system

Abstract

We provide the system. [Solution] A means for the user to input information about their areas of interest and personality, A means of sending the input information to the server, A means of analyzing the information received by the server and selecting the optimal application from the database, A means of sending information about the selected application to the terminal, A system that includes means for displaying transmitted application information to the user.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, 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] s>In modern times, it is not easy for users to find applications that suit their interests and personalities. There are a huge number of applications, and it takes a great deal of time and effort to appropriately screen them and find the optimal ones. Furthermore, users have limited opportunities to encounter useful applications that they or others could not have thought of. As a result, there is a problem of decreased user satisfaction.

Means for Solving the Problems

[0005] This invention provides a system in which a user inputs information about their areas of interest and personality, and transmits this input data to a server. The server analyzes the received information and selects the most suitable application from a database. Information about the selected application is transmitted to a terminal, which then displays it to the user. This system makes it possible to automatically suggest useful applications that the user or others might not have thought of, thereby improving user satisfaction. Specifically, this includes the step of tagging applications based on the user's input data and matching them with application information in the database. The invention also provides means for generating a list of selected applications and including their detailed information.

[0006] A "user" is a person or entity that uses the system to input information about their interests and personality, and receives recommended applications.

[0007] "Input methods" refer to interfaces that allow users to provide the system with information about their areas of interest and personality.

[0008] "Means of transmission" refers to the means of communication used to send information entered by the user to the server.

[0009] "Means of analysis" refers to the processes and technologies used by a server to compare application information in a database based on user information received by the server.

[0010] A "database" is a part of a system that stores information from multiple applications, and is used by a server to access and select applications.

[0011] "Selection methods" refer to the process and techniques for identifying the application that best suits the user's areas of interest and personality, based on application information within the database.

[0012] A "list" is a format that summarizes the detailed information of the selected applications and is presented to the user.

[0013] "Means of display" refers to the technologies and processes by which a terminal visually presents application information received from a server to the user through a user interface. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0015] 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.

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

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

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

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

[0020] 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).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention relates to a system that takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Specific embodiments of this system are described below.

[0036] 1. User input

[0037] Users use smartphones or other devices to input information about their areas of interest and personality through a dedicated application or web interface. For example, consider a case where a user inputs information such as "reading" and "introverted."

[0038] 2. Transmission method of the terminal

[0039] The terminal formats the information entered by the user into JSON or XML format and sends it to the server as an HTTP request. User input data is protected by a secure protocol.

[0040] 3. Server analysis methods

[0041] The server parses the JSON data received from the terminal. For example, it retrieves data like the following:

[0042] json

[0043] {

[0044] "interest": "reading",

[0045] "personality": "introverted"

[0046] }

[0047] The server analyzes this data to identify the user's areas of interest and personality.

[0048] 4. Server Selection Methods

[0049] The server searches the database for application information and selects the most suitable application based on the user's input. The database is categorized by application areas of interest and personality tags.

[0050] For example, search for applications tagged with "reading" and "introverted." Applications found in this step might include reading community apps or reading list management apps.

[0051] 5. Server result generation means

[0052] The server generates a list of appropriate applications from the search results. This list includes detailed information such as the application name, description, and download link.

[0053] The generated list is then converted back into JSON or XML format and sent to the terminal.

[0054] 6. Display methods for the terminal

[0055] The terminal analyzes application information received from the server and displays it on the user interface. Users can view a list of recommended applications and check detailed information.

[0056] Specific example

[0057] 1. User input

[0058] The user opens the application on their device and enters their area of ​​interest, "reading," and their personality type, "introverted."

[0059] 2. Sending from the device

[0060] The terminal formats the input data as follows and sends it to the server:

[0061] json

[0062] {

[0063] "interest": "reading",

[0064] "personality": "introverted"

[0065] }

[0066] 3. Server analysis

[0067] The server performs analysis and extracts "reading" and "introversion" from the user's data.

[0068] 4. Server Selection

[0069] The server searches the database and finds the relevant application. For example, "reading community app" might be the relevant one.

[0070] 5. Generating the results

[0071] The server generates a list of found applications and sends it to the terminal in the following format:

[0072] json

[0073] {

[0074] "recommendations": [

[0075] {

[0076] "name": "Reading community app",

[0077] "Description": "An app that allows you to connect with people who love reading."

[0078] "link": "http: / / example.com / app1"

[0079] }

[0080] ]

[0081] }

[0082] 6. Display on the device

[0083] The device analyzes the received information and displays details about the "Reading Community App" to the user. The user can read the application description and click the download link to install the application.

[0084] This system aims to improve user satisfaction by allowing users to easily find the most suitable applications based on their interests and personality.

[0085] The following describes the processing flow.

[0086] Step 1:

[0087] The user enters information about their areas of interest and personality. For example, the user might use a smartphone application to enter information such as "sports" and "sociable."

[0088] Step 2:

[0089] The terminal formats the user's input information into JSON format. Specifically, it converts it to the following data format:

[0090] json

[0091] {

[0092] "interest": "sports",

[0093] "personality": "social"

[0094] }

[0095] Step 3:

[0096] The device formats the JSON data and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for transmission.

[0097] Step 4:

[0098] The server receives an HTTP request and parses the JSON data. The analysis extracts the information "sports" and "sociable."

[0099] Step 5:

[0100] The server queries the database based on the information it extracts. The query includes searching for applications tagged with "sports" and "sociable".

[0101] Step 6:

[0102] The server analyzes the query results and generates a list of applications best suited to the user's interests and personality. For example, the following applications might be selected:

[0103] Sports event participation app

[0104] Team sports matching app

[0105] Step 7:

[0106] The application list generated by the server is converted back into JSON format and sent to the terminal. The JSON data will be in the following format:

[0107] json

[0108] {

[0109] "recommendations": [

[0110] {

[0111] "name": "Sports event participation app",

[0112] "Description": "An app that makes it easy to participate in sports events held in your neighborhood."

[0113] "link": "http: / / example.com / app1"

[0114] },

[0115] {

[0116] "name": "Team Sports Matching App",

[0117] "Description": "An app that allows you to match with people who share the same interest in the same sport and form a team."

[0118] "link": "http: / / example.com / app2"

[0119] }

[0120] ]

[0121] }

[0122] Step 8:

[0123] The terminal parses the JSON data received from the server. Based on the analysis results, it prepares to display information about recommended applications in the user interface.

[0124] Step 9:

[0125] The device displays an application list to the user through its user interface. The user can view details of the recommended applications and obtain them using the download links.

[0126] This process makes it easy for users to find applications that perfectly match their interests and personality.

[0127] (Example 1)

[0128] 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."

[0129] Traditional application recommendation systems have struggled to effectively provide users with appropriate applications that are sufficiently based on their interests and personalities. In particular, it takes considerable time and effort for users to find the best fit from a vast number of applications. There is a need for a system that can solve this problem and provide users with the most suitable applications quickly and efficiently.

[0130] 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.

[0131] In this invention, the server includes means for inputting information about the user's areas of interest and personality; means for converting the input information into a data format and transmitting it to the server; means for the server to analyze the received information and select the most suitable software from a database based on the user's areas of interest and personality; means for generating a list of selected software, converting it into a data format including detailed information and transmitting it to a terminal; and means for displaying the transmitted software information to the user. This enables the user to quickly and accurately find applications that match their interests and personality.

[0132] "User" refers to an individual or group that uses a computer system or digital service.

[0133] "Areas of interest" refers to themes and topics that users are interested in and in which they gather information and engage in activities.

[0134] "Personality" refers to psychological attributes that indicate an individual's tendencies in behavior and thinking.

[0135] "Means of input" refers to the devices or interfaces that users use to provide information.

[0136] "Terminal" refers to an electronic device (e.g., smartphone, PC) that a user uses to input and receive information.

[0137] "Converting to a data format" refers to the act of changing information into a structured format (e.g., JSON, XML) that follows certain rules.

[0138] A "server" refers to a computer system that receives and processes requests from users.

[0139] "Analyzing received information" refers to the act of a server reading data sent by a user, understanding its contents, and processing it.

[0140] A "database" refers to a system for efficiently storing and retrieving information.

[0141] "Selecting software" refers to the act of choosing the most suitable application based on specified criteria.

[0142] "Software" refers to a computer program that runs on an electronic device and provides a specific function.

[0143] "Generating a list" refers to the act of organizing selected items (e.g., applications) into a list format.

[0144] "Detailed information" refers to additional and specific data (e.g., name, description, link) related to the selected item (e.g., software).

[0145] "Converting to a data format" refers to the act of structuring information into a different, defined format.

[0146] "To display" refers to the act of visually presenting information through the user interface of a device.

[0147] This invention relates to a system that takes user information about their areas of interest and personality and recommends appropriate software based on that information. Specific embodiments of this system are described below.

[0148] 1. User input

[0149] Users open a dedicated application or web interface using a device such as a smartphone or PC. The user interface displays forms for entering information about their areas of interest and personality. For example, the user might enter "reading" and "introverted."

[0150] 2. Data transmission from the terminal

[0151] The terminal formats the data entered by the user into JSON format. The formatted data is then sent to the server using the HTTPS protocol. For example, the data is sent as follows:

[0152] json

[0153] {

[0154] "interest": "reading",

[0155] "personality": "introverted"

[0156] }

[0157] 3. Server data analysis

[0158] The server parses the received JSON data and extracts the user's areas of interest (e.g., "reading") and personality traits (e.g., "introverted"). A JSON parser library is used for this analysis.

[0159] 4. Server application selection

[0160] The server searches the database and selects the most suitable software based on the user's input data. The database contains software information categorized by areas of interest and personality tags. For example, it searches for software tagged with "reading" and "introverted."

[0161] 5. Server result generation

[0162] The server generates a list of recommended software from the search results. This list includes the software name, description, and download link. The generated list is then converted back into JSON format and sent to the terminal.

[0163] 6. Display on the device

[0164] The terminal parses the JSON data received from the server and displays a list of recommended software in the user interface. The user can view detailed information about the software and, if necessary, click the download link to install it.

[0165] Specific example:

[0166] 1. User input

[0167] The user opens the application on their smartphone and enters their area of ​​interest, "reading," and their personality type, "introverted."

[0168] 2. Sending from the device

[0169] The terminal formats the input data into JSON format and sends it to the server:

[0170] {

[0171] "interest": "reading",

[0172] "personality": "introverted"

[0173] }

[0174] 3. Server analysis

[0175] The server performs analysis and extracts "reading" and "introversion" from the user's data.

[0176] 4. Server Selection

[0177] The server searches the database and finds software tagged as "reading" and "introverted."

[0178] 5. Generating the results

[0179] The server generates a list of the found software and sends it to the terminal in the following format:

[0180] {

[0181] "recommendations": [

[0182] {

[0183] "name": "Reading community app",

[0184] "Description": "An app that allows you to connect with people who love reading."

[0185] "link": "http: / / example.com / app1"

[0186] }

[0187] ]

[0188] }

[0189] 6. Display on the device

[0190] The device analyzes the received information and displays details about the "Reading Community App" to the user. The user can then read the application description and click the download link to install the application.

[0191] This system aims to improve user satisfaction by allowing them to easily find the most suitable software based on their interests and personality.

[0192] Example of a prompt:

[0193] Please describe a system that takes user input information about their areas of interest and personality, and then recommends appropriate applications based on that information.

[0194] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0195] Step 1:

[0196] User input

[0197] Users open a dedicated application or web interface using a device such as a smartphone or PC. The user interface displays forms for entering information about their areas of interest and personality. For example, the user might enter "reading" and "introverted."

[0198] Input: User information about areas of interest and personality.

[0199] Process: The user enters information into a form on their device.

[0200] Output: Input data is retained on the terminal.

[0201] Step 2:

[0202] Data transmission from the device

[0203] The terminal formats the data entered by the user into JSON format. The JSON-formatted data is then sent to the server using the HTTPS protocol. For example, the data is sent in the following format:

[0204] json

[0205] {

[0206] "interest": "reading",

[0207] "personality": "introverted"

[0208] }

[0209] Input: User input data

[0210] Processing: Convert input data to JSON format and send it to the server via HTTPS.

[0211] Output: Data sent as an HTTP request to the server

[0212] Step 3:

[0213] Server Data Analysis

[0214] The server parses the received JSON data and extracts the user's areas of interest (e.g., "reading") and personality traits (e.g., "introverted"). A JSON parser library is used for this analysis.

