system

Abstract

We provide the system. [Solution] Means for collecting user characteristics information, Methods for retrieving information from multiple databases, A means of analyzing collected information and suggesting products that suit the user's situation, A means of presenting the proposed product to an information processing device, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, in response to diversified lifestyles and needs, it has been required to provide optimal services for individual users. However, it is difficult and time-consuming for users themselves to find the necessary services from a vast amount of information. Therefore, there is a need for a system that can quickly propose highly relevant services based on users' lifestages and profile information.

Means for Solving the Problems

[0005] This invention provides a system that includes means for collecting user profile information and means for obtaining information from affiliated databases, and further includes means for analyzing the collected information to propose services that match the user's life stage. This system efficiently proposes the most suitable services to the user by summarizing the latest trend information using generative artificial intelligence and correlating information obtained from multiple databases.

[0006] "User profile information" refers to data that represents basic attributes and behavioral history of a user.

[0007] "Means" refers to the methods or devices used to achieve a specific purpose.

[0008] A "partnership database" refers to a collection of information shared by multiple companies and service providers.

[0009] "Acquiring information" refers to the act of gathering necessary data from databases or other sources.

[0010] "Analyzing collected information" is the process of evaluating the obtained data and extracting its meaning and value.

[0011] "Life stage" is a concept that indicates what stage in a user's life they are currently in.

[0012] "Proposing a service" means presenting users with options that have the potential to provide convenience or value.

[0013] "User terminal" refers to an electronic device used by a user to receive services.

[0014] "Generative artificial intelligence" refers to AI technology that can generate and interpret data such as text and language.

[0015] "Trend information" refers to data on topics and themes that have gathered popularity and interest in recent years.

[0016] "Associating with each other" means linking two or more pieces of information to form a coherent and meaningful form.

Brief Explanation of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Embodiment for Implementing the Invention

[0018] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0021] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] 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."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] This invention relates to a system for proposing services optimized for users. The system mainly consists of a server and terminals, and each component plays the role described below.

[0039] The server first collects user profile information, including the user's basic attributes and past behavioral history. This information is collected by the software by accessing a database and is used to identify the user's life stage and needs.

[0040] Next, the server retrieves information from its partner database. Here, it obtains the latest service information and rankings from multiple related companies and service providers. The server further collects publicly available trend information and summarizes it using generative artificial intelligence technology. This summarization process ensures that vast amounts of data are presented to users in an important and easily understandable format.

[0041] The server then integrates and analyzes all the collected information. This analysis generates a list of services that match the user's life stage. Specifically, the server uses the collected information to automatically select services that the user is likely to need at the moment.

[0042] This selected information is presented to the user through the device. The device receives the information and provides it to the user in a user-friendly interface. For example, if a user is spending more time at home, the device can suggest home entertainment options.

[0043] As a concrete example, let's assume a user is preparing to enter university. The server reads this information from the user's profile and retrieves information on student scholarships and financial support from affiliated databases. Furthermore, it uses artificial intelligence to generate and provide information on popular learning programs and events based on social trends. Finally, the device integrates all of this information to help the user intuitively make the necessary choices.

[0044] Thus, the present invention is implemented in a form that enables a highly accurate and rapid response to the needs of users.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The server collects user profile information. The software retrieves basic user attributes and past behavioral history from the database and uses this information to analyze the user's life stage and needs.

[0048] Step 2:

[0049] The server accesses the partner database to retrieve information. The server collects the latest service information and rankings from related companies and service providers, and filters the information to be most relevant based on the user's profile.

[0050] Step 3:

[0051] The server collects trend information from external sources and summarizes it using generative artificial intelligence. This prepares the information to be delivered to users in an important and easy-to-understand format.

[0052] Step 4:

[0053] The server integrates and analyzes all the collected information. Using data processing algorithms, it automatically extracts and suggests services suitable for the user, creating a list of recommendations.

[0054] Step 5:

[0055] The terminal receives information from the server and presents it to the user through a user interface. The terminal displays the information in a visually clear and interactive format, supporting users in easily making selections and evaluations.

[0056] (Example 1)

[0057] 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."

[0058] Conventional systems have struggled to quickly and accurately propose the most suitable services to users. This problem stems from insufficient data collection and analysis, as well as an inability to flexibly respond to users' changing needs. Furthermore, the correlation of collected information is often inadequate, resulting in a lack of service recommendations that are truly beneficial to users.

[0059] 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.

[0060] In this invention, the server includes means for collecting user attribute information, means for obtaining information from relevant information sources, and means for analyzing the collected data and recommending services that correspond to the user's status. This makes it possible to propose services that respond quickly and accurately to the diverse needs of users.

[0061] "User attribute information" refers to data that includes the user's basic characteristics, behavioral history, interests, and other relevant information.

[0062] "Relevant information sources" refer to data providers that are accessible for information gathering, such as partner companies, digital platforms, and publicly available information endpoints.

[0063] "Collected data" refers to the collection of all information obtained from user attribute information and related information sources.

[0064] "Services tailored to the user's situation" refers to products and services that are customized to the user's current life stage and individual needs.

[0065] A "generative model" refers to an algorithm that uses natural language processing technology to summarize data and provide information in a format that is easy for humans to understand.

[0066] "Means of association" refers to processes and technologies that integrate data obtained from different sources and process it into consistent information.

[0067] This invention is an information processing system for providing services optimized for users. The system mainly consists of servers and terminals, each playing a specific role.

[0068] The server is responsible for collecting user attribute information, using database access software to obtain basic user characteristics and behavioral history. Furthermore, the server collects information through various digital platforms and APIs to obtain the latest information from relevant sources. Based on a generative model, the server summarizes the collected trend information and analyzes it to select services that correspond to the user's state.

[0069] Specific hardware and software include server equipment that enables high-speed data processing, database management software, and generative AI models that realize natural language processing.

[0070] Next, the device receives recommended services from the server and presents them to the user through an easy-to-use user interface. If the user is looking for a new movie during their activities at home, the server lists movies recommended by partnered streaming services based on the user's past viewing history and provides that information to the user through the device.

[0071] A concrete example of a prompt message would be, "Based on your recent movie viewing history, please suggest some new release movies."

[0072] Through this system, users can receive services that meet their needs quickly and accurately, thereby improving their quality of life.

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

[0074] Step 1:

[0075] The server collects user attribute information. As input, it obtains basic characteristics and past behavioral history provided by the user. This information is collected using database access software, and the server uses it for analysis. Specifically, the server analyzes cookie information and log data to identify the user's interests and preferences. As output, user profile data is generated.

[0076] Step 2:

[0077] The server retrieves information from relevant sources. As input, it obtains the latest service information and trend data through affiliated digital platforms and relevant APIs. The server analyzes this information and organizes the relationships between pieces of data as needed. Specifically, the server sends requests to service providers' APIs and stores the obtained data in its internal database. The output is an updated list of information.

[0078] Step 3:

[0079] The server summarizes and analyzes the collected information using a generative AI model. The input for this step is user profile data and updated information obtained from relevant sources. Using prompts, the generative AI model performs the summarization process and refines the information. Specifically, the server prompts the AI ​​model, and the resulting summary is further refined using an internal algorithm. The output is a customized service recommendation list for each user.

[0080] Step 4:

[0081] The terminal displays a list of recommended services sent from the server. The input is recommendation information from the server, which is presented to the user in an easy-to-understand format via the interface. Specifically, the terminal displays a notification on the user's screen, and a function is built that allows the user to view detailed information with the press of a button. As output, the information is presented in a format that is easy for the user to consider, enabling the user to make informed decisions.

[0082] (Application Example 1)

[0083] 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."

[0084] In today's information-saturated world, it is difficult for users to find the products and services that are best suited to them. A system is needed to solve this problem and provide product suggestions that match the user's needs and life stage.

[0085] 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.

[0086] In this invention, the server includes means for collecting user characteristic information, means for obtaining information from multiple databases, and means for analyzing the collected information and suggesting products that suit the user's situation. This enables the rapid suggestion of products and services optimized for the user.

[0087] "User characteristic information" refers to information that shows a user's basic attributes and past behavioral history, and is data used to suggest products and services.

[0088] A "multiple database" refers to a set of multiple sources of information used to aggregate information from related companies and service providers.

[0089] "A means of analyzing collected information and suggesting products that suit the user's situation" refers to a system that integrates user profiles with external information to select products optimized for individual users.

[0090] An "information processing device" is a terminal device that displays suggested information from a server to the user in an intuitive manner.

[0091] "Generative artificial intelligence" is an artificial intelligence technology used to summarize collected trend information and present it in a format that is easy for users to understand.

[0092] "Means of correlating information obtained from different sources" refers to processing methods for effectively integrating information obtained from multiple databases to generate meaningful suggestions.

[0093] This invention realizes a system for proposing products and services optimized for the user. The system consists of a server and an information processing terminal.

[0094] The server first collects user characteristic information. It retrieves the user's basic attributes and past behavioral history from a database to form a user profile. This process utilizes a database management system (e.g., MySQL®).

[0095] Next, the server retrieves information from multiple external databases. This information includes the latest updates from related companies and service providers, and is collected using a variety of APIs.

[0096] The server uses the collected data to perform data analysis, utilizing generative artificial intelligence technologies, such as machine learning frameworks (e.g., TENSORFLOW®). This allows it to build a recommendation model that selects products tailored to the user's situation.

[0097] The generated proposals are sent to an information processing terminal. The terminal presents them to the user, displaying them in a user-friendly interface. The smartphone application is developed with React Native, providing the user with an intuitive operating experience.

[0098] For example, if a user is interested in sports equipment, the server will suggest appropriate running shoes and related fitness equipment based on their past purchase history and market trends.

[0099] As an example of a prompt statement, the following request is input to the generating AI model.

[0100] "Considering current trends, please suggest products that a male user in his 30s might be interested in. He has a past purchase history of running-related items."

[0101] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0102] Step 1:

[0103] The server collects user characteristic information. It retrieves the user's basic attributes and past behavioral history from the database to form profile data. The input data is the user ID, and the output data is a user profile object. In this step, an SQL query is executed for data collection.

[0104] Step 2:

[0105] The server retrieves information from multiple databases and gathers external information relevant to the user's interests. This includes product information and trend data from related companies. The input data is the API access key, and the output data is a list of the retrieved information. Necessary information is collected through API requests.

[0106] Step 3:

[0107] The server uses generative artificial intelligence to analyze information and suggest products suitable for the user's situation. It analyzes user profiles and external information and generates a suggestion list using a specific algorithm. Input data consists of profile objects and information lists, while output data is a list of suggested products. Machine learning models such as TensorFlow are used for recommendation processing.

[0108] Step 4:

[0109] The server sends the generated suggestions to the information processing terminal. Based on the suggestion list, it sends the most suitable product information to the terminal. The input data is the suggestion list, and the output data is the product information sent to the user terminal. Data transmission is performed using a network protocol.

[0110] Step 5:

[0111] The terminal presents received suggestions to the user. Product information is displayed on an intuitive user interface, allowing the user to easily browse and select items. Input data is the submitted product information, and output data is the content displayed on the user interface. The UI design is done using React Native.

