612] The challenge lies in enabling the efficient acquisition and use of information tailored to individual skills and experience, thereby improving productivity in learning and work. In particular, finding the most relevant information from a vast amount of data is time-consuming and laborious, so an effective method is needed.

[0613] 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.

[0614] In this invention, the server includes means for acquiring user skill information, means for generating appropriate information retrieval commands based on the user skill information, and means for searching for internal and external information resources using the information retrieval commands. This makes it possible to efficiently retrieve information according to each user's skill level and present it in an appropriate format.

[0615] A "user" refers to an individual or organization that utilizes an information retrieval and provision system, and is the recipient of information customized based on their skills and information.

[0616] "Skills information" refers to data about a user's past work history and skill set, used to identify the user's knowledge level and experience.

[0617] An "information retrieval command" is a search query generated based on the user's skill information, and refers to a command used by the system to identify and obtain the information the user needs.

[0618] "Internal information resources" refer to databases and information libraries stored within the system, and include information that can be provided to users.

[0619] "External information resources" refer to databases and information sources outside the system, including information sources accessible via the internet.

[0620] "Adjustment" refers to the operation of appropriately filtering or sorting search results based on the user's skill information.

[0621] "Visualization" refers to methods of presenting information in formats such as text, visual aids, and videos in order to make the information easy for users to understand.

[0622] "Response" refers to the level of understanding and feedback that users provide regarding the information they are given, and it is data that the system collects and uses to improve the information it provides.

[0623] The system of this invention operates in cooperation with a server, a terminal, and a user, enabling the provision of customized information based on individual skill information.

[0624] The user first accesses the system using their own device and logs into their account. The device collects the user's skills information and sends it to the server. This information includes specific data about the user's past work history and skill set.

[0625] The server utilizes a generative AI model to generate appropriate information retrieval commands based on the user's skills. These commands are customized to make it easier for the user to identify the information they need. For example, if a user wants to learn about cloud infrastructure, the server will generate queries in a format that is easy for that user to understand.

[0626] Using the generated information retrieval commands, the server searches for internal and external information resources and collects relevant information. This collected information is tailored according to the user's skill level. Specifically, less experienced users are provided with basic information, while experienced users are provided with detailed technical information.

[0627] The terminal provides the user with refined information received from the server. This information is presented in various formats, such as text, visual explanations, or videos, and is displayed according to the user's preferences. Through this process, the user can efficiently learn at a level that suits their skill level. An example of a prompt might be, "Please explain the basic concepts of cloud infrastructure for beginners."

[0628] The system further collects user feedback from the terminal and sends it to the server. The server analyzes this data and uses a generative AI model to improve the information provided. This process allows the system to continuously provide information optimized for the user.

[0629] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0630] Step 1:

[0631] The user accesses the system using a terminal and logs into their account. As input, the user provides their login information along with their skill information. The terminal sends this information to the server. As output, the user's skill information is passed to the server and used in the next step.

[0632] Step 2:

[0633] The server generates appropriate information retrieval commands using a generative AI model based on the skills information received from the user. The input is the user's skills information, and the output is the generated search commands. As part of data processing, the skills information is analyzed to form commands for searching for highly relevant information. Specifically, the server designs the optimal search query based on the user's experience and skill set.

[0634] Step 3:

[0635] The server executes generated information retrieval commands and searches for internal and external information resources. As input, it uses the generated search commands to collect information from internal and external data sources. As output, the relevant information data is stored on the server. Data processing involves information collection and filtering. Specifically, the server scans multiple databases and collects information that matches the user's needs.

[0636] Step 4:

[0637] The server adjusts and customizes the collected information based on the user's skill level. Inputs include collected information and the user's skill level. The output is customized information. The data processing involves organizing the information in a format best suited to the user's understanding. Specifically, if the user is a beginner, basic information will be presented prominently.

[0638] Step 5:

[0639] The terminal displays customized information received from the server to the user. The input is customized information received from the server. The output is information provided to the user in visual or text format. Specifically, the user can view the information in their chosen format, enabling efficient learning.