[0215] Input: JSON data sent from the device

[0216] Processing: Analyze the data using a JSON parser library and extract areas of interest and personality traits.

[0217] Output: Analyzed areas of interest and personality data

[0218] Step 4:

[0219] Server application selection

[0220] The server searches the database and selects the most suitable software based on the user's input data. The database contains software information categorized by areas of interest and personality tags. For example, it searches for software tagged with "reading" and "introverted."

[0221] Input: Extracted areas of interest and personality data

[0222] Process: Execute database queries and search for software based on tags.

[0223] Output: List of applicable software

[0224] Step 5:

[0225] Server result generation

[0226] The server generates a list of recommended software from the search results. This list includes the software name, description, and download link. The generated list is then converted back into JSON format and sent to the terminal.

[0227] Input: Software list from search results

[0228] Processing: Format the recommended software list into JSON format and send it to the terminal.

[0229] Output: Recommended software list in JSON format

[0230] Step 6:

[0231] Terminal display

[0232] The terminal parses the JSON data received from the server and displays a list of recommended software in the user interface. The user can browse this list, identify the necessary software, and click the download link to install it.

[0233] Input: JSON data received from the server

[0234] Processing: The data is parsed using a JSON parser library and displayed in the user interface.

[0235] Output: Recommended software list displayed in the user interface

[0236] Through these steps, users can easily find the optimal software based on their interests and personality, leading to increased satisfaction.

[0237] (Application Example 1)

[0238] 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."

[0239] Traditional security measures have been uniform, failing to adequately provide personalized information tailored to individual user interests and personalities. Furthermore, limited means of providing real-time security information instantly made it difficult for users to obtain necessary information immediately. Therefore, there is a need for a personalized and rapid security information delivery system that enables users to conduct their daily activities more safely.

[0240] 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.

[0241] In this invention, the server includes means for providing personalized security measures based on user input information, means including a smart device for providing security information visually in real time, and means for analysis means for tagging and matching software based on the user's areas of interest and personality. This enables the user to obtain optimal security measures tailored to their own characteristics in real time.

[0242] "Means for inputting information" refers to the means by which users input data about their areas of interest and personality.

[0243] "Means for sending information to the server" refers to the means for sending entered user information to the server.

[0244] "Means for analyzing received information" refers to the means by which a server analyzes received data to identify the user's areas of interest and personality.

[0245] "A method for selecting the optimal software from a database" refers to a method for searching a database based on analyzed information and selecting the most suitable software for the user.

[0246] "Means for transmitting information about selected software to a terminal" refers to the means for transmitting information about selected software to the user's terminal.

[0247] "Means for displaying transmitted software information to the user" refers to means for displaying transmitted software information on the user's terminal.

[0248] "Means of providing personalized security measures" refers to means of providing individualized security measures based on user input information.

[0249] A "smart device that provides security information visually in real time" is a smart device that provides security-related information to users visually in real time.

[0250] "Analysis means" refers to a means of tagging and matching software based on the user's areas of interest and personality.

[0251] This invention is a system that allows users to input information about their areas of interest and personality, and then provides appropriate security measures based on that information. The following describes embodiments for carrying out this invention.

[0252] First, users input information about their areas of interest and personality via devices such as smart glasses or smartphones. This information is formatted digitally and sent to the server via a secure protocol. For example, if a user inputs "jogging" and "highly cautious," this information is sent to the server in JSON or XML format.

[0253] The server analyzes the received information to identify the user's areas of interest and personality. This analysis is performed using a pre-trained generative AI model. Based on the analysis results, the server selects appropriate security measures and related software from its database. This database stores various security measures and software information and is tagged, allowing for quick matching.

[0254] The selected security measures and software information are converted back into JSON or XML format and sent to the device. The device analyzes the received information and displays it visually to the user. When using smart glasses, security information is provided visually in real time. For example, while the user is jogging, a warning might appear saying, "Crime has been increasing in this area recently, please choose a different route."

[0255] This system will allow users to receive personalized security information in real time, based on their interests and personality. This is expected to improve user safety and increase user satisfaction.

[0256] As a concrete example, the following is an example of a prompt message when a user enters "jogging" as an area of ​​interest and "cautious" as a personality trait:

[0257] "The user's interest is jogging, and their personality is cautious. Please recommend an application that provides the most suitable security measures for them in real time."

[0258] As described above, the present invention is a system that provides optimal security measures based on the user's interests and personality, and is extremely effective in improving user safety.

[0259] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0260] Step 1:

[0261] Users input information about their areas of interest and personality using devices such as smart glasses or smartphones.

[0262] Input: User's areas of interest and personality information (e.g., "Jogging", "Highly cautious")

[0263] Output: User information formatted in JSON or XML format.

[0264] Operation: The user enters data into each field through the application interface, and this data is converted into a digital format.

[0265] Step 2:

[0266] The terminal sends formatted user information to the server via a secure protocol.

[0267] Input: Formatted user information

[0268] Output: HTTP request sent to the server

[0269] Operation: The terminal software converts user information into JSON or XML format and sends it to the server using a secure protocol (e.g., HTTPS).

[0270] Step 3:

[0271] The server analyzes the received user information to identify the user's areas of interest and personality.

[0272] Input: User information received by the server (in JSON or XML format)

[0273] Output: Analyzed user information (areas of interest and personality)

[0274] Operation: The server software uses a generated AI model (e.g., a model built with Scikit - learn) to analyze the user information and identify the areas of interest and personality.

[0275] Step 4:

[0276] The server selects appropriate security measures and related software from the database based on the analyzed information.

[0277] Input: Analyzed user information (areas of interest and personality)

[0278] Output: List of optimal security measures and related software

[0279] Operation: The server's database search function searches for tagged security measures and software information and identifies items that match the areas of interest and personality.

[0280] Step 5: <​​​​​​​​​​​​​​​​ Step 6:

[0286] The terminal analyzes the received security measures and software information and visually displays it to the user.

[0287] Input: Information received in JSON or XML format

[0288] Output: Security information and software displayed on the user interface

[0289] Operation: The terminal software analyzes the received data and displays it on the screen of smart glasses or a smartphone. For example, when the user is jogging, a message such as "This area has recently seen an increase in crime. Please choose another route." is displayed.

[0290] Through the above steps, the user can obtain appropriate security measures in real time based on their interests and personality.

[0291] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions.

[0292] This invention combines an emotion engine with a system that inputs information related to the fields and personality that the user is interested in and recommends appropriate applications based on that information. Hereinafter, specific embodiments of this system will be described.

[0293] 1. User Input

[0294] The user uses a smartphone or other terminal to input information related to the fields and personality that they are interested in through a dedicated application or web interface. For example, it is conceivable that the user inputs information such as "music" and "likes adventure".

[0295] 2. Emotional Engine

[0296] The terminal is equipped with a microphone and a camera for collecting the user's voice and facial expression data. The emotional engine collects this data and analyzes the user's emotions in real time. For example, when the user is speaking with a smiling face, the emotional engine identifies the emotion of "joy".

[0297] 3. Transmission Means of the Terminal

[0298] The terminal formats the information input by the user and the result of the emotion analysis obtained from the emotional engine into JSON format and sends it to the server as an HTTP request. The user's input data and emotion analysis data are protected by a secure protocol.

[0299] 4. Analysis Means of the Server

[0300] The server analyzes the JSON data received from the terminal. For example, it obtains the following data:

[0301] json

[0302] {

[0303] "interest": "music",

[0304] "personality": "liking adventure",

[0305] "emotion": "joy"

[0306] }

[0307] The server analyzes this data to identify the user's areas of interest, personality, and emotions.

[0308] 5. Selection Means of the Server

[0309] The server searches the database for application information and selects the most suitable application based on user input and sentiment analysis results. The database is categorized by application areas of interest, personality, and sentiment tags.

[0310] For example, search for applications tagged with "music," "adventure," and "joy." The applications found in this step might include the latest adventure music apps or apps for participating in live music events.

[0311] 6. Server result generation means

[0312] The server generates a list of appropriate applications from the search results. This list includes detailed information such as the application name, description, and download link.

[0313] The generated list is converted back to JSON format and sent to the terminal.

[0314] 7. Display methods for the terminal

[0315] The terminal analyzes application information received from the server and displays it on the user interface. Users can view a list of recommended applications and check detailed information.

[0316] Specific example

[0317] 1. User input

[0318] The user opens the application on their device and enters their area of ​​interest, "Music," and their personality, "Adventurous."

[0319] 2. Analysis of the Emotion Engine

[0320] While the user is inputting, the emotion engine analyzes their voice and facial expressions to detect if the user is experiencing the emotion of "joy."

[0321] 3. Sending from the device

[0322] The terminal formats the input data and sentiment analysis results as follows and sends them to the server:

[0323] json

[0324] {

[0325] "interest": "music",

[0326] "personality": "adventurous",

[0327] "emotion": "joy"

[0328] }

[0329] 4. Server analysis

[0330] The server performs analysis and extracts "music," "adventure," and "joy" from the user's data.

[0331] 5. Server Selection

[0332] The server searches the database and finds the relevant application. For example, "Adventure Music App" might be the relevant entry.

[0333] 6. Generating Results

[0334] The server generates a list of found applications and sends it to the terminal in the following format:

[0335] json

[0336] {

[0337] "recommendations": [

[0338] {

[0339] "name": "Adventure Music App",

[0340] "Description": "An app for enjoying the latest adventure music."

[0341] "link": "http: / / example.com / app1"

[0342] },

[0343] {

[0344] "name": "Live music event participation app",

[0345] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[0346] "link": "http: / / example.com / app2"

[0347] }

[0348] ]

[0349] }

[0350] 7. Display on the device

[0351] The device analyzes the received information and displays details about the "Adventure Music App" and the "Live Music Event Participation App" to the user. The user can read the application description and click the download link to install the application.

[0352] This system aims to improve user satisfaction by making it easy for users to find the most suitable applications based on their interests, personality, and emotions.

[0353] The following describes the processing flow.

[0354] Step 1:

[0355] The user enters information about their areas of interest and personality. For example, the user might use a smartphone application to enter information such as "music" and "adventure-loving."

[0356] Step 2:

[0357] The device captures the user's voice and facial expressions in real time. It uses the built-in microphone and camera to collect user emotion data.

[0358] Step 3:

[0359] The emotion engine analyzes the collected voice and facial expression data. For example, the emotion engine analyzes the tone of voice and facial movements to determine that the user's emotion is "joy."

[0360] Step 4:

[0361] The device formats the user's input information and the sentiment engine's analysis results into JSON format. Specifically, it converts the data to the following format:

[0362] json

[0363] {

[0364] "interest": "music",

[0365] "personality": "adventurous",

[0366] "emotion": "joy"

[0367] }

[0368] Step 5:

[0369] The device formats the JSON data and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for transmission.

[0370] Step 6:

[0371] The server receives an HTTP request and parses the JSON data. As a result of the parsing, the server extracts the information "music," "adventure," and "joy."

[0372] Step 7:

[0373] The server queries the database based on the information it extracts. This query includes searching for applications tagged with "music," "adventure," and "joy."

[0374] Step 8:

[0375] The server analyzes the query results and generates a list of applications best suited to the user's interests, personality, and emotions. For example, the following applications might be selected:

[0376] Adventure Music App

[0377] Live music event participation app

[0378] Step 9:

[0379] The application list generated by the server is converted back into JSON format and sent to the terminal. The JSON data will be in the following format:

[0380] json

[0381] {

[0382] "recommendations": [

[0383] {

[0384] "name": "Adventure Music App",

[0385] "Description": "An app for enjoying the latest adventure music."

[0386] "link": "http: / / example.com / app1"

[0387] },

[0388] {

[0389] "name": "Live music event participation app",

[0390] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[0391] "link": "http: / / example.com / app2"

[0392] }

[0393] ]

[0394] }

[0395] Step 10:

[0396] The terminal parses the JSON data received from the server. Based on the analysis results, it prepares to display information about recommended applications in the user interface.

[0397] Step 11:

[0398] The device displays an application list to the user through its user interface. The user can view details of the recommended applications and obtain them using the download links.

[0399] This detailed process allows users to easily find the optimal application based on their interests, personality, and emotions.

[0400] (Example 2)

[0401] 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".

[0402] Traditional recommendation systems are limited to recommending applications based on user interests and personality traits, lacking recommendations that take user emotions into account. This resulted in users not receiving recommendations that matched their current emotional state, making it difficult to improve user satisfaction.