[0112] Step 6:

[0113] Users browse products displayed on their device and make purchase decisions. Products selected by the user proceed to the purchase process. Input data represents the user's selection, while output data indicates the start of the purchase and delivery procedures. Selection and purchase operations are performed through the user interface.

[0114] 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.

[0115] This invention relates to a system characterized by recognizing user emotions and reflecting them in profiles and service recommendations. This system mainly consists of a server, a terminal, and an emotion engine.

[0116] The server first collects user profile information. This involves retrieving basic user attributes and past behavioral history from a database to identify the user's life stage and needs. Next, the server retrieves relevant information from partner databases. This includes the latest service information, rankings, and relevant data based on the user's interests.

[0117] The emotion engine analyzes user input and behavioral data to recognize the user's emotional state. For example, it analyzes the user's facial expressions and operation patterns on the input interface to identify the user's current emotions. This emotional information is reflected in the service suggestions provided by the server in real time, presenting the optimal choice based on the user's emotional state.

[0118] Trend information is also a crucial element; the server collects this information from external sources and summarizes it using generative artificial intelligence. This provides users with useful and easy-to-understand information. The results of this information collection and analysis are integrated to generate a list of personalized suggestions for the user.

[0119] When users receive suggestions through their devices, the devices display the information clearly through their user interface. For example, if a user is feeling stressed, the device will highlight and display relaxation-related services. Furthermore, the suggestions are dynamically updated in response to the user's emotional changes, providing the optimal experience.

[0120] For example, when a user is feeling stressed at work, the emotion engine detects this state, and the server suggests music streaming services or discount information on recreational spots that can help the user relax. The device then presents these options in an intuitive way, contributing to reducing the user's stress.

[0121] Thus, the present invention is implemented in a form that realizes a highly personalized experience by reflecting the user's emotions in real time.

[0122] The following describes the processing flow.

[0123] Step 1:

[0124] The server collects user profile information. The server accesses the database to retrieve the user's basic attributes and past behavioral history. This generates foundational data for analyzing individual life stages and needs.

[0125] Step 2:

[0126] The device acquires real-time input data from the user. This includes user actions on the interface and biometric data from wearable devices. This data is used as material for emotion recognition.

[0127] Step 3:

[0128] The emotion engine analyzes user input data and detects emotional states. Using algorithms, the emotion engine analyzes user operation patterns and biometric data to identify emotions such as stress and joy.

[0129] Step 4:

[0130] The server retrieves information from partner databases. Here, service information and trend data from multiple sources are reused to narrow down the content that is most relevant to the user.

[0131] Step 5:

[0132] The server integrates and analyzes emotional information and acquired data. By considering the emotional state and linking user profile information with service data, it creates service suggestions that are tailored to the user's feelings.

[0133] Step 6:

[0134] The device displays personalized service suggestions to the user. The device reflects the user's emotional state and provides information in a suitable format. For example, if the user is seeking relaxation, relaxation-related services will be highlighted.

[0135] Step 7:

[0136] The user selects a service from the options presented. The user reviews the information provided via their device and chooses a service that suits their emotional state.

[0137] Step 8:

[0138] The server records the user's selections, forming a feedback loop. Based on the selected information, profile information is further updated to improve the accuracy of future service recommendations.

[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 as the "terminal".

[0141] Traditional systems often offered uniform service suggestions without considering the user's emotional state, making it difficult to provide appropriate suggestions tailored to each user's situation. Therefore, there is a need to provide users with more personalized experiences and information that is appropriate to their life stage and emotional state.

[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 a device means for collecting users' personal information, a device means for acquiring data from an external storage area, and a device means for analyzing the acquired data and proposing tasks appropriate to the user's life stage. This makes it possible to reflect the user's emotional state in real time and provide services and information optimized for each individual user.

[0144] A "device for collecting users' personal information" refers to equipment or software that acquires information such as a user's basic attributes, interests, and past behavioral history, and stores it in a database.

[0145] A "device for acquiring data from external storage" is a device that acquires necessary data from external information sources such as the internet or affiliated databases and makes it available for use within the system.

[0146] A "device that analyzes acquired data and proposes tasks appropriate to the user's stage of life" is a device that analyzes collected data and selects and presents the most suitable tasks and services according to the user's current situation.

[0147] A "device that analyzes user input and behavior patterns to identify emotional states" is a device that recognizes emotions from a user's actions and inputs and identifies their current mental state.

[0148] A "device that adjusts suggested services based on emotional information" is a device that selects appropriate services and information based on the user's emotional state and optimizes the content presented.

[0149] A "device that uses machine learning algorithms to summarize the latest trend information" is a device that uses technology to analyze diverse datasets and generate integrated information on current trends and developments.

[0150] A "device that correlates data acquired from diverse memory areas" is a device that correlates data collected from different sources, analyzes it comprehensively, and extracts valuable information.

[0151] This system consists of three main elements: a server, a terminal, and an emotion engine. The method for carrying out the invention is as follows:

[0152] The server first collects the user's personal information. This is done via database access, retrieving the user's basic attributes (age, gender, interests, etc.) and past behavioral history from the data store. This information is used to determine the user's stage in life and suggest the most suitable services.

[0153] Next, the server retrieves information from external storage, such as cloud-based data services. This information includes the latest market trends, popular service rankings, and data tailored to user interests. The collected information is then analyzed using generative AI models to generate meaningful insights.

[0154] The terminal plays the role of transmitting user input information and operation patterns to the emotion engine. This allows the emotion engine to identify the user's emotional state in real time and provide information and service suggestions based on that emotion. For example, if a user is feeling stressed, the engine will detect that emotion, and the server will suggest a music service for relaxation. An example of a prompt in this case would be, "Please suggest services to recommend when the user is feeling stressed at work."

[0155] Furthermore, the device receives suggestions from the server and displays information intuitively through the user interface. In doing so, it visually highlights information that the user is likely to be interested in, making it easier to select. This allows users to easily choose services on the spot and gain options to improve their quality of life.

[0156] This invention aims to dynamically adjust information according to the individual needs of users and provide an emotionally personalized experience.

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

[0158] Step 1:

[0159] The server collects users' personal information using database access methods. Inputs include user ID and past behavioral patterns. Based on this data, the server retrieves profile information such as age, gender, and interests from the database. The output is detailed profile information to determine the user's life stage. This information is used in the next proposed step.

[0160] Step 2:

[0161] The server retrieves the latest service information and trend data from external storage. Inputs include access information to relevant APIs and cloud services. The server analyzes this data using a generative AI model to generate meaningful service rankings and trend information. The output provides foundational information for creating personalized recommendations. Specifically, it extracts the most relevant information for the user from past usage history and newly acquired trends.

[0162] Step 3:

[0163] The device sends user input and operation patterns to the emotion engine. Input includes user typing and click patterns, as well as facial recognition data indicating emotions. The emotion engine analyzes this data to identify the current emotional state. The output provides information based on the emotional state. For example, it might generate emotion data indicating "the user is feeling stressed."

[0164] Step 4:

[0165] The server integrates acquired emotional and profile information to generate service suggestions optimized for individual needs. Inputs include emotional data and profile data. Based on this, the server makes suggestions that include relaxation music and access information to specific services. The output generates a list of personalized services for each user.

[0166] Step 5:

[0167] The terminal displays the generated service suggestions on the user interface. The input is suggestion information sent from the server. Based on this, the terminal visually highlights the information in a way that allows the user to intuitively select. The output is a list of services presented as options. Specifically, a link to a music streaming service for stress relief is displayed in an active state.

[0168] (Application Example 2)

[0169] 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".

[0170] The problem that this invention aims to solve is to enrich the way people spend time at home by providing optimal services based on their emotions. Conventional systems have found it difficult to accurately grasp the emotional state of users and propose the most suitable service at that moment.

[0171] 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.

[0172] In this invention, the server includes means for analyzing and identifying the user's emotional state, means for collecting user profile information, and means for obtaining information from a partner database. This makes it possible to provide personalized services that respond to the user's real-time emotional state.

[0173] "Means for analyzing and identifying the user's emotional state" refers to a function that uses emotion analysis technology to identify the user's current emotional state based on data such as their speech and facial expressions.

[0174] "Means for collecting user profile information" refers to a function that retrieves profile data, including users' personal information and past behavioral history, from a database and collects information related to the individual.

[0175] "Means of obtaining information from partner databases" refers to functions that link with external databases to obtain information and service data related to the user's interests.

[0176] "A means of analyzing collected information and proposing services appropriate to the user's stage of life" refers to a function that analyzes collected user data and, based on the results, proposes services that match the user's stage of life and needs.

[0177] "Means of providing the proposed service to the user's device" refers to a function that appropriately displays the proposed service information on the user's device and makes it easily accessible to the user.

[0178] "A means of summarizing the latest trend information using generative artificial intelligence" refers to a function that utilizes artificial intelligence technology to analyze the latest information collected from external sources and summarize it in a way that is easy for users to understand.

[0179] "Means of linking data obtained from multiple information sources" refers to a function that combines data collected from different databases, integrates the information by creating meaningful relationships between them.

[0180] To implement this invention, it is necessary to build a system that analyzes the user's emotions within the home and proposes personalized services. This system consists of a user terminal, a server, and an emotion recognition engine.

[0181] The server first has a means of collecting user profile information. Specifically, it retrieves data such as the user's age, lifestyle, and past behavioral history from a database, and uses this to create an individualized profile. This profile is used to optimize the proposed services.

[0182] The emotion recognition engine uses data acquired from the camera and microphone to analyze the user's emotional state. This engine identifies the user's emotions by analyzing changes in voice tone and facial expressions. This emotional information is transmitted to the server in real time to aid in service delivery.

[0183] The server also has a means of suggesting the most relevant trend information and services to users by utilizing information obtained from partner databases. This information includes suggestions tailored to the user's situation, such as the latest entertainment and relaxation methods.

[0184] On the device, when users receive service suggestions, the information is presented in a way that is easy to understand intuitively. To this end, relaxing music is played, and appropriate video content is suggested.

[0185] For example, if a user looks tired after work, the emotion recognition engine will detect this state, and the server will recommend relaxation music. This suggestion will be displayed to the user through their device.

[0186] Generative AI models use prompts such as, "Create a program that suggests the most suitable entertainment activity for the user based on their current emotional state," as an example of a prompt used for summarizing information and generating suggestions.

[0187] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0188] Step 1:

[0189] The server retrieves user profile information from the database. The input requires a user ID, and the output includes profile data such as age, hobbies, and past service usage history. Based on this data, subsequent processing can identify services suitable for the user.

[0190] Step 2:

[0191] The emotion recognition engine receives real-time audio and video data acquired from the device's camera and microphone as input. By analyzing this data, it outputs the user's current emotional state. Specifically, it analyzes voice tone and facial expressions to identify stress levels and fatigue levels.

[0192] Step 3:

[0193] The server receives the user's emotional state output by the emotion recognition engine as input. Based on this, it retrieves relevant service information from the partner database. Through this data acquisition and analysis, it generates a service suggestion list optimized for the user as output.

[0194] Step 4:

[0195] The terminal receives service proposals sent from the server and displays them on the user interface. Input consists of specific service proposal data, and output provides intuitive information to the user through visual displays and audio guidance.