[0640] Step 6:

[0641] The terminal collects user feedback and sends it to the server. The input is user feedback, and the output is aggregated feedback data sent to the server. Specifically, users input their understanding and evaluation of the provided information, which is then used to improve future information provision.

[0642] (Application Example 1)

[0643] 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".

[0644] Traditional online learning platforms have not adequately provided optimized educational content tailored to users' skill levels and learning speeds, failing to fully address individual learning needs. This has resulted in difficulties for users to learn efficiently and hindered improvements in learning effectiveness.

[0645] 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.

[0646] In this invention, the server includes means for acquiring user experience information, means for generating appropriate search queries based on the user experience information, and means for optimizing predetermined learning content according to the user's skill level. This provides users with customized learning content, enabling effective learning tailored to their individual needs.

[0647] "User experience information" refers to information about a user's past work history and skill set, and is data used to identify an individual's knowledge level and experience.

[0648] A "search query" is a command generated to explore a relevant data set, and is text or code that contains conditions for precisely retrieving specific information.

[0649] A "relevant data set" refers to a collection of data accessed based on specified search criteria, and is a database or information source used to provide the information the user is seeking.

[0650] "Customization" is the process of adjusting information to suit the individual user's needs and skill level, and providing it in the most appropriate form.

[0651] A "generative AI model" is a type of artificial intelligence that learns patterns from large amounts of data and generates appropriate output based on the input, which is used to optimize information provision and analyze feedback.

[0652] "External information sources" refer not only to databases within the system, but also to additional information resources obtained from the internet or other systems.

[0653] The system for implementing this invention consists of a user terminal, a central server for processing information, and an external information source. The user first accesses the system through the terminal and logs into an account for skill improvement. The terminal utilizes React Native to achieve cross-platform compatibility, enabling smooth operation on smartphones and tablets.

[0654] The terminal sends user experience information, specifically past work history and evaluation data, to the server. Based on this information, the server generates appropriate search queries. These queries utilize Google Firebase to search a cloud-based database and aggregate the necessary information. During this process, optimization is performed according to the user's skill level, and predetermined learning content is adjusted accordingly.

[0655] Furthermore, it utilizes a generative AI model (for example, the AI ​​model used in Hugging Face) to determine whether the information provided matches the user's needs. The data obtained as feedback is reflected in subsequent search queries, enabling continuous optimization. The server performs these calculations using the AWS platform, ensuring fast and secure information delivery.

[0656] As a concrete example, when a newly hired employee needs to acquire specialized knowledge in a particular field, this system can be used to recommend learning materials tailored to their knowledge level. For instance, a prompt to the generative AI model might be: "Please provide recommended learning content tailored to each user's current level, with the aim of improving sales skills. In particular, please include content that will help strengthen negotiation techniques."

[0657] Therefore, this invention is designed to enable users to quickly and efficiently acquire content, dramatically improving learning effectiveness by providing information perfectly matched to each user's knowledge level.

[0658] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0659] Step 1:

[0660] The terminal provides an interface for users to log in to the system. It receives the user's ID and password as input and sends them to the authentication server. The server compares the authentication information with the database to verify that the user is legitimate. Once authentication is complete, it retrieves the user's past experience information from the database and sends it to the terminal.

[0661] Step 2:

[0662] The server generates appropriate search queries based on the user's experience information. This process uses data mining techniques to derive search criteria that match the user's knowledge level and areas of interest. The output is a search query optimized for the user.

[0663] Step 3:

[0664] The server uses the generated search query to explore relevant data sets. Here, it filters the information on Google Firebase and selects relevant learning content. The search query is used as input, and the filtered information is obtained as output.

[0665] Step 4:

[0666] The server customizes the acquired information according to the user's skill level. It utilizes a generative AI model to analyze the user's learning history and feedback, adjusting the display format and content of the information. This ensures that information is provided in a way that is easy for the user to understand.