[0403] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting information about the user's areas of interest and personality, means for collecting the input information for analysis, and means for analyzing the collected data in real time and identifying the user's emotions. This makes it possible to recommend the most suitable application based on the user's interests, personality, and real-time emotion analysis.

[0404] A "user" refers to an individual who uses the system to input information about their areas of interest and personality, and receives recommendations for applications.

[0405] "Areas of interest" refers to the categories or themes that the user is interested in.

[0406] "Personality" refers to a user's behavioral patterns and psychological characteristics, and is used in systems to capture the user's preferences.

[0407] "Means of inputting information" refers to interfaces or devices that allow users to provide data about their interests and personality to a system.

[0408] "Means of collecting information for analysis" refers to devices and systems that collect user-input data internally and further collect real-time sentiment data.

[0409] "Means of identifying emotions" refers to algorithms and devices that analyze collected data such as voice and facial expressions to identify the user's current emotional state.

[0410] A "server" refers to a computer system that receives information and sentiment analysis results entered by users, and then analyzes and processes them.

[0411] A "database" refers to a storage device or system used to store and manage application information that corresponds to a user's areas of interest, personality, and emotions.

[0412] "Means for selecting the optimal software" refers to algorithms and devices that allow a server to select the most suitable application from a database based on user input information and sentiment analysis results.

[0413] "Means for transmitting software information to a terminal" refers to communication methods and protocols for transmitting detailed information about a selected application to the user's terminal.

[0414] "Means for displaying software information" refers to interfaces or devices that visually present and display detailed information about applications received on a user's terminal.

[0415] "Tagging" refers to the technique of assigning specific categories or attributes to applications to facilitate organization and searching.

[0416] A "list" refers to a format that compiles information on multiple selected applications into a single entity.

[0417] "Detailed information" refers to supplementary information that helps users understand the application, such as the application's name, description, and download link.

[0418] Specific embodiments of this invention will now be described. The program of this system takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Furthermore, by combining it with an emotion engine, it also provides recommendations based on the user's emotions.

[0419] First, users use a device such as a smartphone or PC to input information about their areas of interest and personality through a dedicated application or web interface. For example, a user might input information such as "music" and "adventure-loving."

[0420] Next, the device is equipped with a microphone and camera, which collect voice and facial expression data while the user is entering information. The emotion engine analyzes this data in real time to identify the user's emotions. For example, if the user is smiling while speaking, the emotion engine will identify the emotion as "joy."

[0421] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for this. The server parses the received JSON data to identify the user's areas of interest, personality, and emotions. For example, it might parse JSON data like the following:

[0422] json

[0423] {

[0424] "interest": "music",

[0425] "personality": "adventurous",

[0426] "emotion": "joy"

[0427] }

[0428] Next, the server searches the database and selects the most suitable application based on the user's input information and sentiment analysis results. The database categorizes applications by interest, personality, and sentiment tags. For example, it searches for applications tagged with "music," "adventure," and "joy." At this point, applications such as "adventure music app" or "live music event participation app" may be selected.

[0429] The server generates a list of suitable applications from the search results, converts this list to JSON format, and sends it to the terminal. The list includes detailed information such as the application name, description, and download link. The terminal parses the received application information and displays it in the user interface. The user can browse the list of recommended applications and view detailed information. This allows the user to easily find the best application based on their interests, personality, and real-time emotions.

[0430] As a concrete example, the user opens an application on their device and enters their area of ​​interest, "music," and their personality, "adventurous." While the user is entering the information, the emotion engine analyzes their voice and facial expressions and detects that the user is experiencing the emotion of "joy." The device formats the input data and emotion analysis results and sends them to the server. The server performs the analysis and retrieves "music," "adventurous," and "joy" from the user's data. The server searches its database and finds the corresponding "adventure music app." The server generates a list of these apps and sends it to the device. The device displays the received information to the user, who can then review the details and install the application.

[0431] Examples of prompt statements include the following forms:

[0432] "Users use their smartphones to input information about their interests and personality, and an emotion engine analyzes their emotions in real time. For example, if they input 'music' and 'adventure,' it will indicate a feeling of joy. The device then sends the input data and analysis results to a server, which selects and recommends the most suitable applications to the user."

[0433] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0434] Step 1:

[0435] The system uses a means for users to input information about their areas of interest and personality. Specifically, users enter information such as "music" or "adventure-loving" into input fields on their smartphone or PC. The entered information is then passed to the system (input data: areas of interest, personality).

[0436] Step 2:

[0437] The device collects the input information for analysis. In this process, it uses its microphone and camera to collect the user's voice and facial expression data. For example, suppose the camera captures a scene where the user is smiling and talking while inputting data (input data: areas of interest, personality, voice data, facial expression data).

[0438] Step 3:

[0439] The emotion engine built into the device analyzes collected voice and facial expression data in real time to identify the user's emotions. Specifically, it uses an emotion recognition algorithm to identify emotions such as "joy" from voice tone and facial expressions (input data: voice data, facial expression data; output data: emotion).

[0440] Step 4:

[0441] The device formats the user's entered areas of interest and personality information, along with the sentiment analysis results, into JSON format. For example, it might be formatted as follows:

[0442] json

[0443] {

[0444] "interest": "music",

[0445] "personality": "adventurous",

[0446] "emotion": "joy"

[0447] }

[0448] Then, this JSON data is sent to the server as a secure HTTP request (input data: areas of interest, personality, emotions; output data: JSON data).

[0449] Step 5:

[0450] The server parses the received JSON data. Specifically, the server parses the received data, stores each part in an internal variable, and records it in the debug log (input data: JSON data, output data: areas of interest, personality, emotions).

[0451] Step 6:

[0452] The server searches the database based on the analyzed interests, personality, and emotions to select the most suitable software. For example, it might execute a database query to find applications that match "music," "adventurous," and "joy" (input data: interests, personality, emotions; output data: software list).

[0453] Step 7:

[0454] The server generates a list of the found software and converts it into JSON format as a list containing detailed descriptions. For example, it may look like this:

[0455] json

[0456] {

[0457] "recommendations": [

[0458] {

[0459] "name": "Adventure Music App",

[0460] "Description": "An app for enjoying the latest adventure music."

[0461] "link": "http: / / example.com / app1"

[0462] },

[0463] {

[0464] "name": "Live music event participation app",

[0465] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[0466] "link": "http: / / example.com / app2"

[0467] }

[0468] ]

[0469] }

[0470] Then, this JSON data is sent to the terminal as an HTTP response (input data: software list, output data: JSON data).

[0471] Step 8:

[0472] The terminal parses the received JSON data and displays it on the user interface. Specifically, it visually presents the application name, description, and download link (input data: JSON data, output data: user interface display). Based on the displayed information, the user can check detailed information and install the application by clicking the download link.

[0473] (Application Example 2)

[0474] 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 device 14 will be referred to as the "terminal."

[0475] Traditional content recommendation systems primarily rely on user interests and personality traits, and none have taken real-time emotions into account. Therefore, they fail to recommend content that matches the user's current emotional state, resulting in low user satisfaction.

[0476] 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.

[0477] In this invention, the server includes means for inputting information about the user's areas of interest and personality; means for collecting emotional data in real time using an emotional engine that analyzes the input information and the user's emotions; means for transmitting the input information and emotional data to the server; means for the server to analyze the received information and select the most suitable content from a database; means for transmitting information about the selected content to a terminal; and means for displaying the transmitted content information to the user. This enables real-time content recommendations that take the user's emotions into account.

[0478] "User" refers to consumers or users who use the system to input information about their areas of interest and personality.

[0479] "Areas of interest" refers to specific categories or themes that the user is interested in.

[0480] "Personality" refers to a user's personal characteristics and preferences.

[0481] An "emotion engine" refers to a technology that analyzes a user's voice and facial expression data to identify their emotions in real time.

[0482] "Emotional data" refers to information that quantifies or stringifies the user's emotional state as analyzed by the emotion engine.

[0483] A "server" refers to a computer system that receives and analyzes information sent by users.

[0484] A "database" refers to a storage device or system in which a server stores information about applications and content.

[0485] "Content" refers to information and media that users can enjoy, such as movies, music, videos, and podcasts.

[0486] "Recommendation" refers to the act of selecting and presenting the most suitable content based on the user's areas of interest, personality, and emotional data.

[0487] A "terminal" refers to a device used by a user to input information, such as a smartphone or smart glasses.

[0488] "Display" refers to the act of visually presenting content or recommendation results on a device's screen.

[0489] This invention is a system that recommends optimal content based on the user's areas of interest, personality, and real-time sentiment data. The system provides means for the user to input information about their areas of interest and personality, and for collecting and analyzing sentiment data using a sentiment engine.

[0490] System-wide configuration

[0491] 1. User input means

[0492] Users input information about their interests and personality through a dedicated application using devices such as smartphones or smart glasses. For example, a user might input "horror movies" and "adventure lover."

[0493] 2. Collection and analysis of emotional data using an emotion engine

[0494] The emotion engine uses the microphone and camera built into the device to collect the user's voice and facial expressions, and analyzes their emotions in real time. For example, it can detect the emotion of "excitement."

[0495] 3. Transmission method

[0496] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. This step uses a secure protocol to protect the data.

[0497] 4. Server-based analysis and selection methods

[0498] The server analyzes the received JSON data to identify the user's areas of interest, personality, and emotions. Based on this data, the server searches a database and selects the most suitable content based on the user's input and the emotion analysis results. For example, "horror adventure movies" or "adventure podcasts."

[0499] 5. Result generation and transmission means

[0500] The server generates a list of relevant content from the search results, converts it back to JSON format, and sends it to the terminal. The generated list includes detailed information such as the content name, description, and links.

[0501] 6. Display means

[0502] The terminal analyzes content information received from the server and displays it on the user interface. Users can view a list of recommended content and check detailed information.

[0503] Hardware and software to be used

[0504] Hardware:

[0505] The devices include smartphones and smart glasses. These devices are equipped with microphones and cameras and are used to collect emotional data.

[0506] software:

[0507] The frontend uses React to build the user interface, while the backend uses Node.js and Express for server-side processing. Additionally, an emotion engine analyzes speech and facial expressions, utilizing image recognition and natural language processing algorithms.

[0508] Explanation of specific examples

[0509] For example, if a user enters "horror movies" and "adventure lover" through a smartphone app, and the sentiment analysis identifies this as "excited," that information will be sent to the server in the following JSON format:

[0510] json

[0511] {

[0512] "interest": "Horror movies",

[0513] "personality": "adventurous",

[0514] "emotion": "excitement"

[0515] }

[0516] The server analyzes this data and selects content such as "horror adventure movies" and "adventure podcasts" from the database. This result is sent to the device and displayed visually to the user.

[0517] Example of a prompt

[0518] A user entered "horror movies" and "adventure" through a smartphone app, and sentiment analysis identified their mood as "excited." Please use this data to recommend appropriate content. For example, we expect responses like the following:

[0519] Horror Adventure Movie: An exciting film where horror and adventure intertwine.

[0520] Adventure Podcasts: Podcasts that will awaken your adventurous spirit.

[0521] As a result, users can smoothly find content that suits their interests and personality, while also taking their real-time emotions into consideration.

[0522] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0523] Step 1:

[0524] The user opens the smartphone app and enters their areas of interest (e.g., "horror movies") and personality traits (e.g., "adventurous"). The data entered at this point is information about the user's interests and personality.

[0525] Step 2:

[0526] As the user completes their input, the device's emotion engine analyzes their voice and facial expressions to identify their real-time emotions (e.g., "excitement"). This analysis is performed using an emotion analysis algorithm based on the collected audio and video data. The output data is then tagged with emotion tags.

[0527] Step 3:

[0528] The terminal formats the user's input information on areas of interest and personality, along with the sentiment data analyzed by the sentiment engine, into JSON format and sends it to the server using an HTTP POST request. The input data consists of the user's interests, personality, and sentiment, while the output data is a request in JSON format.

[0529] Step 4:

[0530] The server receives JSON data sent from the terminal. It parses the received input data and divides it into individual data items (interests, personality, emotions). The output data consists of these parsed data items.

[0531] Step 5:

[0532] The server searches the database based on the analyzed data items and selects the most suitable content that matches the user's interests, personality, and emotions. This selection uses a database where content information is pre-tagged. The input data consists of segmented data items, and the output data is a list of recommended content.