[0196] Step 5:

[0197] The user selects the most suitable service based on the suggestions displayed on the device. This selection process updates the user's preference information and, if necessary, provides prompts to the generating AI model to further optimize the service. The input is the user's selection result, and the output is the updated preference data and improvements to future service suggestions.

[0198] 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.

[0199] Data generation model 58 is a type of 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.

[0200] 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.

[0201] [Second Embodiment]

[0202] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0203] 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.

[0204] 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).

[0205] 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.

[0206] 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.

[0207] 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).

[0208] 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.

[0209] 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.

[0210] 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.

[0211] 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.

[0212] 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.

[0213] 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".

[0214] This invention relates to a system for proposing services optimized for users. The system mainly consists of a server and terminals, and each component plays the role described below.

[0215] The server first collects user profile information, including the user's basic attributes and past behavioral history. This information is collected by the software by accessing a database and is used to identify the user's life stage and needs.

[0216] Next, the server retrieves information from its partner database. Here, it obtains the latest service information and rankings from multiple related companies and service providers. The server further collects publicly available trend information and summarizes it using generative artificial intelligence technology. This summarization process ensures that vast amounts of data are presented to users in an important and easily understandable format.

[0217] The server then integrates and analyzes all the collected information. This analysis generates a list of services that match the user's life stage. Specifically, the server uses the collected information to automatically select services that the user is likely to need at the moment.

[0218] This selected information is presented to the user through the device. The device receives the information and provides it to the user in a user-friendly interface. For example, if a user is spending more time at home, the device can suggest home entertainment options.

[0219] As a concrete example, let's assume a user is preparing to enter university. The server reads this information from the user's profile and retrieves information on student scholarships and financial support from affiliated databases. Furthermore, it uses artificial intelligence to generate and provide information on popular learning programs and events based on social trends. Finally, the device integrates all of this information to help the user intuitively make the necessary choices.

[0220] Thus, the present invention is implemented in a form that enables a highly accurate and rapid response to the needs of users.

[0221] The following describes the processing flow.

[0222] Step 1:

[0223] The server collects user profile information. The software retrieves basic user attributes and past behavioral history from the database and uses this information to analyze the user's life stage and needs.

[0224] Step 2:

[0225] The server accesses the partner database to retrieve information. The server collects the latest service information and rankings from related companies and service providers, and filters the information to be most relevant based on the user's profile.

[0226] Step 3:

[0227] The server collects trend information from external sources and summarizes it using generative artificial intelligence. This prepares the information to be delivered to users in an important and easy-to-understand format.

[0228] Step 4:

[0229] The server integrates and analyzes all the collected information. Using data processing algorithms, it automatically extracts and suggests services suitable for the user, creating a list of recommendations.

[0230] Step 5:

[0231] The terminal receives information from the server and presents it to the user through a user interface. The terminal displays the information in a visually clear and interactive format, supporting users in easily making selections and evaluations.

[0232] (Example 1)

[0233] 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."

[0234] Conventional systems have struggled to quickly and accurately propose the most suitable services to users. This problem stems from insufficient data collection and analysis, as well as an inability to flexibly respond to users' changing needs. Furthermore, the correlation of collected information is often inadequate, resulting in a lack of service recommendations that are truly beneficial to users.

[0235] 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.

[0236] In this invention, the server includes means for collecting user attribute information, means for obtaining information from relevant information sources, and means for analyzing the collected data and recommending services that correspond to the user's status. This makes it possible to propose services that respond quickly and accurately to the diverse needs of users.

[0237] "User attribute information" refers to data that includes the user's basic characteristics, behavioral history, interests, and other relevant information.

[0238] "Relevant information sources" refer to data providers that are accessible for information gathering, such as partner companies, digital platforms, and publicly available information endpoints.

[0239] "Collected data" refers to the collection of all information obtained from user attribute information and related information sources.

[0240] "Services tailored to the user's situation" refers to products and services that are customized to the user's current life stage and individual needs.

[0241] A "generative model" refers to an algorithm that uses natural language processing technology to summarize data and provide information in a format that is easy for humans to understand.

[0242] "Means of association" refers to processes and technologies that integrate data obtained from different sources and process it into consistent information.

[0243] This invention is an information processing system for providing services optimized for users. The system mainly consists of servers and terminals, each playing a specific role.

[0244] The server is responsible for collecting user attribute information, using database access software to obtain basic user characteristics and behavioral history. Furthermore, the server collects information through various digital platforms and APIs to obtain the latest information from relevant sources. Based on a generative model, the server summarizes the collected trend information and analyzes it to select services that correspond to the user's state.

[0245] Specific hardware and software include server equipment that enables high-speed data processing, database management software, and generative AI models that realize natural language processing.

[0246] Next, the device receives recommended services from the server and presents them to the user through an easy-to-use user interface. If the user is looking for a new movie during their activities at home, the server lists movies recommended by partnered streaming services based on the user's past viewing history and provides that information to the user through the device.

[0247] A concrete example of a prompt message would be, "Based on your recent movie viewing history, please suggest some new release movies."

[0248] Through this system, users can receive services that meet their needs quickly and accurately, thereby improving their quality of life.

[0249] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0250] Step 1:

[0251] The server collects user attribute information. As input, it obtains basic characteristics and past behavioral history provided by the user. This information is collected using database access software, and the server uses it for analysis. Specifically, the server analyzes cookie information and log data to identify the user's interests and preferences. As output, user profile data is generated.

[0252] Step 2:

[0253] The server retrieves information from relevant sources. As input, it obtains the latest service information and trend data through affiliated digital platforms and relevant APIs. The server analyzes this information and organizes the relationships between pieces of data as needed. Specifically, the server sends requests to service providers' APIs and stores the obtained data in its internal database. The output is an updated list of information.

[0254] Step 3:

[0255] The server summarizes and analyzes the collected information using a generative AI model. The input for this step is user profile data and updated information obtained from relevant sources. Using prompts, the generative AI model performs the summarization process and refines the information. Specifically, the server prompts the AI ​​model, and the resulting summary is further refined using an internal algorithm. The output is a customized service recommendation list for each user.

[0256] Step 4:

[0257] The terminal displays a list of recommended services sent from the server. The input is recommendation information from the server, which is presented to the user in an easy-to-understand format via the interface. Specifically, the terminal displays a notification on the user's screen, and a function is built that allows the user to view detailed information with the press of a button. As output, the information is presented in a format that is easy for the user to consider, enabling the user to make informed decisions.

[0258] (Application Example 1)

[0259] 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."

[0260] In today's information-saturated world, it is difficult for users to find the products and services that are best suited to them. A system is needed to solve this problem and provide product suggestions that match the user's needs and life stage.

[0261] 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.

[0262] In this invention, the server includes means for collecting user characteristic information, means for obtaining information from multiple databases, and means for analyzing the collected information and suggesting products that suit the user's situation. This enables the rapid suggestion of products and services optimized for the user.

[0263] "User characteristic information" refers to information that shows a user's basic attributes and past behavioral history, and is data used to suggest products and services.

[0264] A "multiple database" refers to a set of multiple sources of information used to aggregate information from related companies and service providers.

[0265] "A means of analyzing collected information and suggesting products that suit the user's situation" refers to a system that integrates user profiles with external information to select products optimized for individual users.

[0266] An "information processing device" is a terminal device that displays suggested information from a server to the user in an intuitive manner.

[0267] "Generative artificial intelligence" is an artificial intelligence technology used to summarize collected trend information and present it in a format that is easy for users to understand.

[0268] "Means of correlating information obtained from different sources" refers to processing methods for effectively integrating information obtained from multiple databases to generate meaningful suggestions.

[0269] This invention realizes a system for proposing products and services optimized for the user. The system consists of a server and an information processing terminal.

[0270] The server first collects user characteristic information. It retrieves basic user attributes and past behavioral history from a database to form a user profile. A database management system (e.g., MySQL) is used in this process.

[0271] Next, the server retrieves information from multiple external databases. This information includes the latest updates from related companies and service providers, and is collected using a variety of APIs.

[0272] The server uses the collected data to perform data analysis, utilizing generative artificial intelligence technologies such as machine learning frameworks (e.g., TensorFlow). This allows it to build a recommendation model that selects products tailored to the user's situation.

[0273] The generated proposals are sent to an information processing terminal. The terminal presents them to the user, displaying them in a user-friendly interface. The smartphone application is developed with React Native, providing the user with an intuitive operating experience.

[0274] For example, if a user is interested in sports equipment, the server will suggest appropriate running shoes and related fitness equipment based on their past purchase history and market trends.

[0275] As an example of a prompt statement, the following request is input to the generating AI model.

[0276] "Considering current trends, please suggest products that a male user in his 30s might be interested in. He has a past purchase history of running-related items."

[0277] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0278] Step 1:

[0279] The server collects user characteristic information. It retrieves the user's basic attributes and past behavioral history from the database to form profile data. The input data is the user ID, and the output data is a user profile object. In this step, an SQL query is executed for data collection.

[0280] Step 2:

[0281] The server retrieves information from multiple databases and gathers external information relevant to the user's interests. This includes product information and trend data from related companies. The input data is the API access key, and the output data is a list of the retrieved information. Necessary information is collected through API requests.

[0282] Step 3:

[0283] The server analyzes information using a generative artificial intelligence and proposes products suitable for the user's situation. It analyzes the user profile and external information and generates a proposal list using a specific algorithm. The input data is a profile object and an information list, and the output data is a list of proposed products. A machine learning model such as TensorFlow is used to perform the recommendation process.

[0284] Step 4:

[0285] The server sends the generated proposals to the information processing terminal. Based on the proposal list, the optimal product information is sent to the terminal. The input data is the proposal list, and the output data is the product information sent to the user terminal. Data transmission is performed using a network protocol.

[0286] Step 5:

[0287] The terminal presents the received proposals to the user. The product information is displayed on an intuitive user interface so that the user can easily browse and select. The input data is the transmitted product information, and the output data is the display content of the user interface. UI design is performed using React Native.

[0288] Step 6:

[0289] The user browses the products presented on the terminal and makes a purchase decision. The products selected by the user's operation proceed to the purchase process. The input data is the user's selection, and the output data is the start of the purchase and delivery procedures. Selection and purchase operations are performed through the user interface.

[0290] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0291] This invention relates to a system characterized by recognizing user emotions and reflecting them in profiles and service recommendations. This system mainly consists of a server, a terminal, and an emotion engine.

[0292] The server first collects user profile information. This involves retrieving basic user attributes and past behavioral history from a database to identify the user's life stage and needs. Next, the server retrieves relevant information from partner databases. This includes the latest service information, rankings, and relevant data based on the user's interests.

[0293] The emotion engine analyzes user input and behavioral data to recognize the user's emotional state. For example, it analyzes the user's facial expressions and operation patterns on the input interface to identify the user's current emotions. This emotional information is reflected in the service suggestions provided by the server in real time, presenting the optimal choice based on the user's emotional state.

[0294] Trend information is also a crucial element; the server collects this information from external sources and summarizes it using generative artificial intelligence. This provides users with useful and easy-to-understand information. The results of this information collection and analysis are integrated to generate a list of personalized suggestions for the user.

[0295] When users receive suggestions through their devices, the devices display the information clearly through their user interface. For example, if a user is feeling stressed, the device will highlight and display relaxation-related services. Furthermore, the suggestions are dynamically updated in response to the user's emotional changes, providing the optimal experience.