[0667] Step 5:

[0668] The terminal provides customized information to the user. This information is displayed in text, visual, or video format. Input is customized information from the server, and output is the content displayed on the user's screen.

[0669] Step 6:

[0670] Users learn from the information provided and send feedback through their devices. This feedback includes their assessment of their understanding and the relevance of the content.

[0671] Step 7:

[0672] The device sends user feedback to the server. The server analyzes this information and further optimizes the next information delivery through a generative AI model. In this way, the system can continuously improve its learning efficiency.

[0673] 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.

[0674] The system of the present invention not only provides customized information based on the user's knowledge and skills, but also enables more adaptive information delivery that takes into account the user's emotions. It comprises an advanced system based on the interaction between the server, terminal, and user.

[0675] When a user accesses the system through a terminal and requests specific information, the terminal incorporates sensors that recognize the user's experience information and emotional state. The emotional state is determined by an emotion engine based on the user's facial expressions, tone of voice, input patterns, and other factors.

[0676] The device combines the user's acquired experience information and emotional state data and sends it to the server. The server uses this information to generate search queries optimized for the user and explore relevant internal databases and external resources. Depending on the emotional state, for example, if the user is stressed, the information can be simplified or content with a relaxing effect can be prioritized.

[0677] The collected information is customized to be most effectively communicated based on the user's current emotional state. When relaxed, a detailed, technical explanation is provided, while when emotionally unstable, concise and easy-to-understand content is offered. The device presents the customized information to the user, delivering it in a format that is easily accepted by the user.

[0678] Users provide feedback through their devices on how they receive and use information. This feedback, along with the user's emotional state supplemented by an emotion engine, is sent to the server and used to improve the information delivery process in the future. Thus, the present invention is a system that takes into account the individual emotional state of each user, enabling more personalized information delivery.

[0679] For example, if a user is feeling stressed while trying to learn new technical information, this system recognizes that emotion and provides the information in a less burdensome, visually easy-to-understand format. This allows the user to reduce stress while increasing learning efficiency.

[0680] The following describes the processing flow.

[0681] Step 1:

[0682] The user logs into the system via a terminal. The terminal uses sensors to analyze the user's facial expressions and voice tone, and uses an emotion engine to recognize their emotional state. The terminal then sends the emotional state and experience information to the server.

[0683] Step 2:

[0684] Based on the received experience information, the server generates search queries appropriate to the user's skill level. Depending on the emotional state, it adjusts the queries and selects keywords to search for information best suited to the user's current mental state.

[0685] Step 3:

[0686] The server searches relevant databases and external information resources based on the generated query. The sentiment engine selects content considering the user's emotions and collects high-priority information.

[0687] Step 4:

[0688] The server customizes the collected information and organizes it in a format best suited to the user's emotional state. The information is adjusted according to the user's needs, ranging from detailed technical data to simplified versions with extensive use of visual aids.

[0689] Step 5:

[0690] The device provides the user with customized information received from the server. It presents the information in the most easily understandable format, tailored to the user's emotional state, ensuring they receive the information without experiencing stress.

[0691] Step 6:

[0692] The user reviews the displayed information and provides feedback on their emotional response and level of understanding via the device. The device then sends this feedback to the server.

[0693] Step 7:

[0694] The server analyzes the feedback and uses an emotion engine to improve the information delivery mechanism. This feedback loop allows the system to provide even more personalized information in the future.

[0695] (Example 2)

[0696] 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".

[0697] While existing information delivery systems can provide information based on the user's experience and knowledge level, they fail to consider the user's emotional state. This can lead to user stress and affect the ease with which information is received. This invention proposes a system that appropriately grasps the user's emotional state and provides information accordingly quickly and effectively.

[0698] 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.

[0699] In this invention, the server includes means for acquiring user experience information and emotional information, means for evaluating the user's emotional state based on the information, and means for generating an optimal search query based on the evaluation. This makes it possible to provide information tailored to the user's emotional state.

[0700] "User experience information" refers to information about the knowledge and skills that a user has acquired to date.