[0533] Step 6:

[0534] The server generates a list of selected content, converts it back into JSON format, and sends it to the terminal. This list includes content names, descriptions, links, etc. The input data is the recommended content list, and the output data is a JSON response.

[0535] Step 7:

[0536] The terminal parses the received JSON-formatted content information and displays it on the user interface. Based on this displayed information, the user can select content and view detailed information. The input data is a JSON-formatted response, while the output data is a visually represented content information.

[0537] 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.

[0538] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0539] 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.

[0540] [Second Embodiment]

[0541] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0542] 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.

[0543] 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).

[0544] 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.

[0545] 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.

[0546] 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).

[0547] 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.

[0548] 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.

[0549] 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.

[0550] 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.

[0551] 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.

[0552] 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".

[0553] This invention relates to a system that takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Specific embodiments of this system are described below.

[0554] 1. User input

[0555] Users use smartphones or other devices to input information about their areas of interest and personality through a dedicated application or web interface. For example, consider a case where a user inputs information such as "reading" and "introverted."

[0556] 2. Transmission method of the terminal

[0557] The terminal formats the information entered by the user into JSON or XML format and sends it to the server as an HTTP request. User input data is protected by a secure protocol.

[0558] 3. Server analysis methods

[0559] The server parses the JSON data received from the terminal. For example, it retrieves data like the following:

[0560] json

[0561] {

[0562] "interest": "reading",

[0563] "personality": "introverted"

[0564] }

[0565] The server analyzes this data to identify the user's areas of interest and personality.

[0566] 4. Server Selection Methods

[0567] The server searches the database for application information and selects the most suitable application based on the user's input. The database is categorized by application areas of interest and personality tags.

[0568] For example, search for applications tagged with "reading" and "introverted." Applications found in this step might include reading community apps or reading list management apps.

[0569] 5. Server result generation means

[0570] The server generates a list of appropriate applications from the search results. This list includes detailed information such as the application name, description, and download link.

[0571] The generated list is then converted back into JSON or XML format and sent to the terminal.

[0572] 6. Display methods for the terminal

[0573] The terminal analyzes application information received from the server and displays it on the user interface. Users can view a list of recommended applications and check detailed information.

[0574] Specific example

[0575] 1. User input

[0576] The user opens the application on their device and enters their area of ​​interest, "reading," and their personality type, "introverted."

[0577] 2. Sending from the device

[0578] The terminal formats the input data as follows and sends it to the server:

[0579] json

[0580] {

[0581] "interest": "reading",

[0582] "personality": "introverted"

[0583] }

[0584] 3. Server analysis

[0585] The server performs analysis and extracts "reading" and "introversion" from the user's data.

[0586] 4. Server Selection

[0587] The server searches the database and finds the relevant application. For example, "reading community app" might be the relevant one.

[0588] 5. Generating the results

[0589] The server generates a list of found applications and sends it to the terminal in the following format:

[0590] json

[0591] {

[0592] "recommendations": [

[0593] {

[0594] "name": "Reading community app",

[0595] "Description": "An app that allows you to connect with people who love reading."

[0596] "link": "http: / / example.com / app1"

[0597] }

[0598] ]

[0599] }

[0600] 6. Display on the device

[0601] The device analyzes the received information and displays details about the "Reading Community App" to the user. The user can read the application description and click the download link to install the application.

[0602] This system aims to improve user satisfaction by allowing users to easily find the most suitable applications based on their interests and personality.

[0603] The following describes the processing flow.

[0604] Step 1:

[0605] The user enters information about their areas of interest and personality. For example, the user might use a smartphone application to enter information such as "sports" and "sociable."

[0606] Step 2:

[0607] The terminal formats the user's input information into JSON format. Specifically, it converts it to the following data format:

[0608] json

[0609] {

[0610] "interest": "sports",

[0611] "personality": "social"

[0612] }

[0613] Step 3:

[0614] The device formats the JSON data and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for transmission.

[0615] Step 4:

[0616] The server receives an HTTP request and parses the JSON data. The analysis extracts the information "sports" and "sociable."

[0617] Step 5:

[0618] The server queries the database based on the information it extracts. The query includes searching for applications tagged with "sports" and "sociable".

[0619] Step 6:

[0620] The server analyzes the query results and generates a list of applications best suited to the user's interests and personality. For example, the following applications might be selected:

[0621] Sports event participation app

[0622] Team sports matching app

[0623] Step 7:

[0624] The application list generated by the server is converted back into JSON format and sent to the terminal. The JSON data will be in the following format:

[0625] json

[0626] {

[0627] "recommendations": [

[0628] {

[0629] "name": "Sports event participation app",

[0630] "Description": "An app that makes it easy to participate in sports events held in your neighborhood."

[0631] "link": "http: / / example.com / app1"

[0632] },

[0633] {

[0634] "name": "Team Sports Matching App",

[0635] "Description": "An app that allows you to match with people who share the same interest in the same sport and form a team."

[0636] "link": "http: / / example.com / app2"

[0637] }

[0638] ]

[0639] }

[0640] Step 8:

[0641] The terminal parses the JSON data received from the server. Based on the analysis results, it prepares to display information about recommended applications in the user interface.

[0642] Step 9:

[0643] The device displays an application list to the user through its user interface. The user can view details of the recommended applications and obtain them using the download links.

[0644] This process makes it easy for users to find applications that perfectly match their interests and personality.

[0645] (Example 1)

[0646] 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".

[0647] Traditional application recommendation systems have struggled to effectively provide users with appropriate applications that are sufficiently based on their interests and personalities. In particular, it takes considerable time and effort for users to find the best fit from a vast number of applications. There is a need for a system that can solve this problem and provide users with the most suitable applications quickly and efficiently.

[0648] 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.

[0649] In this invention, the server includes means for inputting information about the user's areas of interest and personality; means for converting the input information into a data format and transmitting it to the server; means for the server to analyze the received information and select the most suitable software from a database based on the user's areas of interest and personality; means for generating a list of selected software, converting it into a data format including detailed information and transmitting it to a terminal; and means for displaying the transmitted software information to the user. This enables the user to quickly and accurately find applications that match their interests and personality.

[0650] "User" refers to an individual or group that uses a computer system or digital service.

[0651] "Areas of interest" refers to themes and topics that users are interested in and in which they gather information and engage in activities.

[0652] "Personality" refers to psychological attributes that indicate an individual's tendencies in behavior and thinking.

[0653] "Means of input" refers to the devices or interfaces that users use to provide information.

[0654] "Terminal" refers to an electronic device (e.g., smartphone, PC) that a user uses to input and receive information.

[0655] "Converting to a data format" refers to the act of changing information into a structured format (e.g., JSON, XML) that follows certain rules.

[0656] A "server" refers to a computer system that receives and processes requests from users.

[0657] "Analyzing received information" refers to the act of a server reading data sent by a user, understanding its contents, and processing it.

[0658] A "database" refers to a system for efficiently storing and retrieving information.

[0659] "Selecting software" refers to the act of choosing the most suitable application based on specified criteria.

[0660] "Software" refers to a computer program that runs on an electronic device and provides a specific function.

[0661] "Generating a list" refers to the act of organizing selected items (e.g., applications) into a list format.

[0662] "Detailed information" refers to additional and specific data (e.g., name, description, link) related to the selected item (e.g., software).

[0663] "Converting to a data format" refers to the act of structuring information into a different, defined format.

[0664] "To display" refers to the act of visually presenting information through the user interface of a device.

[0665] This invention relates to a system that takes user information about their areas of interest and personality and recommends appropriate software based on that information. Specific embodiments of this system are described below.

[0666] 1. User input

[0667] Users open a dedicated application or web interface using a device such as a smartphone or PC. The user interface displays forms for entering information about their areas of interest and personality. For example, the user might enter "reading" and "introverted."

[0668] 2. Data transmission from the terminal

[0669] The terminal formats the data entered by the user into JSON format. The formatted data is then sent to the server using the HTTPS protocol. For example, the data is sent as follows:

[0670] json

[0671] {

[0672] "interest": "reading",

[0673] "personality": "introverted"

[0674] }

[0675] 3. Server data analysis

[0676] The server parses the received JSON data and extracts the user's areas of interest (e.g., "reading") and personality traits (e.g., "introverted"). A JSON parser library is used for this analysis.

[0677] 4. Server application selection

[0678] The server searches the database and selects the most suitable software based on the user's input data. The database contains software information categorized by areas of interest and personality tags. For example, it searches for software tagged with "reading" and "introverted."

[0679] 5. Server result generation

[0680] The server generates a list of recommended software from the search results. This list includes the software name, description, and download link. The generated list is then converted back into JSON format and sent to the terminal.

[0681] 6. Display on the device

[0682] The terminal parses the JSON data received from the server and displays a list of recommended software in the user interface. The user can view detailed information about the software and, if necessary, click the download link to install it.

[0683] Specific example:

[0684] 1. User input

[0685] The user opens the application on their smartphone and enters their area of ​​interest, "reading," and their personality type, "introverted."

[0686] 2. Sending from the device

[0687] The terminal formats the input data into JSON format and sends it to the server:

[0688] {

[0689] "interest": "reading",

[0690] "personality": "introverted"

[0691] }

[0692] 3. Server analysis

[0693] The server performs analysis and extracts "reading" and "introversion" from the user's data.

[0694] 4. Server Selection

[0695] The server searches the database and finds software tagged as "reading" and "introverted."

[0696] 5. Generating the results

[0697] The server generates a list of the found software and sends it to the terminal in the following format:

[0698] {

[0699] "recommendations": [

[0700] {

[0701] "name": "Reading community app",

[0702] "Description": "An app that allows you to connect with people who love reading."

[0703] "link": "http: / / example.com / app1"

[0704] }

[0705] ]

[0706] }

[0707] 6. Display on the device

[0708] The device analyzes the received information and displays details about the "Reading Community App" to the user. The user can then read the application description and click the download link to install the application.

[0709] This system aims to improve user satisfaction by allowing them to easily find the most suitable software based on their interests and personality.

[0710] Example of a prompt:

[0711] Please describe a system that takes user input information about their areas of interest and personality, and then recommends appropriate applications based on that information.

[0712] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0713] Step 1:

[0714] User input

[0715] Users open a dedicated application or web interface using a device such as a smartphone or PC. The user interface displays forms for entering information about their areas of interest and personality. For example, the user might enter "reading" and "introverted."

[0716] Input: User information about areas of interest and personality.

[0717] Process: The user enters information into a form on their device.

[0718] Output: Input data is retained on the terminal.

[0719] Step 2:

[0720] Data transmission from the device

[0721] The terminal formats the data entered by the user into JSON format. The JSON-formatted data is then sent to the server using the HTTPS protocol. For example, the data is sent in the following format:

[0722] json

[0723] {

[0724] "interest": "reading",

[0725] "personality": "introverted"

[0726] }

[0727] Input: User input data

[0728] Processing: Convert input data to JSON format and send it to the server via HTTPS.

[0729] Output: Data sent as an HTTP request to the server

[0730] Step 3:

[0731] Server Data Analysis

[0732] The server parses the received JSON data and extracts the user's areas of interest (e.g., "reading") and personality traits (e.g., "introverted"). A JSON parser library is used for this analysis.

[0733] Input: JSON data sent from the device

[0734] Processing: Analyze the data using a JSON parser library and extract areas of interest and personality traits.

[0735] Output: Analyzed areas of interest and personality data

[0736] Step 4:

[0737] Server application selection

[0738] The server searches the database and selects the most suitable software based on the user's input data. The database contains software information categorized by areas of interest and personality tags. For example, it searches for software tagged with "reading" and "introverted."

[0739] Input: Extracted areas of interest and personality data

[0740] Process: Execute database queries and search for software based on tags.

[0741] Output: List of applicable software

[0742] Step 5:

[0743] Server result generation

[0744] The server generates a list of recommended software from the search results. This list includes the software name, description, and download link. The generated list is then converted back into JSON format and sent to the terminal.

[0745] Input: Software list from search results

[0746] Processing: Format the recommended software list into JSON format and send it to the terminal.

[0747] Output: Recommended software list in JSON format

[0748] Step 6:

[0749] Terminal display

[0750] The terminal parses the JSON data received from the server and displays a list of recommended software in the user interface. The user can browse this list, identify the necessary software, and click the download link to install it.