[0296] For example, when a user is feeling stressed at work, the emotion engine detects this state, and the server suggests music streaming services or discount information on recreational spots that can help the user relax. The device then presents these options in an intuitive way, contributing to reducing the user's stress.

[0297] Thus, the present invention is implemented in a form that realizes a highly personalized experience by reflecting the user's emotions in real time.

[0298] The following describes the processing flow.

[0299] Step 1:

[0300] The server collects user profile information. The server accesses the database to retrieve the user's basic attributes and past behavioral history. This generates foundational data for analyzing individual life stages and needs.

[0301] Step 2:

[0302] The device acquires real-time input data from the user. This includes user actions on the interface and biometric data from wearable devices. This data is used as material for emotion recognition.

[0303] Step 3:

[0304] The emotion engine analyzes user input data and detects emotional states. Using algorithms, the emotion engine analyzes user operation patterns and biometric data to identify emotions such as stress and joy.

[0305] Step 4:

[0306] The server retrieves information from partner databases. Here, service information and trend data from multiple sources are reused to narrow down the content that is most relevant to the user.

[0307] Step 5:

[0308] The server integrates the obtained data with the emotion information and performs analysis. By associating the user profile information with the service data in consideration of the emotional state, a service proposal tailored to the user's mood is created.

[0309] Step 6:

[0310] The terminal displays a personalized service proposal to the user. The terminal reflects the user's emotional state and provides information in a suitable form. For example, when the user is seeking relaxation, relaxation-related services are emphasized.

[0311] Step 7:

[0312] The user selects the presented service. The user checks the information provided via the terminal and selects a service that suits their emotional state.

[0313] Step 8:

[0314] The server records the user's selection and forms a feedback loop. Based on the selected information, the profile information is further updated to help improve the accuracy of future service proposals.

[0315] (Example 2)

[0316] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0317] In the conventional system, a uniform service proposal is often made without considering the emotional state of the user, and it is difficult to make an appropriate proposal according to the user's situation. Therefore, it is required to provide a more personalized experience for the user and provide information suitable for their life stage and emotional state.

[0318] 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.

[0319] In this invention, the server includes a device means for collecting users' personal information, a device means for acquiring data from an external storage area, and a device means for analyzing the acquired data and proposing tasks appropriate to the user's life stage. This makes it possible to reflect the user's emotional state in real time and provide services and information optimized for each individual user.

[0320] A "device for collecting users' personal information" refers to equipment or software that acquires information such as a user's basic attributes, interests, and past behavioral history, and stores it in a database.

[0321] A "device for acquiring data from external storage" is a device that acquires necessary data from external information sources such as the internet or affiliated databases and makes it available for use within the system.

[0322] A "device that analyzes acquired data and proposes tasks appropriate to the user's stage of life" is a device that analyzes collected data and selects and presents the most suitable tasks and services according to the user's current situation.

[0323] A "device that analyzes user input and behavior patterns to identify emotional states" is a device that recognizes emotions from a user's actions and inputs and identifies their current mental state.

[0324] A "device that adjusts suggested services based on emotional information" is a device that selects appropriate services and information based on the user's emotional state and optimizes the content presented.

[0325] A "device that uses machine learning algorithms to summarize the latest trend information" is a device that uses technology to analyze diverse datasets and generate integrated information on current trends and developments.

[0326] A "device that correlates data acquired from diverse memory areas" is a device that correlates data collected from different sources, analyzes it comprehensively, and extracts valuable information.

[0327] This system consists of three main elements: a server, a terminal, and an emotion engine. The method for carrying out the invention is as follows:

[0328] The server first collects the user's personal information. This is done via database access, retrieving the user's basic attributes (age, gender, interests, etc.) and past behavioral history from the data store. This information is used to determine the user's stage in life and suggest the most suitable services.

[0329] Next, the server retrieves information from external storage, such as cloud-based data services. This information includes the latest market trends, popular service rankings, and data tailored to user interests. The collected information is then analyzed using generative AI models to generate meaningful insights.

[0330] The terminal plays the role of transmitting user input information and operation patterns to the emotion engine. This allows the emotion engine to identify the user's emotional state in real time and provide information and service suggestions based on that emotion. For example, if a user is feeling stressed, the engine will detect that emotion, and the server will suggest a music service for relaxation. An example of a prompt in this case would be, "Please suggest services to recommend when the user is feeling stressed at work."

[0331] Furthermore, the device receives suggestions from the server and displays information intuitively through the user interface. In doing so, it visually highlights information that the user is likely to be interested in, making it easier to select. This allows users to easily choose services on the spot and gain options to improve their quality of life.

[0332] This invention aims to dynamically adjust information according to the individual needs of users and provide an emotionally personalized experience.

[0333] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0334] Step 1:

[0335] The server collects users' personal information using database access methods. Inputs include user ID and past behavioral patterns. Based on this data, the server retrieves profile information such as age, gender, and interests from the database. The output is detailed profile information to determine the user's life stage. This information is used in the next proposed step.

[0336] Step 2:

[0337] The server retrieves the latest service information and trend data from external storage. Inputs include access information to relevant APIs and cloud services. The server analyzes this data using a generative AI model to generate meaningful service rankings and trend information. The output provides foundational information for creating personalized recommendations. Specifically, it extracts the most relevant information for the user from past usage history and newly acquired trends.

[0338] Step 3:

[0339] The device sends user input and operation patterns to the emotion engine. Input includes user typing and click patterns, as well as facial recognition data indicating emotions. The emotion engine analyzes this data to identify the current emotional state. The output provides information based on the emotional state. For example, it might generate emotion data indicating "the user is feeling stressed."

[0340] Step 4:

[0341] The server integrates acquired emotional and profile information to generate service suggestions optimized for individual needs. Inputs include emotional data and profile data. Based on this, the server makes suggestions that include relaxation music and access information to specific services. The output generates a list of personalized services for each user.

[0342] Step 5:

[0343] The terminal displays the generated service suggestions on the user interface. The input is suggestion information sent from the server. Based on this, the terminal visually highlights the information in a way that allows the user to intuitively select. The output is a list of services presented as options. Specifically, a link to a music streaming service for stress relief is displayed in an active state.

[0344] (Application Example 2)

[0345] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0346] The problem that this invention aims to solve is to enrich the way people spend time at home by providing optimal services based on their emotions. Conventional systems have found it difficult to accurately grasp the emotional state of users and propose the most suitable service at that moment.

[0347] 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.

[0348] In this invention, the server includes means for analyzing and identifying the user's emotional state, means for collecting user profile information, and means for obtaining information from a partner database. This makes it possible to provide personalized services that respond to the user's real-time emotional state.

[0349] "Means for analyzing and identifying the user's emotional state" refers to a function that uses emotion analysis technology to identify the user's current emotional state based on data such as their speech and facial expressions.

[0350] "Means for collecting user profile information" refers to a function that retrieves profile data, including users' personal information and past behavioral history, from a database and collects information related to the individual.

[0351] "Means of obtaining information from partner databases" refers to functions that link with external databases to obtain information and service data related to the user's interests.

[0352] "A means of analyzing collected information and proposing services appropriate to the user's stage of life" refers to a function that analyzes collected user data and, based on the results, proposes services that match the user's stage of life and needs.

[0353] "Means of providing the proposed service to the user's device" refers to a function that appropriately displays the proposed service information on the user's device and makes it easily accessible to the user.

[0354] "A means of summarizing the latest trend information using generative artificial intelligence" refers to a function that utilizes artificial intelligence technology to analyze the latest information collected from external sources and summarize it in a way that is easy for users to understand.

[0355] "Means of linking data obtained from multiple information sources" refers to a function that combines data collected from different databases, integrates the information by creating meaningful relationships between them.

[0356] To implement this invention, it is necessary to build a system that analyzes the user's emotions within the home and proposes personalized services. This system consists of a user terminal, a server, and an emotion recognition engine.

[0357] The server first has a means of collecting user profile information. Specifically, it retrieves data such as the user's age, lifestyle, and past behavioral history from a database, and uses this to create an individualized profile. This profile is used to optimize the proposed services.

[0358] The emotion recognition engine uses data acquired from the camera and microphone to analyze the user's emotional state. This engine identifies the user's emotions by analyzing changes in voice tone and facial expressions. This emotional information is transmitted to the server in real time to aid in service delivery.

[0359] The server also has a means of suggesting the most relevant trend information and services to users by utilizing information obtained from partner databases. This information includes suggestions tailored to the user's situation, such as the latest entertainment and relaxation methods.

[0360] On the device, when users receive service suggestions, the information is presented in a way that is easy to understand intuitively. To this end, relaxing music is played, and appropriate video content is suggested.

[0361] For example, if a user looks tired after work, the emotion recognition engine will detect this state, and the server will recommend relaxation music. This suggestion will be displayed to the user through their device.

[0362] Generative AI models use prompts such as, "Create a program that suggests the most suitable entertainment activity for the user based on their current emotional state," as an example of a prompt used for summarizing information and generating suggestions.

[0363] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0364] Step 1:

[0365] The server retrieves user profile information from the database. The input requires a user ID, and the output includes profile data such as age, hobbies, and past service usage history. Based on this data, subsequent processing can identify services suitable for the user.

[0366] Step 2:

[0367] The emotion recognition engine receives real-time audio and video data acquired from the device's camera and microphone as input. By analyzing this data, it outputs the user's current emotional state. Specifically, it analyzes voice tone and facial expressions to identify stress levels and fatigue levels.

[0368] Step 3:

[0369] The server receives the user's emotional state output by the emotion recognition engine as input. Based on this, it retrieves relevant service information from the partner database. Through this data acquisition and analysis, it generates a service suggestion list optimized for the user as output.

[0370] Step 4:

[0371] The terminal receives service proposals sent from the server and displays them on the user interface. Input consists of specific service proposal data, and output provides intuitive information to the user through visual displays and audio guidance.

[0372] Step 5:

[0373] The user selects the most suitable service based on the suggestions displayed on the device. This selection process updates the user's preference information and, if necessary, provides prompts to the generating AI model to further optimize the service. The input is the user's selection result, and the output is the updated preference data and improvements to future service suggestions.

[0374] 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.

[0375] 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.

[0376] 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.

[0377] [Third Embodiment]

[0378] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0379] 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.

[0380] 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).

[0381] 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.

[0382] 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.

[0383] 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).

[0384] 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.

[0385] 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.

[0386] 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.

[0387] 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.

[0388] 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.

[0389] 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".

[0390] This invention relates to a system for proposing services optimized for users. The system mainly consists of a server and terminals, and each component plays the role described below.

[0391] The server first collects user profile information, including the user's basic attributes and past behavioral history. This information is collected by the software by accessing a database and is used to identify the user's life stage and needs.

[0392] Next, the server retrieves information from its partner database. Here, it obtains the latest service information and rankings from multiple related companies and service providers. The server further collects publicly available trend information and summarizes it using generative artificial intelligence technology. This summarization process ensures that vast amounts of data are presented to users in an important and easily understandable format.

[0393] The server then integrates and analyzes all the collected information. This analysis generates a list of services that match the user's life stage. Specifically, the server uses the collected information to automatically select services that the user is likely to need at the moment.