[0701] "Emotional information" refers to information that indicates the user's current mental state, and includes data obtained from facial expressions, tone of voice, input patterns, etc.

[0702] "Assessing emotional state" means analyzing acquired emotional information to determine what emotions the user is experiencing.

[0703] "Generating search queries" means creating search criteria to retrieve the most relevant information based on the user's experience and emotional state.

[0704] "External and internal information sources" refer to all information storage locations that the server can access to retrieve information, including databases on the internet and internal company databases.

[0705] "Adjusting and customizing" is the process of transforming explored information into a format appropriate to the user's specific needs and emotional state.

[0706] "To present" means to ultimately display information obtained from the server to the user.

[0707] This invention is an information provision system that customizes information according to the user's emotional state. The system includes a terminal, a server, and sensors for collecting emotional information.

[0708] Users access the system via a terminal. The terminal incorporates cameras and microphones to recognize the user's facial expressions, voice tone, and input patterns. Using the data collected from these sensors, the system acquires the user's emotional information and uses an emotion engine to determine their emotional state. The emotion engine is based on a generative AI model and performs real-time emotional evaluation.

[0709] User sentiment and experience information transmitted from the device is received by the server. Based on this information, the server creates the optimal search query. The search query is used to explore relevant information through access to external and internal information sources. The server adjusts and customizes the data obtained from the search according to the user's sentiment state and converts it into a format that can be presented to the user.

[0710] For example, if a user is trying to learn technical content but their emotion sensor detects that they are experiencing stress, the server will convert the learning content into an easily understandable infographic or video format and provide it to them.

[0711] An example of a prompt message generated in this case would be: "The user is trying to search for technical information but is feeling stressed. Please suggest ways to present the information visually in a simplified manner so that he can understand it in a relaxed state."

[0712] This system allows users to receive information in a way that suits their emotional state, resulting in more efficient and effective information acquisition.

[0713] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0714] Step 1:

[0715] The user activates the device and accesses the information provision system. Input includes the user's basic information and the purpose or keywords they are searching for. The device uses emotion sensors such as a camera and microphone to collect the user's facial expressions and voice tone in real time. This allows the user's emotional information to be obtained. The output is a set of the user's emotional information and experience information.

[0716] Step 2:

[0717] The device sends acquired emotional and experiential information to the server. The input is the data collected in step 1. The server receives this data and uses an emotion engine to evaluate the user's emotional state. A generative AI model analyzes the emotional information to output a detailed emotional status. As a result, the evaluation of the emotional state and the priority of information to be presented to the user are determined.

[0718] Step 3:

[0719] The server generates the optimal search query based on the user's emotional state and the requested information. The input consists of the emotional state assessment and the search keywords received from the user. The generative AI model creates an appropriate search query and explores both external and internal information sources. The output is a list of highly relevant information.

[0720] Step 4:

[0721] The server adjusts and customizes information obtained from external and internal sources based on the user's emotional state. The input is the list of information obtained in step 3. The server adjusts the visual elements and language difficulty and converts the information into a format suitable for the user's state. The output is the customized set of information.

[0722] Step 5:

[0723] The terminal presents the user with customized information received from the server. The input is the customized information set generated in step 4. The terminal displays or delivers the information via audio in a format easily understood by the user, using its screen or audio device. The output is the information presented to the user.

[0724] Step 6:

[0725] Users review the information provided and offer feedback on how they received it and its effects. Input consists of the user's comments and evaluations. The device collects this data and sends it to the server. Output is feedback data used to improve future data collection and information presentation.

[0726] (Application Example 2)

[0727] 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".

[0728] When users acquire information, especially when they require information customized according to their emotional state, conventional systems struggle to provide information that adequately considers the user's emotional state. As a result, users have difficulty properly understanding and utilizing the information they receive, leading to a decrease in information utilization efficiency. Furthermore, the lack of emotionally responsive content prevents the system from maximizing the user experience.

[0729] 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.