[0751] Input: JSON data received from the server

[0752] Processing: The data is parsed using a JSON parser library and displayed in the user interface.

[0753] Output: Recommended software list displayed in the user interface

[0754] Through these steps, users can easily find the optimal software based on their interests and personality, leading to increased satisfaction.

[0755] (Application Example 1)

[0756] 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."

[0757] Traditional security measures have been uniform, failing to adequately provide personalized information tailored to individual user interests and personalities. Furthermore, limited means of providing real-time security information instantly made it difficult for users to obtain necessary information immediately. Therefore, there is a need for a personalized and rapid security information delivery system that enables users to conduct their daily activities more safely.

[0758] 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.

[0759] In this invention, the server includes means for providing personalized security measures based on user input information, means including a smart device for providing security information visually in real time, and means for analysis means for tagging and matching software based on the user's areas of interest and personality. This enables the user to obtain optimal security measures tailored to their own characteristics in real time.

[0760] "Means for inputting information" refers to the means by which users input data about their areas of interest and personality.

[0761] "Means for sending information to the server" refers to the means for sending entered user information to the server.

[0762] "Means for analyzing received information" refers to the means by which a server analyzes received data to identify the user's areas of interest and personality.

[0763] "A method for selecting the optimal software from a database" refers to a method for searching a database based on analyzed information and selecting the most suitable software for the user.

[0764] "Means for transmitting information about selected software to a terminal" refers to the means for transmitting information about selected software to the user's terminal.

[0765] "Means for displaying transmitted software information to the user" refers to means for displaying transmitted software information on the user's terminal.

[0766] "Means of providing personalized security measures" refers to means of providing individualized security measures based on user input information.

[0767] A "smart device that provides security information visually in real time" is a smart device that provides security-related information to users visually in real time.

[0768] "Analysis means" refers to a means of tagging and matching software based on the user's areas of interest and personality.

[0769] This invention is a system that allows users to input information about their areas of interest and personality, and then provides appropriate security measures based on that information. The following describes embodiments for carrying out this invention.

[0770] First, users input information about their areas of interest and personality via devices such as smart glasses or smartphones. This information is formatted digitally and sent to the server via a secure protocol. For example, if a user inputs "jogging" and "highly cautious," this information is sent to the server in JSON or XML format.

[0771] The server analyzes the received information to identify the user's areas of interest and personality. This analysis is performed using a pre-trained generative AI model. Based on the analysis results, the server selects appropriate security measures and related software from its database. This database stores various security measures and software information and is tagged, allowing for quick matching.

[0772] The selected security measures and software information are converted back into JSON or XML format and sent to the device. The device analyzes the received information and displays it visually to the user. When using smart glasses, security information is provided visually in real time. For example, while the user is jogging, a warning might appear saying, "Crime has been increasing in this area recently, please choose a different route."

[0773] This system will allow users to receive personalized security information in real time, based on their interests and personality. This is expected to improve user safety and increase user satisfaction.

[0774] As a concrete example, the following is an example of a prompt message when a user enters "jogging" as an area of ​​interest and "cautious" as a personality trait:

[0775] "The user's interest is jogging, and their personality is cautious. Please recommend an application that provides the most suitable security measures for them in real time."

[0776] As described above, the present invention is a system that provides optimal security measures based on the user's interests and personality, and is extremely effective in improving user safety.

[0777] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0778] Step 1:

[0779] Users input information about their areas of interest and personality using devices such as smart glasses or smartphones.

[0780] Input: User's areas of interest and personality information (e.g., "Jogging", "Highly cautious")

[0781] Output: User information formatted in JSON or XML format.

[0782] Operation: The user enters data into each field through the application interface, and this data is converted into a digital format.

[0783] Step 2:

[0784] The terminal sends formatted user information to the server via a secure protocol.

[0785] Input: Formatted user information

[0786] Output: HTTP request sent to the server

[0787] Operation: The terminal software converts user information into JSON or XML format and sends it to the server using a secure protocol (e.g., HTTPS).

[0788] Step 3:

[0789] The server analyzes the received user information to identify the user's areas of interest and personality.

[0790] Input: User information received by the server (in JSON or XML format)

[0791] Output: Analyzed user information (areas of interest and personality)

[0792] Operation: The server software uses a generated AI model (e.g., a model built with Scikit-learn) to analyze user information and identify areas of interest and personality.

[0793] Step 4:

[0794] Based on the analyzed information, the server selects appropriate security measures and related software from the database.

[0795] Input: Analyzed user information (areas of interest and personality)

[0796] Output: List of optimal security measures and related software

[0797] Operation: The server's database search function searches for tagged security measures and software information, identifying items that match the user's areas of interest and personality.

[0798] Step 5:

[0799] The server converts the selected security measures and software information into JSON or XML format and sends it back to the terminal.

[0800] Input: List of optimal security measures and software

[0801] Output: Data in JSON or XML format sent to the terminal.

[0802] Operation: The server software formats the selected security measures and software information and sends it to the terminal as an HTTP response.

[0803] Step 6:

[0804] The device analyzes received security measures and software information and displays it visually to the user.

[0805] Input: Information received in JSON or XML format

[0806] Output: Security information and software displayed on the user interface

[0807] Operation: The terminal software analyzes the received data and displays it on the screen of smart glasses or a smartphone. For example, while a user is jogging, a message might appear saying, "Crime has been increasing in this area recently, please choose a different route."

[0808] Through these steps, users can obtain appropriate security measures in real time based on their interests and personality.

[0809] 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.

[0810] This invention combines an emotion engine with a system that takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Specific embodiments of this system are described below.

[0811] 1. User input

[0812] Users use smartphones or other devices to input information about their interests and personality through a dedicated application or web interface. For example, a user might input information such as "music" and "adventure-loving."

[0813] 2. Emotional Engine

[0814] The device is equipped with a microphone and camera to collect user voice and facial expression data. The emotion engine collects this data and analyzes the user's emotions in real time. For example, if the user is smiling while speaking, the emotion engine identifies the emotion as "joy."

[0815] 3. Transmission method of the terminal

[0816] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. The user's input data and sentiment analysis data are protected by a secure protocol.

[0817] 4. Server analysis methods

[0818] The server parses the JSON data received from the terminal. For example, it retrieves data like the following:

[0819] json

[0820] {

[0821] "interest": "music",

[0822] "personality": "adventurous",

[0823] "emotion": "joy"

[0824] }

[0825] The server analyzes this data to identify the user's areas of interest, personality, and emotions.

[0826] 5. Server Selection Methods

[0827] The server searches the database for application information and selects the most suitable application based on user input and sentiment analysis results. The database is categorized by application areas of interest, personality, and sentiment tags.

[0828] For example, search for applications tagged with "music," "adventure," and "joy." The applications found in this step might include the latest adventure music apps or apps for participating in live music events.

[0829] 6. Server result generation means

[0830] The server generates a list of appropriate applications from the search results. This list includes detailed information such as the application name, description, and download link.

[0831] The generated list is converted back to JSON format and sent to the terminal.

[0832] 7. Display methods for the terminal

[0833] The terminal analyzes application information received from the server and displays it on the user interface. Users can view a list of recommended applications and check detailed information.

[0834] Specific example

[0835] 1. User input

[0836] The user opens the application on their device and enters their area of ​​interest, "Music," and their personality, "Adventurous."

[0837] 2. Analysis of the Emotion Engine

[0838] While the user is inputting, the emotion engine analyzes their voice and facial expressions to detect if the user is experiencing the emotion of "joy."

[0839] 3. Sending from the device

[0840] The terminal formats the input data and sentiment analysis results as follows and sends them to the server:

[0841] json

[0842] {

[0843] "interest": "music",

[0844] "personality": "adventurous",

[0845] "emotion": "joy"

[0846] }

[0847] 4. Server analysis

[0848] The server performs analysis and extracts "music," "adventure," and "joy" from the user's data.

[0849] 5. Server Selection

[0850] The server searches the database and finds the relevant application. For example, "Adventure Music App" might be the relevant entry.

[0851] 6. Generating Results

[0852] The server generates a list of found applications and sends it to the terminal in the following format:

[0853] json

[0854] {

[0855] "recommendations": [

[0856] {

[0857] "name": "Adventure Music App",

[0858] "Description": "An app for enjoying the latest adventure music."

[0859] "link": "http: / / example.com / app1"

[0860] },

[0861] {

[0862] "name": "Live music event participation app",

[0863] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[0864] "link": "http: / / example.com / app2"

[0865] }

[0866] ]

[0867] }

[0868] 7. Display on the device

[0869] The device analyzes the received information and displays details about the "Adventure Music App" and the "Live Music Event Participation App" to the user. The user can read the application description and click the download link to install the application.

[0870] This system aims to improve user satisfaction by making it easy for users to find the most suitable applications based on their interests, personality, and emotions.

[0871] The following describes the processing flow.

[0872] Step 1:

[0873] The user enters information about their areas of interest and personality. For example, the user might use a smartphone application to enter information such as "music" and "adventure-loving."

[0874] Step 2:

[0875] The device captures the user's voice and facial expressions in real time. It uses the built-in microphone and camera to collect user emotion data.

[0876] Step 3:

[0877] The emotion engine analyzes the collected voice and facial expression data. For example, the emotion engine analyzes the tone of voice and facial movements to determine that the user's emotion is "joy."

[0878] Step 4:

[0879] The device formats the user's input information and the sentiment engine's analysis results into JSON format. Specifically, it converts the data to the following format:

[0880] json

[0881] {

[0882] "interest": "music",

[0883] "personality": "adventurous",

[0884] "emotion": "joy"

[0885] }

[0886] Step 5:

[0887] The device formats the JSON data and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for transmission.

[0888] Step 6:

[0889] The server receives an HTTP request and parses the JSON data. As a result of the parsing, the server extracts the information "music," "adventure," and "joy."

[0890] Step 7:

[0891] The server queries the database based on the information it extracts. This query includes searching for applications tagged with "music," "adventure," and "joy."

[0892] Step 8:

[0893] The server analyzes the query results and generates a list of applications best suited to the user's interests, personality, and emotions. For example, the following applications might be selected:

[0894] Adventure Music App

[0895] Live music event participation app

[0896] Step 9:

[0897] The application list generated by the server is converted back into JSON format and sent to the terminal. The JSON data will be in the following format:

[0898] json

[0899] {

[0900] "recommendations": [

[0901] {

[0902] "name": "Adventure Music App",

[0903] "Description": "An app for enjoying the latest adventure music."

[0904] "link": "http: / / example.com / app1"

[0905] },

[0906] {

[0907] "name": "Live music event participation app",

[0908] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[0909] "link": "http: / / example.com / app2"

[0910] }

[0911] ]

[0912] }

[0913] Step 10:

[0914] The terminal parses the JSON data received from the server. Based on the analysis results, it prepares to display information about recommended applications in the user interface.

[0915] Step 11:

[0916] The device displays an application list to the user through its user interface. The user can view details of the recommended applications and obtain them using the download links.

[0917] This detailed process allows users to easily find the optimal application based on their interests, personality, and emotions.

[0918] (Example 2)

[0919] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0920] Traditional recommendation systems are limited to recommending applications based on user interests and personality traits, lacking recommendations that take user emotions into account. This resulted in users not receiving recommendations that matched their current emotional state, making it difficult to improve user satisfaction.

[0921] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting information about the user's areas of interest and personality, means for collecting the input information for analysis, and means for analyzing the collected data in real time and identifying the user's emotions. This makes it possible to recommend the most suitable application based on the user's interests, personality, and real-time emotion analysis.

[0922] A "user" refers to an individual who uses the system to input information about their areas of interest and personality, and receives recommendations for applications.

[0923] "Areas of interest" refers to the categories or themes that the user is interested in.

[0924] "Personality" refers to a user's behavioral patterns and psychological characteristics, and is used in systems to capture the user's preferences.

[0925] "Means of inputting information" refers to interfaces or devices that allow users to provide data about their interests and personality to a system.

[0926] "Means of collecting information for analysis" refers to devices and systems that collect user-input data internally and further collect real-time sentiment data.

[0927] "Means of identifying emotions" refers to algorithms and devices that analyze collected data such as voice and facial expressions to identify the user's current emotional state.

[0928] A "server" refers to a computer system that receives information and sentiment analysis results entered by users, and then analyzes and processes them.

[0929] A "database" refers to a storage device or system used to store and manage application information that corresponds to a user's areas of interest, personality, and emotions.