[0394] This selected information is presented to the user through the device. The device receives the information and provides it to the user in a user-friendly interface. For example, if a user is spending more time at home, the device can suggest home entertainment options.

[0395] As a concrete example, let's assume a user is preparing to enter university. The server reads this information from the user's profile and retrieves information on student scholarships and financial support from affiliated databases. Furthermore, it uses artificial intelligence to generate and provide information on popular learning programs and events based on social trends. Finally, the device integrates all of this information to help the user intuitively make the necessary choices.

[0396] Thus, the present invention is implemented in a form that enables a highly accurate and rapid response to the needs of users.

[0397] The following describes the processing flow.

[0398] Step 1:

[0399] The server collects user profile information. The software retrieves basic user attributes and past behavioral history from the database and uses this information to analyze the user's life stage and needs.

[0400] Step 2:

[0401] The server accesses the partner database to retrieve information. The server collects the latest service information and rankings from related companies and service providers, and filters the information to be most relevant based on the user's profile.

[0402] Step 3:

[0403] The server collects trend information from external sources and summarizes it using generative artificial intelligence. This prepares the information to be delivered to users in an important and easy-to-understand format.

[0404] Step 4:

[0405] The server integrates and analyzes all the collected information. Using data processing algorithms, it automatically extracts and suggests services suitable for the user, creating a list of recommendations.

[0406] Step 5:

[0407] The terminal receives information from the server and presents it to the user through a user interface. The terminal displays the information in a visually clear and interactive format, supporting users in easily making selections and evaluations.

[0408] (Example 1)

[0409] 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."

[0410] Conventional systems have struggled to quickly and accurately propose the most suitable services to users. This problem stems from insufficient data collection and analysis, as well as an inability to flexibly respond to users' changing needs. Furthermore, the correlation of collected information is often inadequate, resulting in a lack of service recommendations that are truly beneficial to users.

[0411] 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.

[0412] In this invention, the server includes means for collecting user attribute information, means for obtaining information from relevant information sources, and means for analyzing the collected data and recommending services that correspond to the user's status. This makes it possible to propose services that respond quickly and accurately to the diverse needs of users.

[0413] "User attribute information" refers to data that includes the user's basic characteristics, behavioral history, interests, and other relevant information.

[0414] "Relevant information sources" refer to data providers that are accessible for information gathering, such as partner companies, digital platforms, and publicly available information endpoints.

[0415] "Collected data" refers to the collection of all information obtained from user attribute information and related information sources.

[0416] "Services tailored to the user's situation" refers to products and services that are customized to the user's current life stage and individual needs.

[0417] A "generative model" refers to an algorithm that uses natural language processing technology to summarize data and provide information in a format that is easy for humans to understand.

[0418] "Means of association" refers to processes and technologies that integrate data obtained from different sources and process it into consistent information.

[0419] This invention is an information processing system for providing services optimized for users. The system mainly consists of servers and terminals, each playing a specific role.

[0420] The server is responsible for collecting user attribute information, using database access software to obtain basic user characteristics and behavioral history. Furthermore, the server collects information through various digital platforms and APIs to obtain the latest information from relevant sources. Based on a generative model, the server summarizes the collected trend information and analyzes it to select services that correspond to the user's state.

[0421] Specific hardware and software include server equipment that enables high-speed data processing, database management software, and generative AI models that realize natural language processing.

[0422] Next, the device receives recommended services from the server and presents them to the user through an easy-to-use user interface. If the user is looking for a new movie during their activities at home, the server lists movies recommended by partnered streaming services based on the user's past viewing history and provides that information to the user through the device.

[0423] A concrete example of a prompt message would be, "Based on your recent movie viewing history, please suggest some new release movies."

[0424] Through this system, users can receive services that meet their needs quickly and accurately, thereby improving their quality of life.

[0425] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0426] Step 1:

[0427] The server collects user attribute information. As input, it obtains basic characteristics and past behavioral history provided by the user. This information is collected using database access software, and the server uses it for analysis. Specifically, the server analyzes cookie information and log data to identify the user's interests and preferences. As output, user profile data is generated.

[0428] Step 2:

[0429] The server retrieves information from relevant sources. As input, it obtains the latest service information and trend data through affiliated digital platforms and relevant APIs. The server analyzes this information and organizes the relationships between pieces of data as needed. Specifically, the server sends requests to service providers' APIs and stores the obtained data in its internal database. The output is an updated list of information.

[0430] Step 3:

[0431] The server summarizes and analyzes the collected information using a generative AI model. The input for this step is user profile data and updated information obtained from relevant sources. Using prompts, the generative AI model performs the summarization process and refines the information. Specifically, the server prompts the AI ​​model, and the resulting summary is further refined using an internal algorithm. The output is a customized service recommendation list for each user.

[0432] Step 4:

[0433] The terminal displays a list of recommended services sent from the server. The input is recommendation information from the server, which is presented to the user in an easy-to-understand format via the interface. Specifically, the terminal displays a notification on the user's screen, and a function is built that allows the user to view detailed information with the press of a button. As output, the information is presented in a format that is easy for the user to consider, enabling the user to make informed decisions.

[0434] (Application Example 1)

[0435] 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."

[0436] In today's information-saturated world, it is difficult for users to find the products and services that are best suited to them. A system is needed to solve this problem and provide product suggestions that match the user's needs and life stage.

[0437] 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.

[0438] In this invention, the server includes means for collecting user characteristic information, means for obtaining information from multiple databases, and means for analyzing the collected information and suggesting products that suit the user's situation. This enables the rapid suggestion of products and services optimized for the user.

[0439] "User characteristic information" refers to information that shows a user's basic attributes and past behavioral history, and is data used to suggest products and services.

[0440] A "multiple database" refers to a set of multiple sources of information used to aggregate information from related companies and service providers.

[0441] "A means of analyzing collected information and suggesting products that suit the user's situation" refers to a system that integrates user profiles with external information to select products optimized for individual users.

[0442] An "information processing device" is a terminal device that displays suggested information from a server to the user in an intuitive manner.

[0443] "Generative artificial intelligence" is an artificial intelligence technology used to summarize collected trend information and present it in a format that is easy for users to understand.

[0444] "Means of correlating information obtained from different sources" refers to processing methods for effectively integrating information obtained from multiple databases to generate meaningful suggestions.

[0445] This invention realizes a system for proposing products and services optimized for the user. The system consists of a server and an information processing terminal.

[0446] The server first collects user characteristic information. It retrieves basic user attributes and past behavioral history from a database to form a user profile. A database management system (e.g., MySQL) is used in this process.

[0447] Next, the server retrieves information from multiple external databases. This information includes the latest updates from related companies and service providers, and is collected using a variety of APIs.

[0448] The server uses the collected data to perform data analysis, utilizing generative artificial intelligence technologies such as machine learning frameworks (e.g., TensorFlow). This allows it to build a recommendation model that selects products tailored to the user's situation.

[0449] The generated proposals are sent to an information processing terminal. The terminal presents them to the user, displaying them in a user-friendly interface. The smartphone application is developed with React Native, providing the user with an intuitive operating experience.

[0450] For example, if a user is interested in sports equipment, the server will suggest appropriate running shoes and related fitness equipment based on their past purchase history and market trends.

[0451] As an example of a prompt statement, the following request is input to the generating AI model.

[0452] "Considering current trends, please suggest products that a male user in his 30s might be interested in. He has a past purchase history of running-related items."

[0453] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0454] Step 1:

[0455] The server collects user characteristic information. It retrieves the user's basic attributes and past behavioral history from the database to form profile data. The input data is the user ID, and the output data is a user profile object. In this step, an SQL query is executed for data collection.

[0456] Step 2:

[0457] The server retrieves information from multiple databases and gathers external information relevant to the user's interests. This includes product information and trend data from related companies. The input data is the API access key, and the output data is a list of the retrieved information. Necessary information is collected through API requests.

[0458] Step 3:

[0459] The server uses generative artificial intelligence to analyze information and suggest products suitable for the user's situation. It analyzes user profiles and external information and generates a suggestion list using a specific algorithm. Input data consists of profile objects and information lists, while output data is a list of suggested products. Machine learning models such as TensorFlow are used for recommendation processing.

[0460] Step 4:

[0461] The server sends the generated suggestions to the information processing terminal. Based on the suggestion list, it sends the most suitable product information to the terminal. The input data is the suggestion list, and the output data is the product information sent to the user terminal. Data transmission is performed using a network protocol.

[0462] Step 5:

[0463] The terminal presents received suggestions to the user. Product information is displayed on an intuitive user interface, allowing the user to easily browse and select items. Input data is the submitted product information, and output data is the content displayed on the user interface. The UI design is done using React Native.

[0464] Step 6:

[0465] Users browse products displayed on their device and make purchase decisions. Products selected by the user proceed to the purchase process. Input data represents the user's selection, while output data indicates the start of the purchase and delivery procedures. Selection and purchase operations are performed through the user interface.

[0466] 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.

[0467] This invention relates to a system characterized by recognizing user emotions and reflecting them in profiles and service recommendations. This system mainly consists of a server, a terminal, and an emotion engine.

[0468] The server first collects user profile information. This involves retrieving basic user attributes and past behavioral history from a database to identify the user's life stage and needs. Next, the server retrieves relevant information from partner databases. This includes the latest service information, rankings, and relevant data based on the user's interests.

[0469] The emotion engine analyzes user input and behavioral data to recognize the user's emotional state. For example, it analyzes the user's facial expressions and operation patterns on the input interface to identify the user's current emotions. This emotional information is reflected in the service suggestions provided by the server in real time, presenting the optimal choice based on the user's emotional state.

[0470] Trend information is also a crucial element; the server collects this information from external sources and summarizes it using generative artificial intelligence. This provides users with useful and easy-to-understand information. The results of this information collection and analysis are integrated to generate a list of personalized suggestions for the user.

[0471] When users receive suggestions through their devices, the devices display the information clearly through their user interface. For example, if a user is feeling stressed, the device will highlight and display relaxation-related services. Furthermore, the suggestions are dynamically updated in response to the user's emotional changes, providing the optimal experience.

[0472] For example, when a user is feeling stressed at work, the emotion engine detects this state, and the server suggests music streaming services or discount information on recreational spots that can help the user relax. The device then presents these options in an intuitive way, contributing to reducing the user's stress.

[0473] Thus, the present invention is implemented in a form that realizes a highly personalized experience by reflecting the user's emotions in real time.

[0474] The following describes the processing flow.

[0475] Step 1:

[0476] The server collects user profile information. The server accesses the database to retrieve the user's basic attributes and past behavioral history. This generates foundational data for analyzing individual life stages and needs.

[0477] Step 2:

[0478] The device acquires real-time input data from the user. This includes user actions on the interface and biometric data from wearable devices. This data is used as material for emotion recognition.

[0479] Step 3:

[0480] The emotion engine analyzes user input data and detects emotional states. Using algorithms, the emotion engine analyzes user operation patterns and biometric data to identify emotions such as stress and joy.

[0481] Step 4:

[0482] The server retrieves information from partner databases. Here, service information and trend data from multiple sources are reused to narrow down the content that is most relevant to the user.

[0483] Step 5:

[0484] The server integrates and analyzes emotional information and acquired data. By considering the emotional state and linking user profile information with service data, it creates service suggestions that are tailored to the user's feelings.