[0730] In this invention, the server includes means for generating appropriate search queries based on the user's experience information and emotional state, means for searching relevant databases and external knowledge, and means for recognizing and determining the user's emotions. This makes it possible to provide content optimized based on the emotional state.

[0731] "User experience information" refers to information about the knowledge and skills that users have acquired to date, and is used to optimize information provision services.

[0732] "Emotional state" refers to the user's psychological state and is determined from factors such as facial expressions, tone of voice, and input patterns.

[0733] A "search query" is a command generated to find specific information, and it is created based on the user's experience and emotional state.

[0734] A "related database" is a collection of data where the information to be provided is stored, and it is searched based on search queries.

[0735] "External knowledge" refers to knowledge obtained from information sources outside of the system's database, and is used to improve the quality of information provided.

[0736] "Content" refers to the information and entertainment provided to users, and is selected with consideration for the user's emotional state.

[0737] "Emotion recognition functionality" is a technology that analyzes a user's facial expressions and voice to determine their emotional state, and is used to optimize information delivery.

[0738] "Feedback" refers to users' reactions and evaluations of the information and services provided, and is used to improve future services.

[0739] This invention relates to a system that optimizes information delivery by utilizing user experience information and emotional states.

[0740] This system primarily consists of interactions between a server, a terminal, and the user. The terminal is equipped with sensors to detect the user's facial expressions, voice tone, and input patterns. This activates an emotion recognition function that determines the user's emotional state. The terminal is responsible for collecting this data and transmitting it to the server.

[0741] The server generates an optimal search query based on the user's received experience information and emotional state. This search query is used to explore relevant databases and external knowledge. The server integrates this information, selects content that matches the user's current emotional state, and presents customized information to the user through the device.

[0742] For example, when a user is feeling tired from work, the system can recommend relaxing music. Similarly, when a user is feeling active, it can provide new recipes or educational videos.

[0743] This system also collects user feedback to help improve future information delivery. The feedback is sent to the server and analyzed to improve the effectiveness of information delivery and help provide a more personalized experience.

[0744] (Example of a prompt message)

[0745] An example of a prompt might be, "Analyze the user's face and voice, and generate optimal relaxation content tailored to their emotional state." Through such prompts, the system utilizes a generative AI model to provide content optimized for the user.

[0746] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0747] Step 1:

[0748] The device uses sensors to acquire data on the user's facial expressions and voice tone. This data is input into the emotion recognition function and used as basic information to determine the user's emotional state. By analyzing changes in facial expressions and pitch, the emotion engine outputs specific emotional states such as "tired" or "energetic."

[0749] Step 2:

[0750] The terminal sends acquired user experience information and emotional state data to the server. The server receives this information as input and processes the data to generate appropriate search queries. Here, data calculations are performed to determine which information the system should prioritize based on information about the user's skills and emotional state. The generated queries become commands for information retrieval.

[0751] Step 3:

[0752] The server uses the generated search query to explore relevant databases and external knowledge sources. It filters the information within the database and selects information that matches the user's emotional state. For example, for a user who needs to relax, it selects upbeat music or visually pleasing images as output. On the other hand, users who are highly motivated to learn are presented with learning videos and technical materials.

[0753] Step 4:

[0754] The device receives customized information from the server and presents it in an appropriate format according to the user's emotional state. Here, data processing is performed to display the selected content in an easy-to-understand manner for the user. For example, a summary is displayed for text, and a preview is displayed for video, ensuring that the user can effectively receive the information.

[0755] Step 5:

[0756] Users receive the provided information and send feedback to the system via their device. This feedback is used to improve the information provision process in the future. The feedback data is aggregated on the server and processed to serve as a reference when reviewing the criteria for selecting the information provided. This process further personalizes the user experience and improves the accuracy of the information provided.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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."

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0778] The following is further disclosed regarding the embodiments described above.

[0779] (Claim 1)

[0780] Means for obtaining user experience information,

[0781] A means for generating an appropriate search query based on the user's experience information,

[0782] A means for searching related databases using the aforementioned search query,

[0783] Means for customizing the search results according to the user's experience information,

[0784] Means of providing customized information to users,

[0785] A system that includes this.