[0930] "Means for selecting the optimal software" refers to algorithms and devices that allow a server to select the most suitable application from a database based on user input information and sentiment analysis results.

[0931] "Means for transmitting software information to a terminal" refers to communication methods and protocols for transmitting detailed information about a selected application to the user's terminal.

[0932] "Means for displaying software information" refers to interfaces or devices that visually present and display detailed information about applications received on a user's terminal.

[0933] "Tagging" refers to the technique of assigning specific categories or attributes to applications to facilitate organization and searching.

[0934] A "list" refers to a format that compiles information on multiple selected applications into a single entity.

[0935] "Detailed information" refers to supplementary information that helps users understand the application, such as the application's name, description, and download link.

[0936] Specific embodiments of this invention will now be described. The program of this system takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Furthermore, by combining it with an emotion engine, it also provides recommendations based on the user's emotions.

[0937] First, users use a device such as a smartphone or PC to input information about their areas of interest and personality through a dedicated application or web interface. For example, a user might input information such as "music" and "adventure-loving."

[0938] Next, the device is equipped with a microphone and camera, which collect voice and facial expression data while the user is entering information. The emotion engine analyzes this data in real time to identify the user's emotions. For example, if the user is smiling while speaking, the emotion engine will identify the emotion as "joy."

[0939] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for this. The server parses the received JSON data to identify the user's areas of interest, personality, and emotions. For example, it might parse JSON data like the following:

[0940] json

[0941] {

[0942] "interest": "music",

[0943] "personality": "adventurous",

[0944] "emotion": "joy"

[0945] }

[0946] Next, the server searches the database and selects the most suitable application based on the user's input information and sentiment analysis results. The database categorizes applications by interest, personality, and sentiment tags. For example, it searches for applications tagged with "music," "adventure," and "joy." At this point, applications such as "adventure music app" or "live music event participation app" may be selected.

[0947] The server generates a list of suitable applications from the search results, converts this list to JSON format, and sends it to the terminal. The list includes detailed information such as the application name, description, and download link. The terminal parses the received application information and displays it in the user interface. The user can browse the list of recommended applications and view detailed information. This allows the user to easily find the best application based on their interests, personality, and real-time emotions.

[0948] As a concrete example, the user opens an application on their device and enters their area of ​​interest, "music," and their personality, "adventurous." While the user is entering the information, the emotion engine analyzes their voice and facial expressions and detects that the user is experiencing the emotion of "joy." The device formats the input data and emotion analysis results and sends them to the server. The server performs the analysis and retrieves "music," "adventurous," and "joy" from the user's data. The server searches its database and finds the corresponding "adventure music app." The server generates a list of these apps and sends it to the device. The device displays the received information to the user, who can then review the details and install the application.

[0949] Examples of prompt statements include the following forms:

[0950] "Users use their smartphones to input information about their interests and personality, and an emotion engine analyzes their emotions in real time. For example, if they input 'music' and 'adventure,' it will indicate a feeling of joy. The device then sends the input data and analysis results to a server, which selects and recommends the most suitable applications to the user."

[0951] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0952] Step 1:

[0953] The system uses a means for users to input information about their areas of interest and personality. Specifically, users enter information such as "music" or "adventure-loving" into input fields on their smartphone or PC. The entered information is then passed to the system (input data: areas of interest, personality).

[0954] Step 2:

[0955] The device collects the input information for analysis. In this process, it uses its microphone and camera to collect the user's voice and facial expression data. For example, suppose the camera captures a scene where the user is smiling and talking while inputting data (input data: areas of interest, personality, voice data, facial expression data).

[0956] Step 3:

[0957] The emotion engine built into the device analyzes collected voice and facial expression data in real time to identify the user's emotions. Specifically, it uses an emotion recognition algorithm to identify emotions such as "joy" from voice tone and facial expressions (input data: voice data, facial expression data; output data: emotion).

[0958] Step 4:

[0959] The device formats the user's entered areas of interest and personality information, along with the sentiment analysis results, into JSON format. For example, it might be formatted as follows:

[0960] json

[0961] {

[0962] "interest": "music",

[0963] "personality": "adventurous",

[0964] "emotion": "joy"

[0965] }

[0966] Then, this JSON data is sent to the server as a secure HTTP request (input data: areas of interest, personality, emotions; output data: JSON data).

[0967] Step 5:

[0968] The server parses the received JSON data. Specifically, the server parses the received data, stores each part in an internal variable, and records it in the debug log (input data: JSON data, output data: areas of interest, personality, emotions).

[0969] Step 6:

[0970] The server searches the database based on the analyzed interests, personality, and emotions to select the most suitable software. For example, it might execute a database query to find applications that match "music," "adventurous," and "joy" (input data: interests, personality, emotions; output data: software list).

[0971] Step 7:

[0972] The server generates a list of the found software and converts it into JSON format as a list containing detailed descriptions. For example, it may look like this:

[0973] json

[0974] {

[0975] "recommendations": [

[0976] {

[0977] "name": "Adventure Music App",

[0978] "Description": "An app for enjoying the latest adventure music."

[0979] "link": "http: / / example.com / app1"

[0980] },

[0981] {

[0982] "name": "Live music event participation app",

[0983] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[0984] "link": "http: / / example.com / app2"

[0985] }

[0986] ]

[0987] }

[0988] Then, this JSON data is sent to the terminal as an HTTP response (input data: software list, output data: JSON data).

[0989] Step 8:

[0990] The terminal parses the received JSON data and displays it on the user interface. Specifically, it visually presents the application name, description, and download link (input data: JSON data, output data: user interface display). Based on the displayed information, the user can check detailed information and install the application by clicking the download link.

[0991] (Application Example 2)

[0992] 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."

[0993] Traditional content recommendation systems primarily rely on user interests and personality traits, and none have taken real-time emotions into account. Therefore, they fail to recommend content that matches the user's current emotional state, resulting in low user satisfaction.

[0994] 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.

[0995] In this invention, the server includes means for inputting information about the user's areas of interest and personality; means for collecting emotional data in real time using an emotional engine that analyzes the input information and the user's emotions; means for transmitting the input information and emotional data to the server; means for the server to analyze the received information and select the most suitable content from a database; means for transmitting information about the selected content to a terminal; and means for displaying the transmitted content information to the user. This enables real-time content recommendations that take the user's emotions into account.

[0996] "User" refers to consumers or users who use the system to input information about their areas of interest and personality.

[0997] "Areas of interest" refers to specific categories or themes that the user is interested in.

[0998] "Personality" refers to a user's personal characteristics and preferences.

[0999] An "emotion engine" refers to a technology that analyzes a user's voice and facial expression data to identify their emotions in real time.

[1000] "Emotional data" refers to information that quantifies or stringifies the user's emotional state as analyzed by the emotion engine.

[1001] A "server" refers to a computer system that receives and analyzes information sent by users.

[1002] A "database" refers to a storage device or system in which a server stores information about applications and content.

[1003] "Content" refers to information and media that users can enjoy, such as movies, music, videos, and podcasts.

[1004] "Recommendation" refers to the act of selecting and presenting the most suitable content based on the user's areas of interest, personality, and emotional data.

[1005] A "terminal" refers to a device used by a user to input information, such as a smartphone or smart glasses.

[1006] "Display" refers to the act of visually presenting content or recommendation results on a device's screen.

[1007] This invention is a system that recommends optimal content based on the user's areas of interest, personality, and real-time sentiment data. The system provides means for the user to input information about their areas of interest and personality, and for collecting and analyzing sentiment data using a sentiment engine.

[1008] System-wide configuration

[1009] 1. User input means

[1010] Users input information about their interests and personality through a dedicated application using devices such as smartphones or smart glasses. For example, a user might input "horror movies" and "adventure lover."

[1011] 2. Collection and analysis of emotional data using an emotion engine

[1012] The emotion engine uses the microphone and camera built into the device to collect the user's voice and facial expressions, and analyzes their emotions in real time. For example, it can detect the emotion of "excitement."

[1013] 3. Transmission method

[1014] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. This step uses a secure protocol to protect the data.

[1015] 4. Server-based analysis and selection methods

[1016] The server analyzes the received JSON data to identify the user's areas of interest, personality, and emotions. Based on this data, the server searches a database and selects the most suitable content based on the user's input and the emotion analysis results. For example, "horror adventure movies" or "adventure podcasts."

[1017] 5. Result generation and transmission means

[1018] The server generates a list of relevant content from the search results, converts it back to JSON format, and sends it to the terminal. The generated list includes detailed information such as the content name, description, and links.

[1019] 6. Display means

[1020] The terminal analyzes content information received from the server and displays it on the user interface. Users can view a list of recommended content and check detailed information.

[1021] Hardware and software to be used

[1022] Hardware:

[1023] The devices include smartphones and smart glasses. These devices are equipped with microphones and cameras and are used to collect emotional data.

[1024] software:

[1025] The frontend uses React to build the user interface, while the backend uses Node.js and Express for server-side processing. Additionally, an emotion engine analyzes speech and facial expressions, utilizing image recognition and natural language processing algorithms.

[1026] Explanation of specific examples

[1027] For example, if a user enters "horror movies" and "adventure lover" through a smartphone app, and the sentiment analysis identifies this as "excited," that information will be sent to the server in the following JSON format:

[1028] json

[1029] {

[1030] "interest": "Horror movies",

[1031] "personality": "adventurous",

[1032] "emotion": "excitement"

[1033] }

[1034] The server analyzes this data and selects content such as "horror adventure movies" and "adventure podcasts" from the database. This result is sent to the device and displayed visually to the user.

[1035] Example of a prompt

[1036] A user entered "horror movies" and "adventure" through a smartphone app, and sentiment analysis identified their mood as "excited." Please use this data to recommend appropriate content. For example, we expect responses like the following:

[1037] Horror Adventure Movie: An exciting film where horror and adventure intertwine.

[1038] Adventure Podcasts: Podcasts that will awaken your adventurous spirit.

[1039] As a result, users can smoothly find content that suits their interests and personality, while also taking their real-time emotions into consideration.

[1040] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1041] Step 1:

[1042] The user opens the smartphone app and enters their areas of interest (e.g., "horror movies") and personality traits (e.g., "adventurous"). The data entered at this point is information about the user's interests and personality.

[1043] Step 2:

[1044] As the user completes their input, the device's emotion engine analyzes their voice and facial expressions to identify their real-time emotions (e.g., "excitement"). This analysis is performed using an emotion analysis algorithm based on the collected audio and video data. The output data is then tagged with emotion tags.

[1045] Step 3:

[1046] The terminal formats the user's input information on areas of interest and personality, along with the sentiment data analyzed by the sentiment engine, into JSON format and sends it to the server using an HTTP POST request. The input data consists of the user's interests, personality, and sentiment, while the output data is a request in JSON format.

[1047] Step 4:

[1048] The server receives JSON data sent from the terminal. It parses the received input data and divides it into individual data items (interests, personality, emotions). The output data consists of these parsed data items.

[1049] Step 5:

[1050] The server searches the database based on the analyzed data items and selects the most suitable content that matches the user's interests, personality, and emotions. This selection uses a database where content information is pre-tagged. The input data consists of segmented data items, and the output data is a list of recommended content.

[1051] Step 6:

[1052] The server generates a list of selected content, converts it back into JSON format, and sends it to the terminal. This list includes content names, descriptions, links, etc. The input data is the recommended content list, and the output data is a JSON response.

[1053] Step 7:

[1054] The terminal parses the received JSON-formatted content information and displays it on the user interface. Based on this displayed information, the user can select content and view detailed information. The input data is a JSON-formatted response, while the output data is a visually represented content information.

[1055] 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.

[1056] 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.

[1057] 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.

[1058] [Third Embodiment]

[1059] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1060] 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.

[1061] 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).

[1062] 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.

[1063] 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.

[1064] 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).

[1065] 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.

[1066] 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.

[1067] 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.

[1068] 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.

[1069] 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.

[1070] 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".

[1071] This invention relates to a system that takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Specific embodiments of this system are described below.

[1072] 1. User input

[1073] Users use smartphones or other devices to input information about their areas of interest and personality through a dedicated application or web interface. For example, consider a case where a user inputs information such as "reading" and "introverted."

[1074] 2. Transmission method of the terminal

[1075] The terminal formats the information entered by the user into JSON or XML format and sends it to the server as an HTTP request. User input data is protected by a secure protocol.