[0485] Step 6:

[0486] The device displays personalized service suggestions to the user. The device reflects the user's emotional state and provides information in a suitable format. For example, if the user is seeking relaxation, relaxation-related services will be highlighted.

[0487] Step 7:

[0488] The user selects a service from the options presented. The user reviews the information provided via their device and chooses a service that suits their emotional state.

[0489] Step 8:

[0490] The server records the user's selections, forming a feedback loop. Based on the selected information, profile information is further updated to improve the accuracy of future service recommendations.

[0491] (Example 2)

[0492] 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."

[0493] Traditional systems often offered uniform service suggestions without considering the user's emotional state, making it difficult to provide appropriate suggestions tailored to each user's situation. Therefore, there is a need to provide users with more personalized experiences and information that is appropriate to their life stage and emotional state.

[0494] 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.

[0495] In this invention, the server includes a device means for collecting users' personal information, a device means for acquiring data from an external storage area, and a device means for analyzing the acquired data and proposing tasks appropriate to the user's life stage. This makes it possible to reflect the user's emotional state in real time and provide services and information optimized for each individual user.

[0496] A "device for collecting users' personal information" refers to equipment or software that acquires information such as a user's basic attributes, interests, and past behavioral history, and stores it in a database.

[0497] A "device for acquiring data from external storage" is a device that acquires necessary data from external information sources such as the internet or affiliated databases and makes it available for use within the system.

[0498] A "device that analyzes acquired data and proposes tasks appropriate to the user's stage of life" is a device that analyzes collected data and selects and presents the most suitable tasks and services according to the user's current situation.

[0499] A "device that analyzes user input and behavior patterns to identify emotional states" is a device that recognizes emotions from a user's actions and inputs and identifies their current mental state.

[0500] A "device that adjusts suggested services based on emotional information" is a device that selects appropriate services and information based on the user's emotional state and optimizes the content presented.

[0501] A "device that uses machine learning algorithms to summarize the latest trend information" is a device that uses technology to analyze diverse datasets and generate integrated information on current trends and developments.

[0502] A "device that correlates data acquired from diverse memory areas" is a device that correlates data collected from different sources, analyzes it comprehensively, and extracts valuable information.

[0503] This system consists of three main elements: a server, a terminal, and an emotion engine. The method for carrying out the invention is as follows:

[0504] The server first collects the user's personal information. This is done via database access, retrieving the user's basic attributes (age, gender, interests, etc.) and past behavioral history from the data store. This information is used to determine the user's stage in life and suggest the most suitable services.

[0505] Next, the server retrieves information from external storage, such as cloud-based data services. This information includes the latest market trends, popular service rankings, and data tailored to user interests. The collected information is then analyzed using generative AI models to generate meaningful insights.

[0506] The terminal plays the role of transmitting user input information and operation patterns to the emotion engine. This allows the emotion engine to identify the user's emotional state in real time and provide information and service suggestions based on that emotion. For example, if a user is feeling stressed, the engine will detect that emotion, and the server will suggest a music service for relaxation. An example of a prompt in this case would be, "Please suggest services to recommend when the user is feeling stressed at work."

[0507] Furthermore, the device receives suggestions from the server and displays information intuitively through the user interface. In doing so, it visually highlights information that the user is likely to be interested in, making it easier to select. This allows users to easily choose services on the spot and gain options to improve their quality of life.

[0508] This invention aims to dynamically adjust information according to the individual needs of users and provide an emotionally personalized experience.

[0509] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0510] Step 1:

[0511] The server collects users' personal information using database access methods. Inputs include user ID and past behavioral patterns. Based on this data, the server retrieves profile information such as age, gender, and interests from the database. The output is detailed profile information to determine the user's life stage. This information is used in the next proposed step.

[0512] Step 2:

[0513] The server retrieves the latest service information and trend data from external storage. Inputs include access information to relevant APIs and cloud services. The server analyzes this data using a generative AI model to generate meaningful service rankings and trend information. The output provides foundational information for creating personalized recommendations. Specifically, it extracts the most relevant information for the user from past usage history and newly acquired trends.

[0514] Step 3:

[0515] The device sends user input and operation patterns to the emotion engine. Input includes user typing and click patterns, as well as facial recognition data indicating emotions. The emotion engine analyzes this data to identify the current emotional state. The output provides information based on the emotional state. For example, it might generate emotion data indicating "the user is feeling stressed."

[0516] Step 4:

[0517] The server integrates acquired emotional and profile information to generate service suggestions optimized for individual needs. Inputs include emotional data and profile data. Based on this, the server makes suggestions that include relaxation music and access information to specific services. The output generates a list of personalized services for each user.

[0518] Step 5:

[0519] The terminal displays the generated service suggestions on the user interface. The input is suggestion information sent from the server. Based on this, the terminal visually highlights the information in a way that allows the user to intuitively select. The output is a list of services presented as options. Specifically, a link to a music streaming service for stress relief is displayed in an active state.

[0520] (Application Example 2)

[0521] 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."

[0522] The problem that this invention aims to solve is to enrich the way people spend time at home by providing optimal services based on their emotions. Conventional systems have found it difficult to accurately grasp the emotional state of users and propose the most suitable service at that moment.

[0523] 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.

[0524] In this invention, the server includes means for analyzing and identifying the user's emotional state, means for collecting user profile information, and means for obtaining information from a partner database. This makes it possible to provide personalized services that respond to the user's real-time emotional state.

[0525] "Means for analyzing and identifying the user's emotional state" refers to a function that uses emotion analysis technology to identify the user's current emotional state based on data such as their speech and facial expressions.

[0526] "Means for collecting user profile information" refers to a function that retrieves profile data, including users' personal information and past behavioral history, from a database and collects information related to the individual.

[0527] "Means of obtaining information from partner databases" refers to functions that link with external databases to obtain information and service data related to the user's interests.

[0528] "A means of analyzing collected information and proposing services appropriate to the user's stage of life" refers to a function that analyzes collected user data and, based on the results, proposes services that match the user's stage of life and needs.

[0529] "Means of providing the proposed service to the user's device" refers to a function that appropriately displays the proposed service information on the user's device and makes it easily accessible to the user.

[0530] "A means of summarizing the latest trend information using generative artificial intelligence" refers to a function that utilizes artificial intelligence technology to analyze the latest information collected from external sources and summarize it in a way that is easy for users to understand.

[0531] "Means of linking data obtained from multiple information sources" refers to a function that combines data collected from different databases, integrates the information by creating meaningful relationships between them.

[0532] To implement this invention, it is necessary to build a system that analyzes the user's emotions within the home and proposes personalized services. This system consists of a user terminal, a server, and an emotion recognition engine.

[0533] The server first has a means of collecting user profile information. Specifically, it retrieves data such as the user's age, lifestyle, and past behavioral history from a database, and uses this to create an individualized profile. This profile is used to optimize the proposed services.

[0534] The emotion recognition engine uses data acquired from the camera and microphone to analyze the user's emotional state. This engine identifies the user's emotions by analyzing changes in voice tone and facial expressions. This emotional information is transmitted to the server in real time to aid in service delivery.

[0535] The server also has a means of suggesting the most relevant trend information and services to users by utilizing information obtained from partner databases. This information includes suggestions tailored to the user's situation, such as the latest entertainment and relaxation methods.

[0536] On the device, when users receive service suggestions, the information is presented in a way that is easy to understand intuitively. To this end, relaxing music is played, and appropriate video content is suggested.

[0537] For example, if a user looks tired after work, the emotion recognition engine will detect this state, and the server will recommend relaxation music. This suggestion will be displayed to the user through their device.

[0538] Generative AI models use prompts such as, "Create a program that suggests the most suitable entertainment activity for the user based on their current emotional state," as an example of a prompt used for summarizing information and generating suggestions.

[0539] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0540] Step 1:

[0541] The server retrieves user profile information from the database. The input requires a user ID, and the output includes profile data such as age, hobbies, and past service usage history. Based on this data, subsequent processing can identify services suitable for the user.

[0542] Step 2:

[0543] The emotion recognition engine receives real-time audio and video data acquired from the device's camera and microphone as input. By analyzing this data, it outputs the user's current emotional state. Specifically, it analyzes voice tone and facial expressions to identify stress levels and fatigue levels.

[0544] Step 3:

[0545] The server receives the user's emotional state output by the emotion recognition engine as input. Based on this, it retrieves relevant service information from the partner database. Through this data acquisition and analysis, it generates a service suggestion list optimized for the user as output.

[0546] Step 4:

[0547] The terminal receives service proposals sent from the server and displays them on the user interface. Input consists of specific service proposal data, and output provides intuitive information to the user through visual displays and audio guidance.

[0548] Step 5:

[0549] The user selects the most suitable service based on the suggestions displayed on the device. This selection process updates the user's preference information and, if necessary, provides prompts to the generating AI model to further optimize the service. The input is the user's selection result, and the output is the updated preference data and improvements to future service suggestions.

[0550] 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.

[0551] 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.

[0552] 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.

[0553] [Fourth Embodiment]

[0554] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0555] 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.

[0556] 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).

[0557] 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.

[0558] 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.

[0559] 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).

[0560] 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.

[0561] 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.

[0562] 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.

[0563] 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.

[0564] 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.

[0565] 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.

[0566] 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".

[0567] This invention relates to a system for proposing services optimized for users. The system mainly consists of a server and terminals, and each component plays the role described below.

[0568] The server first collects user profile information, including the user's basic attributes and past behavioral history. This information is collected by the software by accessing a database and is used to identify the user's life stage and needs.

[0569] Next, the server retrieves information from its partner database. Here, it obtains the latest service information and rankings from multiple related companies and service providers. The server further collects publicly available trend information and summarizes it using generative artificial intelligence technology. This summarization process ensures that vast amounts of data are presented to users in an important and easily understandable format.

[0570] The server then integrates and analyzes all the collected information. This analysis generates a list of services that match the user's life stage. Specifically, the server uses the collected information to automatically select services that the user is likely to need at the moment.

[0571] This selected information is presented to the user through the device. The device receives the information and provides it to the user in a user-friendly interface. For example, if a user is spending more time at home, the device can suggest home entertainment options.

[0572] As a concrete example, let's assume a user is preparing to enter university. The server reads this information from the user's profile and retrieves information on student scholarships and financial support from affiliated databases. Furthermore, it uses artificial intelligence to generate and provide information on popular learning programs and events based on social trends. Finally, the device integrates all of this information to help the user intuitively make the necessary choices.

[0573] Thus, the present invention is implemented in a form that enables a highly accurate and rapid response to the needs of users.

[0574] The following describes the processing flow.

[0575] Step 1:

[0576] The server collects user profile information. The software retrieves basic user attributes and past behavioral history from the database and uses this information to analyze the user's life stage and needs.

[0577] Step 2:

[0578] The server accesses the partner database to retrieve information. The server collects the latest service information and rankings from related companies and service providers, and filters the information to be most relevant based on the user's profile.

[0579] Step 3:

[0580] The server collects trend information from external sources and summarizes it using generative artificial intelligence. This prepares the information to be delivered to users in an important and easy-to-understand format.

[0581] Step 4:

[0582] The server integrates and analyzes all the collected information. Using data processing algorithms, it automatically extracts and suggests services suitable for the user, creating a list of recommendations.