[0786] (Claim 2)

[0787] Means of obtaining user feedback,

[0788] A means of analyzing the acquired feedback and improving performance,

[0789] The system according to claim 1, comprising:

[0790] (Claim 3)

[0791] The system according to claim 1, further comprising means for searching for external resources based on the generated search query.

[0792] "Example 1"

[0793] (Claim 1)

[0794] Means for acquiring user skill information,

[0795] Means for generating appropriate information retrieval commands based on the user's skill information,

[0796] Means for searching for internal and external information resources using the aforementioned information retrieval command,

[0797] Means for adjusting the search results according to the user's skill information,

[0798] A means of providing users with adjusted information,

[0799] A means of collecting and analyzing user feedback to improve information provision,

[0800] A system that includes this.

[0801] (Claim 2)

[0802] The system according to claim 1, comprising means for providing a customized learning experience according to the user's technical level.

[0803] (Claim 3)

[0804] The system according to claim 1, comprising means for visualizing and presenting information in a format suitable for the user based on the generated information retrieval command.

[0805] "Application Example 1"

[0806] (Claim 1)

[0807] Means for obtaining user experience information,

[0808] A means for generating an appropriate search query based on the user's experience information,

[0809] A means for searching for related data sets using the aforementioned search query,

[0810] Means for customizing the search results according to the user's experience information,

[0811] Means of providing customized information to users,

[0812] A means of optimizing predetermined learning content according to the user's skill level,

[0813] A system that includes this.

[0814] (Claim 2)

[0815] Means of obtaining user feedback,

[0816] A means to improve the overall system performance by analyzing the acquired feedback, optimizing the information using a generative AI model, and

[0817] The system according to claim 1, comprising:

[0818] (Claim 3)

[0819] The system according to claim 1, further comprising means for searching for external information sources based on the generated search query and integrating the obtained information.

[0820] "Example 2 of combining an emotion engine"

[0821] (Claim 1)

[0822] Means for acquiring user experience information and emotional information,

[0823] A means for evaluating the user's emotional state based on the aforementioned information,

[0824] A means for generating an optimal search query based on the aforementioned evaluation,

[0825] A means for searching for external and internal information sources using the aforementioned search query,

[0826] A means for adjusting and customizing the retrieved information according to the user's emotional state,

[0827] A means of presenting customized information to the user,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, comprising means for receiving user feedback and analyzing that feedback and emotional state to improve the information provision process.

[0831] (Claim 3)

[0832] The system according to claim 1, comprising means for dynamically switching the format in which information obtained based on the user's emotional state is presented, thereby enabling simplification and visualization of the information.

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

[0834] (Claim 1)

[0835] Means for obtaining user experience information,

[0836] means for generating an appropriate search query based on the user's experience information and emotional state,

[0837] A means for searching related databases and external knowledge using the aforementioned search query,

[0838] A means of providing content adapted to the user's emotional state based on the search results,

[0839] A means equipped with an emotion recognition function for determining the user's emotions,

[0840] Means of providing customized information to users,

[0841] An information provision system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, comprising means for obtaining user feedback and improving performance based on the obtained feedback.

[0844] (Claim 3)

[0845] The system according to claim 1, comprising means for providing content that has a relaxation effect in accordance with the user's emotions. [Explanation of Symbols]

[0846] 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 obtaining user experience information, A means for generating an appropriate search query based on the user's experience information, A means for searching for related data sets using the aforementioned search query, Means for customizing the search results according to the user's experience information, Means of providing customized information to users, A means of optimizing predetermined learning content according to the user's skill level, A system that includes this.

2. Means of obtaining user feedback, A means to improve the overall system performance by analyzing the acquired feedback, optimizing the information using a generative AI model, and The system according to claim 1, comprising:

3. The system according to claim 1, further comprising means for searching for external information sources based on the generated search query and integrating the obtained information.

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