[1076] 3. Server analysis methods

[1077] The server parses the JSON data received from the terminal. For example, it retrieves data like the following:

[1078] json

[1079] {

[1080] "interest": "reading",

[1081] "personality": "introverted"

[1082] }

[1083] The server analyzes this data to identify the user's areas of interest and personality.

[1084] 4. Server Selection Methods

[1085] The server searches the database for application information and selects the most suitable application based on the user's input. The database is categorized by application areas of interest and personality tags.

[1086] For example, search for applications tagged with "reading" and "introverted." Applications found in this step might include reading community apps or reading list management apps.

[1087] 5. Server result generation means

[1088] The server generates a list of appropriate applications from the search results. This list includes detailed information such as the application name, description, and download link.

[1089] The generated list is then converted back into JSON or XML format and sent to the terminal.

[1090] 6. Display methods for the terminal

[1091] The terminal analyzes application information received from the server and displays it on the user interface. Users can view a list of recommended applications and check detailed information.

[1092] Specific example

[1093] 1. User input

[1094] The user opens the application on their device and enters their area of ​​interest, "reading," and their personality type, "introverted."

[1095] 2. Sending from the device

[1096] The terminal formats the input data as follows and sends it to the server:

[1097] json

[1098] {

[1099] "interest": "reading",

[1100] "personality": "introverted"

[1101] }

[1102] 3. Server analysis

[1103] The server performs analysis and extracts "reading" and "introversion" from the user's data.

[1104] 4. Server Selection

[1105] The server searches the database and finds the relevant application. For example, "reading community app" might be the relevant one.

[1106] 5. Generating the results

[1107] The server generates a list of found applications and sends it to the terminal in the following format:

[1108] json

[1109] {

[1110] "recommendations": [

[1111] {

[1112] "name": "Reading community app",

[1113] "Description": "An app that allows you to connect with people who love reading."

[1114] "link": "http: / / example.com / app1"

[1115] }

[1116] ]

[1117] }

[1118] 6. Display on the device

[1119] The device analyzes the received information and displays details about the "Reading Community App" to the user. The user can read the application description and click the download link to install the application.

[1120] This system aims to improve user satisfaction by allowing users to easily find the most suitable applications based on their interests and personality.

[1121] The following describes the processing flow.

[1122] Step 1:

[1123] The user enters information about their areas of interest and personality. For example, the user might use a smartphone application to enter information such as "sports" and "sociable."

[1124] Step 2:

[1125] The terminal formats the user's input information into JSON format. Specifically, it converts it to the following data format:

[1126] json

[1127] {

[1128] "interest": "sports",

[1129] "personality": "social"

[1130] }

[1131] Step 3:

[1132] The device formats the JSON data and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for transmission.

[1133] Step 4:

[1134] The server receives an HTTP request and parses the JSON data. The analysis extracts the information "sports" and "sociable."

[1135] Step 5:

[1136] The server queries the database based on the information it extracts. The query includes searching for applications tagged with "sports" and "sociable".

[1137] Step 6:

[1138] The server analyzes the query results and generates a list of applications best suited to the user's interests and personality. For example, the following applications might be selected:

[1139] Sports event participation app

[1140] Team sports matching app

[1141] Step 7:

[1142] The application list generated by the server is converted back into JSON format and sent to the terminal. The JSON data will be in the following format:

[1143] json

[1144] {

[1145] "recommendations": [

[1146] {

[1147] "name": "Sports event participation app",

[1148] "Description": "An app that makes it easy to participate in sports events held in your neighborhood."

[1149] "link": "http: / / example.com / app1"

[1150] },

[1151] {

[1152] "name": "Team Sports Matching App",

[1153] "Description": "An app that allows you to match with people who share the same interest in the same sport and form a team."

[1154] "link": "http: / / example.com / app2"

[1155] }

[1156] ]

[1157] }

[1158] Step 8:

[1159] The terminal parses the JSON data received from the server. Based on the analysis results, it prepares to display information about recommended applications in the user interface.

[1160] Step 9:

[1161] The device displays an application list to the user through its user interface. The user can view details of the recommended applications and obtain them using the download links.

[1162] This process makes it easy for users to find applications that perfectly match their interests and personality.

[1163] (Example 1)

[1164] 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."

[1165] Traditional application recommendation systems have struggled to effectively provide users with appropriate applications that are sufficiently based on their interests and personalities. In particular, it takes considerable time and effort for users to find the best fit from a vast number of applications. There is a need for a system that can solve this problem and provide users with the most suitable applications quickly and efficiently.

[1166] 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.

[1167] In this invention, the server includes means for inputting information about the user's areas of interest and personality; means for converting the input information into a data format and transmitting it to the server; means for the server to analyze the received information and select the most suitable software from a database based on the user's areas of interest and personality; means for generating a list of selected software, converting it into a data format including detailed information and transmitting it to a terminal; and means for displaying the transmitted software information to the user. This enables the user to quickly and accurately find applications that match their interests and personality.

[1168] "User" refers to an individual or group that uses a computer system or digital service.

[1169] "Areas of interest" refers to themes and topics that users are interested in and in which they gather information and engage in activities.

[1170] "Personality" refers to psychological attributes that indicate an individual's tendencies in behavior and thinking.

[1171] "Means of input" refers to the devices or interfaces that users use to provide information.

[1172] "Terminal" refers to an electronic device (e.g., smartphone, PC) that a user uses to input and receive information.

[1173] "Converting to a data format" refers to the act of changing information into a structured format (e.g., JSON, XML) that follows certain rules.

[1174] A "server" refers to a computer system that receives and processes requests from users.

[1175] "Analyzing received information" refers to the act of a server reading data sent by a user, understanding its contents, and processing it.

[1176] A "database" refers to a system for efficiently storing and retrieving information.

[1177] "Selecting software" refers to the act of choosing the most suitable application based on specified criteria.

[1178] "Software" refers to a computer program that runs on an electronic device and provides a specific function.

[1179] "Generating a list" refers to the act of organizing selected items (e.g., applications) into a list format.

[1180] "Detailed information" refers to additional and specific data (e.g., name, description, link) related to the selected item (e.g., software).

[1181] "Converting to a data format" refers to the act of structuring information into a different, defined format.

[1182] "To display" refers to the act of visually presenting information through the user interface of a device.

[1183] This invention relates to a system that takes user information about their areas of interest and personality and recommends appropriate software based on that information. Specific embodiments of this system are described below.

[1184] 1. User input

[1185] Users open a dedicated application or web interface using a device such as a smartphone or PC. The user interface displays forms for entering information about their areas of interest and personality. For example, the user might enter "reading" and "introverted."

[1186] 2. Data transmission from the terminal

[1187] The terminal formats the data entered by the user into JSON format. The formatted data is then sent to the server using the HTTPS protocol. For example, the data is sent as follows:

[1188] json

[1189] {

[1190] "interest": "reading",

[1191] "personality": "introverted"

[1192] }

[1193] 3. Server data analysis

[1194] The server parses the received JSON data and extracts the user's areas of interest (e.g., "reading") and personality traits (e.g., "introverted"). A JSON parser library is used for this analysis.

[1195] 4. Server application selection

[1196] The server searches the database and selects the most suitable software based on the user's input data. The database contains software information categorized by areas of interest and personality tags. For example, it searches for software tagged with "reading" and "introverted."

[1197] 5. Server result generation

[1198] The server generates a list of recommended software from the search results. This list includes the software name, description, and download link. The generated list is then converted back into JSON format and sent to the terminal.

[1199] 6. Display on the device

[1200] The terminal parses the JSON data received from the server and displays a list of recommended software in the user interface. The user can view detailed information about the software and, if necessary, click the download link to install it.

[1201] Specific example:

[1202] 1. User input

[1203] The user opens the application on their smartphone and enters their area of ​​interest, "reading," and their personality type, "introverted."

[1204] 2. Sending from the device

[1205] The terminal formats the input data into JSON format and sends it to the server:

[1206] {

[1207] "interest": "reading",

[1208] "personality": "introverted"

[1209] }

[1210] 3. Server analysis

[1211] The server performs analysis and extracts "reading" and "introversion" from the user's data.

[1212] 4. Server Selection

[1213] The server searches the database and finds software tagged as "reading" and "introverted."

[1214] 5. Generating the results

[1215] The server generates a list of the found software and sends it to the terminal in the following format:

[1216] {

[1217] "recommendations": [

[1218] {

[1219] "name": "Reading community app",

[1220] "Description": "An app that allows you to connect with people who love reading."

[1221] "link": "http: / / example.com / app1"

[1222] }

[1223] ]

[1224] }

[1225] 6. Display on the device

[1226] The device analyzes the received information and displays details about the "Reading Community App" to the user. The user can then read the application description and click the download link to install the application.

[1227] This system aims to improve user satisfaction by allowing them to easily find the most suitable software based on their interests and personality.

[1228] Example of a prompt:

[1229] Please describe a system that takes user input information about their areas of interest and personality, and then recommends appropriate applications based on that information.

[1230] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1231] Step 1:

[1232] User input

[1233] Users open a dedicated application or web interface using a device such as a smartphone or PC. The user interface displays forms for entering information about their areas of interest and personality. For example, the user might enter "reading" and "introverted."

[1234] Input: User information about areas of interest and personality.

[1235] Process: The user enters information into a form on their device.

[1236] Output: Input data is retained on the terminal.

[1237] Step 2:

[1238] Data transmission from the device

[1239] The terminal formats the data entered by the user into JSON format. The JSON-formatted data is then sent to the server using the HTTPS protocol. For example, the data is sent in the following format:

[1240] json

[1241] {

[1242] "interest": "reading",

[1243] "personality": "introverted"

[1244] }

[1245] Input: User input data

[1246] Processing: Convert input data to JSON format and send it to the server via HTTPS.

[1247] Output: Data sent as an HTTP request to the server

[1248] Step 3:

[1249] Server Data Analysis

[1250] The server parses the received JSON data and extracts the user's areas of interest (e.g., "reading") and personality traits (e.g., "introverted"). A JSON parser library is used for this analysis.

[1251] Input: JSON data sent from the device

[1252] Processing: Analyze the data using a JSON parser library and extract areas of interest and personality traits.

[1253] Output: Analyzed areas of interest and personality data

[1254] Step 4:

[1255] Server application selection

[1256] The server searches the database and selects the most suitable software based on the user's input data. The database contains software information categorized by areas of interest and personality tags. For example, it searches for software tagged with "reading" and "introverted."

[1257] Input: Extracted areas of interest and personality data

[1258] Process: Execute database queries and search for software based on tags.

[1259] Output: List of applicable software

[1260] Step 5:

[1261] Server result generation

[1262] The server generates a list of recommended software from the search results. This list includes the software name, description, and download link. The generated list is then converted back into JSON format and sent to the terminal.

[1263] Input: Software list from search results

[1264] Processing: Format the recommended software list into JSON format and send it to the terminal.

[1265] Output: Recommended software list in JSON format

[1266] Step 6:

[1267] Terminal display

[1268] The terminal parses the JSON data received from the server and displays a list of recommended software in the user interface. The user can browse this list, identify the necessary software, and click the download link to install it.

[1269] Input: JSON data received from the server

[1270] Processing: The data is parsed using a JSON parser library and displayed in the user interface.

[1271] Output: Recommended software list displayed in the user interface

[1272] Through these steps, users can easily find the optimal software based on their interests and personality, leading to increased satisfaction.

[1273] (Application Example 1)

[1274] 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."

[1275] Traditional security measures have been uniform, failing to adequately provide personalized information tailored to individual user interests and personalities. Furthermore, limited means of providing real-time security information instantly made it difficult for users to obtain necessary information immediately. Therefore, there is a need for a personalized and rapid security information delivery system that enables users to conduct their daily activities more safely.

[1276] 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.

[1277] In this invention, the server includes means for providing personalized security measures based on user input information, means including a smart device for providing security information visually in real time, and means for analysis means for tagging and matching software based on the user's areas of interest and personality. This enables the user to obtain optimal security measures tailored to their own characteristics in real time.

[1278] "Means for inputting information" refers to the means by which users input data about their areas of interest and personality.

[1279] "Means for sending information to the server" refers to the means for sending entered user information to the server.

[1280] "Means for analyzing received information" refers to the means by which a server analyzes received data to identify the user's areas of interest and personality.

[1281] "A method for selecting the optimal software from a database" refers to a method for searching a database based on analyzed information and selecting the most suitable software for the user.