[0583] Step 5:

[0584] The terminal receives information from the server and presents it to the user through a user interface. The terminal displays the information in a visually clear and interactive format, supporting users in easily making selections and evaluations.

[0585] (Example 1)

[0586] 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".

[0587] Conventional systems have struggled to quickly and accurately propose the most suitable services to users. This problem stems from insufficient data collection and analysis, as well as an inability to flexibly respond to users' changing needs. Furthermore, the correlation of collected information is often inadequate, resulting in a lack of service recommendations that are truly beneficial to users.

[0588] 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.

[0589] In this invention, the server includes means for collecting user attribute information, means for obtaining information from relevant information sources, and means for analyzing the collected data and recommending services that correspond to the user's status. This makes it possible to propose services that respond quickly and accurately to the diverse needs of users.

[0590] "User attribute information" refers to data that includes the user's basic characteristics, behavioral history, interests, and other relevant information.

[0591] "Relevant information sources" refer to data providers that are accessible for information gathering, such as partner companies, digital platforms, and publicly available information endpoints.

[0592] "Collected data" refers to the collection of all information obtained from user attribute information and related information sources.

[0593] "Services tailored to the user's situation" refers to products and services that are customized to the user's current life stage and individual needs.

[0594] A "generative model" refers to an algorithm that uses natural language processing technology to summarize data and provide information in a format that is easy for humans to understand.

[0595] "Means of association" refers to processes and technologies that integrate data obtained from different sources and process it into consistent information.

[0596] This invention is an information processing system for providing services optimized for users. The system mainly consists of servers and terminals, each playing a specific role.

[0597] The server is responsible for collecting user attribute information, using database access software to obtain basic user characteristics and behavioral history. Furthermore, the server collects information through various digital platforms and APIs to obtain the latest information from relevant sources. Based on a generative model, the server summarizes the collected trend information and analyzes it to select services that correspond to the user's state.

[0598] Specific hardware and software include server equipment that enables high-speed data processing, database management software, and generative AI models that realize natural language processing.

[0599] Next, the device receives recommended services from the server and presents them to the user through an easy-to-use user interface. If the user is looking for a new movie during their activities at home, the server lists movies recommended by partnered streaming services based on the user's past viewing history and provides that information to the user through the device.

[0600] A concrete example of a prompt message would be, "Based on your recent movie viewing history, please suggest some new release movies."

[0601] Through this system, users can receive services that meet their needs quickly and accurately, thereby improving their quality of life.

[0602] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0603] Step 1:

[0604] The server collects user attribute information. As input, it obtains basic characteristics and past behavioral history provided by the user. This information is collected using database access software, and the server uses it for analysis. Specifically, the server analyzes cookie information and log data to identify the user's interests and preferences. As output, user profile data is generated.

[0605] Step 2:

[0606] The server retrieves information from relevant sources. As input, it obtains the latest service information and trend data through affiliated digital platforms and relevant APIs. The server analyzes this information and organizes the relationships between pieces of data as needed. Specifically, the server sends requests to service providers' APIs and stores the obtained data in its internal database. The output is an updated list of information.

[0607] Step 3:

[0608] The server summarizes and analyzes the collected information using a generative AI model. The input for this step is user profile data and updated information obtained from relevant sources. Using prompts, the generative AI model performs the summarization process and refines the information. Specifically, the server prompts the AI ​​model, and the resulting summary is further refined using an internal algorithm. The output is a customized service recommendation list for each user.

[0609] Step 4:

[0610] The terminal displays a list of recommended services sent from the server. The input is recommendation information from the server, which is presented to the user in an easy-to-understand format via the interface. Specifically, the terminal displays a notification on the user's screen, and a function is built that allows the user to view detailed information with the press of a button. As output, the information is presented in a format that is easy for the user to consider, enabling the user to make informed decisions.

[0611] (Application Example 1)

[0612] 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".

[0613] In today's information-saturated world, it is difficult for users to find the products and services that are best suited to them. A system is needed to solve this problem and provide product suggestions that match the user's needs and life stage.

[0614] 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.

[0615] In this invention, the server includes means for collecting user characteristic information, means for obtaining information from multiple databases, and means for analyzing the collected information and suggesting products that suit the user's situation. This enables the rapid suggestion of products and services optimized for the user.

[0616] "User characteristic information" refers to information that shows a user's basic attributes and past behavioral history, and is data used to suggest products and services.

[0617] A "multiple database" refers to a set of multiple sources of information used to aggregate information from related companies and service providers.

[0618] "A means of analyzing collected information and suggesting products that suit the user's situation" refers to a system that integrates user profiles with external information to select products optimized for individual users.

[0619] An "information processing device" is a terminal device that displays suggested information from a server to the user in an intuitive manner.

[0620] "Generative artificial intelligence" is an artificial intelligence technology used to summarize collected trend information and present it in a format that is easy for users to understand.

[0621] "Means of correlating information obtained from different sources" refers to processing methods for effectively integrating information obtained from multiple databases to generate meaningful suggestions.

[0622] This invention realizes a system for proposing products and services optimized for the user. The system consists of a server and an information processing terminal.

[0623] The server first collects user characteristic information. It retrieves basic user attributes and past behavioral history from a database to form a user profile. A database management system (e.g., MySQL) is used in this process.

[0624] Next, the server retrieves information from multiple external databases. This information includes the latest updates from related companies and service providers, and is collected using a variety of APIs.

[0625] The server uses the collected data to perform data analysis, utilizing generative artificial intelligence technologies such as machine learning frameworks (e.g., TensorFlow). This allows it to build a recommendation model that selects products tailored to the user's situation.

[0626] The generated proposals are sent to an information processing terminal. The terminal presents them to the user, displaying them in a user-friendly interface. The smartphone application is developed with React Native, providing the user with an intuitive operating experience.

[0627] For example, if a user is interested in sports equipment, the server will suggest appropriate running shoes and related fitness equipment based on their past purchase history and market trends.

[0628] As an example of a prompt statement, the following request is input to the generating AI model.

[0629] "Considering current trends, please suggest products that a male user in his 30s might be interested in. He has a past purchase history of running-related items."

[0630] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0631] Step 1:

[0632] The server collects user characteristic information. It retrieves the user's basic attributes and past behavioral history from the database to form profile data. The input data is the user ID, and the output data is a user profile object. In this step, an SQL query is executed for data collection.

[0633] Step 2:

[0634] The server retrieves information from multiple databases and gathers external information relevant to the user's interests. This includes product information and trend data from related companies. The input data is the API access key, and the output data is a list of the retrieved information. Necessary information is collected through API requests.

[0635] Step 3:

[0636] The server uses generative artificial intelligence to analyze information and suggest products suitable for the user's situation. It analyzes user profiles and external information and generates a suggestion list using a specific algorithm. Input data consists of profile objects and information lists, while output data is a list of suggested products. Machine learning models such as TensorFlow are used for recommendation processing.

[0637] Step 4:

[0638] The server sends the generated suggestions to the information processing terminal. Based on the suggestion list, it sends the most suitable product information to the terminal. The input data is the suggestion list, and the output data is the product information sent to the user terminal. Data transmission is performed using a network protocol.

[0639] Step 5:

[0640] The terminal presents received suggestions to the user. Product information is displayed on an intuitive user interface, allowing the user to easily browse and select items. Input data is the submitted product information, and output data is the content displayed on the user interface. The UI design is done using React Native.

[0641] Step 6:

[0642] Users browse products displayed on their device and make purchase decisions. Products selected by the user proceed to the purchase process. Input data represents the user's selection, while output data indicates the start of the purchase and delivery procedures. Selection and purchase operations are performed through the user interface.

[0643] 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.

[0644] This invention relates to a system characterized by recognizing user emotions and reflecting them in profiles and service recommendations. This system mainly consists of a server, a terminal, and an emotion engine.

[0645] The server first collects user profile information. This involves retrieving basic user attributes and past behavioral history from a database to identify the user's life stage and needs. Next, the server retrieves relevant information from partner databases. This includes the latest service information, rankings, and relevant data based on the user's interests.

[0646] The emotion engine analyzes user input and behavioral data to recognize the user's emotional state. For example, it analyzes the user's facial expressions and operation patterns on the input interface to identify the user's current emotions. This emotional information is reflected in the service suggestions provided by the server in real time, presenting the optimal choice based on the user's emotional state.

[0647] Trend information is also a crucial element; the server collects this information from external sources and summarizes it using generative artificial intelligence. This provides users with useful and easy-to-understand information. The results of this information collection and analysis are integrated to generate a list of personalized suggestions for the user.

[0648] When users receive suggestions through their devices, the devices display the information clearly through their user interface. For example, if a user is feeling stressed, the device will highlight and display relaxation-related services. Furthermore, the suggestions are dynamically updated in response to the user's emotional changes, providing the optimal experience.

[0649] For example, when a user is feeling stressed at work, the emotion engine detects this state, and the server suggests music streaming services or discount information on recreational spots that can help the user relax. The device then presents these options in an intuitive way, contributing to reducing the user's stress.

[0650] Thus, the present invention is implemented in a form that realizes a highly personalized experience by reflecting the user's emotions in real time.

[0651] The following describes the processing flow.

[0652] Step 1:

[0653] The server collects user profile information. The server accesses the database to retrieve the user's basic attributes and past behavioral history. This generates foundational data for analyzing individual life stages and needs.

[0654] Step 2:

[0655] The device acquires real-time input data from the user. This includes user actions on the interface and biometric data from wearable devices. This data is used as material for emotion recognition.

[0656] Step 3:

[0657] The emotion engine analyzes user input data and detects emotional states. Using algorithms, the emotion engine analyzes user operation patterns and biometric data to identify emotions such as stress and joy.

[0658] Step 4:

[0659] The server retrieves information from partner databases. Here, service information and trend data from multiple sources are reused to narrow down the content that is most relevant to the user.

[0660] Step 5:

[0661] The server integrates and analyzes emotional information and acquired data. By considering the emotional state and linking user profile information with service data, it creates service suggestions that are tailored to the user's feelings.

[0662] Step 6:

[0663] The device displays personalized service suggestions to the user. The device reflects the user's emotional state and provides information in a suitable format. For example, if the user is seeking relaxation, relaxation-related services will be highlighted.

[0664] Step 7:

[0665] The user selects a service from the options presented. The user reviews the information provided via their device and chooses a service that suits their emotional state.

[0666] Step 8:

[0667] The server records the user's selections, forming a feedback loop. Based on the selected information, profile information is further updated to improve the accuracy of future service recommendations.

[0668] (Example 2)

[0669] 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".

[0670] Traditional systems often offered uniform service suggestions without considering the user's emotional state, making it difficult to provide appropriate suggestions tailored to each user's situation. Therefore, there is a need to provide users with more personalized experiences and information that is appropriate to their life stage and emotional state.

[0671] 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.

[0672] In this invention, the server includes a device means for collecting users' personal information, a device means for acquiring data from an external storage area, and a device means for analyzing the acquired data and proposing tasks appropriate to the user's life stage. This makes it possible to reflect the user's emotional state in real time and provide services and information optimized for each individual user.

[0673] A "device for collecting users' personal information" refers to equipment or software that acquires information such as a user's basic attributes, interests, and past behavioral history, and stores it in a database.

[0674] A "device for acquiring data from external storage" is a device that acquires necessary data from external information sources such as the internet or affiliated databases and makes it available for use within the system.

[0675] A "device that analyzes acquired data and proposes tasks appropriate to the user's stage of life" is a device that analyzes collected data and selects and presents the most suitable tasks and services according to the user's current situation.

[0676] A "device that analyzes user input and behavior patterns to identify emotional states" is a device that recognizes emotions from a user's actions and inputs and identifies their current mental state.

[0677] A "device that adjusts suggested services based on emotional information" is a device that selects appropriate services and information based on the user's emotional state and optimizes the content presented.

[0678] A "device that uses machine learning algorithms to summarize the latest trend information" is a device that uses technology to analyze diverse datasets and generate integrated information on current trends and developments.

[0679] A "device that correlates data acquired from diverse memory areas" is a device that correlates data collected from different sources, analyzes it comprehensively, and extracts valuable information.

[0680] This system consists of three main elements: a server, a terminal, and an emotion engine. The method for carrying out the invention is as follows:

[0681] The server first collects the user's personal information. This is done via database access, retrieving the user's basic attributes (age, gender, interests, etc.) and past behavioral history from the data store. This information is used to determine the user's stage in life and suggest the most suitable services.

[0682] Next, the server retrieves information from external storage, such as cloud-based data services. This information includes the latest market trends, popular service rankings, and data tailored to user interests. The collected information is then analyzed using generative AI models to generate meaningful insights.

[0683] The terminal plays the role of transmitting user input information and operation patterns to the emotion engine. This allows the emotion engine to identify the user's emotional state in real time and provide information and service suggestions based on that emotion. For example, if a user is feeling stressed, the engine will detect that emotion, and the server will suggest a music service for relaxation. An example of a prompt in this case would be, "Please suggest services to recommend when the user is feeling stressed at work."

[0684] Furthermore, the device receives suggestions from the server and displays information intuitively through the user interface. In doing so, it visually highlights information that the user is likely to be interested in, making it easier to select. This allows users to easily choose services on the spot and gain options to improve their quality of life.

[0685] This invention aims to dynamically adjust information according to the individual needs of users and provide an emotionally personalized experience.

[0686] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0687] Step 1:

[0688] The server collects users' personal information using database access methods. Inputs include user ID and past behavioral patterns. Based on this data, the server retrieves profile information such as age, gender, and interests from the database. The output is detailed profile information to determine the user's life stage. This information is used in the next proposed step.

[0689] Step 2:

[0690] The server retrieves the latest service information and trend data from external storage. Inputs include access information to relevant APIs and cloud services. The server analyzes this data using a generative AI model to generate meaningful service rankings and trend information. The output provides foundational information for creating personalized recommendations. Specifically, it extracts the most relevant information for the user from past usage history and newly acquired trends.

[0691] Step 3:

[0692] The device sends user input and operation patterns to the emotion engine. Input includes user typing and click patterns, as well as facial recognition data indicating emotions. The emotion engine analyzes this data to identify the current emotional state. The output provides information based on the emotional state. For example, it might generate emotion data indicating "the user is feeling stressed."

[0693] Step 4:

[0694] The server integrates acquired emotional and profile information to generate service suggestions optimized for individual needs. Inputs include emotional data and profile data. Based on this, the server makes suggestions that include relaxation music and access information to specific services. The output generates a list of personalized services for each user.

[0695] Step 5:

[0696] The terminal displays the generated service suggestions on the user interface. The input is suggestion information sent from the server. Based on this, the terminal visually highlights the information in a way that allows the user to intuitively select. The output is a list of services presented as options. Specifically, a link to a music streaming service for stress relief is displayed in an active state.

[0697] (Application Example 2)

[0698] 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".

[0699] The problem that this invention aims to solve is to enrich the way people spend time at home by providing optimal services based on their emotions. Conventional systems have found it difficult to accurately grasp the emotional state of users and propose the most suitable service at that moment.

[0700] 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.

[0701] In this invention, the server includes means for analyzing and identifying the user's emotional state, means for collecting user profile information, and means for obtaining information from a partner database. This makes it possible to provide personalized services that respond to the user's real-time emotional state.

[0702] "Means for analyzing and identifying the user's emotional state" refers to a function that uses emotion analysis technology to identify the user's current emotional state based on data such as their speech and facial expressions.

[0703] "Means for collecting user profile information" refers to a function that retrieves profile data, including users' personal information and past behavioral history, from a database and collects information related to the individual.

[0704] "Means of obtaining information from partner databases" refers to functions that link with external databases to obtain information and service data related to the user's interests.

[0705] "A means of analyzing collected information and proposing services appropriate to the user's stage of life" refers to a function that analyzes collected user data and, based on the results, proposes services that match the user's stage of life and needs.

[0706] "Means of providing the proposed service to the user's device" refers to a function that appropriately displays the proposed service information on the user's device and makes it easily accessible to the user.

[0707] "A means of summarizing the latest trend information using generative artificial intelligence" refers to a function that utilizes artificial intelligence technology to analyze the latest information collected from external sources and summarize it in a way that is easy for users to understand.

[0708] "Means of linking data obtained from multiple information sources" refers to a function that combines data collected from different databases, integrates the information by creating meaningful relationships between them.

[0709] To implement this invention, it is necessary to build a system that analyzes the user's emotions within the home and proposes personalized services. This system consists of a user terminal, a server, and an emotion recognition engine.

[0710] The server first has a means of collecting user profile information. Specifically, it retrieves data such as the user's age, lifestyle, and past behavioral history from a database, and uses this to create an individualized profile. This profile is used to optimize the proposed services.

[0711] The emotion recognition engine uses data acquired from the camera and microphone to analyze the user's emotional state. This engine identifies the user's emotions by analyzing changes in voice tone and facial expressions. This emotional information is transmitted to the server in real time to aid in service delivery.

[0712] The server also has a means of suggesting the most relevant trend information and services to users by utilizing information obtained from partner databases. This information includes suggestions tailored to the user's situation, such as the latest entertainment and relaxation methods.

[0713] On the device, when users receive service suggestions, the information is presented in a way that is easy to understand intuitively. To this end, relaxing music is played, and appropriate video content is suggested.

[0714] For example, if a user looks tired after work, the emotion recognition engine will detect this state, and the server will recommend relaxation music. This suggestion will be displayed to the user through their device.

[0715] Generative AI models use prompts such as, "Create a program that suggests the most suitable entertainment activity for the user based on their current emotional state," as an example of a prompt used for summarizing information and generating suggestions.

[0716] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0717] Step 1:

[0718] The server retrieves user profile information from the database. The input requires a user ID, and the output includes profile data such as age, hobbies, and past service usage history. Based on this data, subsequent processing can identify services suitable for the user.

[0719] Step 2:

[0720] The emotion recognition engine receives real-time audio and video data acquired from the device's camera and microphone as input. By analyzing this data, it outputs the user's current emotional state. Specifically, it analyzes voice tone and facial expressions to identify stress levels and fatigue levels.

[0721] Step 3:

[0722] The server receives the user's emotional state output by the emotion recognition engine as input. Based on this, it retrieves relevant service information from the partner database. Through this data acquisition and analysis, it generates a service suggestion list optimized for the user as output.

[0723] Step 4:

[0724] The terminal receives service proposals sent from the server and displays them on the user interface. Input consists of specific service proposal data, and output provides intuitive information to the user through visual displays and audio guidance.

[0725] Step 5:

[0726] The user selects the most suitable service based on the suggestions displayed on the device. This selection process updates the user's preference information and, if necessary, provides prompts to the generating AI model to further optimize the service. The input is the user's selection result, and the output is the updated preference data and improvements to future service suggestions.

[0727] 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.

[0728] 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.

[0729] 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 robot 414.

[0730] 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.

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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.

[0735] 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."

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] 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.

[0743] 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.

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] The following is further disclosed regarding the embodiments described above.

[0749] (Claim 1)

[0750] Means for collecting user profile information,

[0751] Means of obtaining information from partner databases,

[0752] A means of analyzing collected information and proposing services that are appropriate for the user's life stage,

[0753] The means of providing the proposed service to the user's terminal,

[0754] A system that includes this.

[0755] (Claim 2)

[0756] The system according to claim 1, comprising means for summarizing the latest trend information using generative artificial intelligence.

[0757] (Claim 3)

[0758] The system according to claim 1, comprising means for relating information obtained from multiple databases to each other.

[0759] "Example 1"

[0760] (Claim 1)

[0761] Means for collecting user attribute information,

[0762] Means of obtaining information from relevant sources,

[0763] A means of analyzing collected data and recommending services that are appropriate to the user's condition,

[0764] Means for providing the recommended service to the user's device,

[0765] A system that includes this.

[0766] (Claim 2)

[0767] The system according to claim 1, comprising means for simplifying the latest trend information using a generative model.

[0768] (Claim 3)

[0769] The system according to claim 1, comprising means for correlating data obtained from multiple sources.

[0770] "Application Example 1"

[0771] (Claim 1)

[0772] Means for collecting user characteristics information,

[0773] Methods for retrieving information from multiple databases,

[0774] A means of analyzing collected information and suggesting products that suit the user's situation,

[0775] A means of presenting the proposed product to an information processing device,

[0776] A system that includes this.

[0777] (Claim 2)

[0778] The system according to claim 1, comprising means for summarizing trend information using generative artificial intelligence.

[0779] (Claim 3)

[0780] The system according to claim 1, comprising means for correlating information obtained from different sources.

[0781] "Example 2 of combining an emotion engine"

[0782] (Claim 1)

[0783] A device and means for collecting users' personal information,

[0784] A device means for acquiring data from an external storage area,

[0785] A device that analyzes acquired data and proposes tasks suitable for the user's life stage,

[0786] A device and means for providing the proposed service to the user's device,

[0787] A device means that analyzes the user's input and behavior patterns to identify their emotional state,

[0788] A device and means for adjusting the tasks proposed based on emotional information,

[0789] A system that includes this.

[0790] (Claim 2)

[0791] The system according to claim 1, comprising a device that compiles the latest trend information using a machine learning algorithm.

[0792] (Claim 3)

[0793] The system according to claim 1, comprising a device for relating data acquired from various storage areas.

[0794] "Application example 2 when combining with an emotional engine"

[0795] (Claim 1)

[0796] A means of analyzing and identifying the emotional state of users,

[0797] Means for collecting user profile information,

[0798] Means of obtaining information from partner databases,

[0799] A means of analyzing collected information and proposing services appropriate to the user's stage of life,

[0800] The means of providing the proposed service to the user's device,

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, comprising means for summarizing the latest trend information using generative artificial intelligence.

[0804] (Claim 3)

[0805] The system according to claim 1, comprising means for relating data obtained from multiple information repositories to each other. [Explanation of Symbols]

[0806] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for collecting user characteristic information, Methods for retrieving information from multiple databases, A means of analyzing collected information and suggesting products that suit the user's situation, A means of presenting the proposed product to an information processing device, A system that includes this.

2. The system according to claim 1, comprising means for summarizing trend information using generative artificial intelligence.

3. The system according to claim 1, comprising means for correlating information obtained from different sources.

Images