[1282] "Means for transmitting information about selected software to a terminal" refers to the means for transmitting information about selected software to the user's terminal.

[1283] "Means for displaying transmitted software information to the user" refers to means for displaying transmitted software information on the user's terminal.

[1284] "Means of providing personalized security measures" refers to means of providing individualized security measures based on user input information.

[1285] A "smart device that provides security information visually in real time" is a smart device that provides security-related information to users visually in real time.

[1286] "Analysis means" refers to a means of tagging and matching software based on the user's areas of interest and personality.

[1287] This invention is a system that allows users to input information about their areas of interest and personality, and then provides appropriate security measures based on that information. The following describes embodiments for carrying out this invention.

[1288] First, users input information about their areas of interest and personality via devices such as smart glasses or smartphones. This information is formatted digitally and sent to the server via a secure protocol. For example, if a user inputs "jogging" and "highly cautious," this information is sent to the server in JSON or XML format.

[1289] The server analyzes the received information to identify the user's areas of interest and personality. This analysis is performed using a pre-trained generative AI model. Based on the analysis results, the server selects appropriate security measures and related software from its database. This database stores various security measures and software information and is tagged, allowing for quick matching.

[1290] The selected security measures and software information are converted back into JSON or XML format and sent to the device. The device analyzes the received information and displays it visually to the user. When using smart glasses, security information is provided visually in real time. For example, while the user is jogging, a warning might appear saying, "Crime has been increasing in this area recently, please choose a different route."

[1291] This system will allow users to receive personalized security information in real time, based on their interests and personality. This is expected to improve user safety and increase user satisfaction.

[1292] As a concrete example, the following is an example of a prompt message when a user enters "jogging" as an area of ​​interest and "cautious" as a personality trait:

[1293] "The user's interest is jogging, and their personality is cautious. Please recommend an application that provides the most suitable security measures for them in real time."

[1294] As described above, the present invention is a system that provides optimal security measures based on the user's interests and personality, and is extremely effective in improving user safety.

[1295] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1296] Step 1:

[1297] Users input information about their areas of interest and personality using devices such as smart glasses or smartphones.

[1298] Input: User's areas of interest and personality information (e.g., "Jogging", "Highly cautious")

[1299] Output: User information formatted in JSON or XML format.

[1300] Operation: The user enters data into each field through the application interface, and this data is converted into a digital format.

[1301] Step 2:

[1302] The terminal sends formatted user information to the server via a secure protocol.

[1303] Input: Formatted user information

[1304] Output: HTTP request sent to the server

[1305] Operation: The terminal software converts user information into JSON or XML format and sends it to the server using a secure protocol (e.g., HTTPS).

[1306] Step 3:

[1307] The server analyzes the received user information to identify the user's areas of interest and personality.

[1308] Input: User information received by the server (in JSON or XML format)

[1309] Output: Analyzed user information (areas of interest and personality)

[1310] Operation: The server software uses a generated AI model (e.g., a model built with Scikit-learn) to analyze user information and identify areas of interest and personality.

[1311] Step 4:

[1312] Based on the analyzed information, the server selects appropriate security measures and related software from the database.

[1313] Input: Analyzed user information (areas of interest and personality)

[1314] Output: List of optimal security measures and related software

[1315] Operation: The server's database search function searches for tagged security measures and software information, identifying items that match the user's areas of interest and personality.

[1316] Step 5:

[1317] The server converts the selected security measures and software information into JSON or XML format and sends it back to the terminal.

[1318] Input: List of optimal security measures and software

[1319] Output: Data in JSON or XML format sent to the terminal.

[1320] Operation: The server software formats the selected security measures and software information and sends it to the terminal as an HTTP response.

[1321] Step 6:

[1322] The device analyzes received security measures and software information and displays it visually to the user.

[1323] Input: Information received in JSON or XML format

[1324] Output: Security information and software displayed on the user interface

[1325] Operation: The terminal software analyzes the received data and displays it on the screen of smart glasses or a smartphone. For example, while a user is jogging, a message might appear saying, "Crime has been increasing in this area recently, please choose a different route."

[1326] Through these steps, users can obtain appropriate security measures in real time based on their interests and personality.

[1327] 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.

[1328] This invention combines an emotion engine with a system that takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Specific embodiments of this system are described below.

[1329] 1. User input

[1330] Users use smartphones or other devices to input information about their interests and personality through a dedicated application or web interface. For example, a user might input information such as "music" and "adventure-loving."

[1331] 2. Emotional Engine

[1332] The device is equipped with a microphone and camera to collect user voice and facial expression data. The emotion engine collects this data and analyzes the user's emotions in real time. For example, if the user is smiling while speaking, the emotion engine identifies the emotion as "joy."

[1333] 3. Transmission method of the terminal

[1334] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. The user's input data and sentiment analysis data are protected by a secure protocol.

[1335] 4. Server analysis methods

[1336] The server parses the JSON data received from the terminal. For example, it retrieves data like the following:

[1337] json

[1338] {

[1339] "interest": "music",

[1340] "personality": "adventurous",

[1341] "emotion": "joy"

[1342] }

[1343] The server analyzes this data to identify the user's areas of interest, personality, and emotions.

[1344] 5. Server Selection Methods

[1345] The server searches the database for application information and selects the most suitable application based on user input and sentiment analysis results. The database is categorized by application areas of interest, personality, and sentiment tags.

[1346] For example, search for applications tagged with "music," "adventure," and "joy." The applications found in this step might include the latest adventure music apps or apps for participating in live music events.

[1347] 6. Server result generation means

[1348] The server generates a list of appropriate applications from the search results. This list includes detailed information such as the application name, description, and download link.

[1349] The generated list is converted back to JSON format and sent to the terminal.

[1350] 7. Display methods for the terminal

[1351] The terminal analyzes application information received from the server and displays it on the user interface. Users can view a list of recommended applications and check detailed information.

[1352] Specific example

[1353] 1. User input

[1354] The user opens the application on their device and enters their area of ​​interest, "Music," and their personality, "Adventurous."

[1355] 2. Analysis of the Emotion Engine

[1356] While the user is inputting, the emotion engine analyzes their voice and facial expressions to detect if the user is experiencing the emotion of "joy."

[1357] 3. Sending from the device

[1358] The terminal formats the input data and sentiment analysis results as follows and sends them to the server:

[1359] json

[1360] {

[1361] "interest": "music",

[1362] "personality": "adventurous",

[1363] "emotion": "joy"

[1364] }

[1365] 4. Server analysis

[1366] The server performs analysis and extracts "music," "adventure," and "joy" from the user's data.

[1367] 5. Server Selection

[1368] The server searches the database and finds the relevant application. For example, "Adventure Music App" might be the relevant entry.

[1369] 6. Generating Results

[1370] The server generates a list of found applications and sends it to the terminal in the following format:

[1371] json

[1372] {

[1373] "recommendations": [

[1374] {

[1375] "name": "Adventure Music App",

[1376] "Description": "An app for enjoying the latest adventure music."

[1377] "link": "http: / / example.com / app1"

[1378] },

[1379] {

[1380] "name": "Live music event participation app",

[1381] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[1382] "link": "http: / / example.com / app2"

[1383] }

[1384] ]

[1385] }

[1386] 7. Display on the device

[1387] The device analyzes the received information and displays details about the "Adventure Music App" and the "Live Music Event Participation App" to the user. The user can read the application description and click the download link to install the application.

[1388] This system aims to improve user satisfaction by making it easy for users to find the most suitable applications based on their interests, personality, and emotions.

[1389] The following describes the processing flow.

[1390] Step 1:

[1391] The user enters information about their areas of interest and personality. For example, the user might use a smartphone application to enter information such as "music" and "adventure-loving."

[1392] Step 2:

[1393] The device captures the user's voice and facial expressions in real time. It uses the built-in microphone and camera to collect user emotion data.

[1394] Step 3:

[1395] The emotion engine analyzes the collected voice and facial expression data. For example, the emotion engine analyzes the tone of voice and facial movements to determine that the user's emotion is "joy."

[1396] Step 4:

[1397] The device formats the user's input information and the sentiment engine's analysis results into JSON format. Specifically, it converts the data to the following format:

[1398] json

[1399] {

[1400] "interest": "music",

[1401] "personality": "adventurous",

[1402] "emotion": "joy"

[1403] }

[1404] Step 5:

[1405] The device formats the JSON data and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for transmission.

[1406] Step 6:

[1407] The server receives an HTTP request and parses the JSON data. As a result of the parsing, the server extracts the information "music," "adventure," and "joy."

[1408] Step 7:

[1409] The server queries the database based on the information it extracts. This query includes searching for applications tagged with "music," "adventure," and "joy."

[1410] Step 8:

[1411] The server analyzes the query results and generates a list of applications best suited to the user's interests, personality, and emotions. For example, the following applications might be selected:

[1412] Adventure Music App

[1413] Live music event participation app

[1414] Step 9:

[1415] The application list generated by the server is converted back into JSON format and sent to the terminal. The JSON data will be in the following format:

[1416] json

[1417] {

[1418] "recommendations": [

[1419] {

[1420] "name": "Adventure Music App",

[1421] "Description": "An app for enjoying the latest adventure music."

[1422] "link": "http: / / example.com / app1"

[1423] },

[1424] {

[1425] "name": "Live music event participation app",

[1426] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[1427] "link": "http: / / example.com / app2"

[1428] }

[1429] ]

[1430] }

[1431] Step 10:

[1432] The terminal parses the JSON data received from the server. Based on the analysis results, it prepares to display information about recommended applications in the user interface.

[1433] Step 11:

[1434] The device displays an application list to the user through its user interface. The user can view details of the recommended applications and obtain them using the download links.

[1435] This detailed process allows users to easily find the optimal application based on their interests, personality, and emotions.

[1436] (Example 2)

[1437] 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."

[1438] Traditional recommendation systems are limited to recommending applications based on user interests and personality traits, lacking recommendations that take user emotions into account. This resulted in users not receiving recommendations that matched their current emotional state, making it difficult to improve user satisfaction.

[1439] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting information about the user's areas of interest and personality, means for collecting the input information for analysis, and means for analyzing the collected data in real time and identifying the user's emotions. This makes it possible to recommend the most suitable application based on the user's interests, personality, and real-time emotion analysis.

[1440] A "user" refers to an individual who uses the system to input information about their areas of interest and personality, and receives recommendations for applications.

[1441] "Areas of interest" refers to the categories or themes that the user is interested in.

[1442] "Personality" refers to a user's behavioral patterns and psychological characteristics, and is used in systems to capture the user's preferences.

[1443] "Means of inputting information" refers to interfaces or devices that allow users to provide data about their interests and personality to a system.

[1444] "Means of collecting information for analysis" refers to devices and systems that collect user-input data internally and further collect real-time sentiment data.

[1445] "Means of identifying emotions" refers to algorithms and devices that analyze collected data such as voice and facial expressions to identify the user's current emotional state.

[1446] A "server" refers to a computer system that receives information and sentiment analysis results entered by users, and then analyzes and processes them.

[1447] A "database" refers to a storage device or system used to store and manage application information that corresponds to a user's areas of interest, personality, and emotions.

[1448] "Means for selecting the optimal software" refers to algorithms and devices that allow a server to select the most suitable application from a database based on user input information and sentiment analysis results.

[1449] "Means for transmitting software information to a terminal" refers to communication methods and protocols for transmitting detailed information about a selected application to the user's terminal.

[1450] "Means for displaying software information" refers to interfaces or devices that visually present and display detailed information about applications received on a user's terminal.

[1451] "Tagging" refers to the technique of assigning specific categories or attributes to applications to facilitate organization and searching.

[1452] A "list" refers to a format that compiles information on multiple selected applications into a single entity.

[1453] "Detailed information" refers to supplementary information that helps users understand the application, such as the application's name, description, and download link.

[1454] Specific embodiments of this invention will now be described. The program of this system takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Furthermore, by combining it with an emotion engine, it also provides recommendations based on the user's emotions.

[1455] First, users use a device such as a smartphone or PC to input information about their areas of interest and personality through a dedicated application or web interface. For example, a user might input information such as "music" and "adventure-loving."

[1456] Next, the device is equipped with a microphone and camera, which collect voice and facial expression data while the user is entering information. The emotion engine analyzes this data in real time to identify the user's emotions. For example, if the user is smiling while speaking, the emotion engine will identify the emotion as "joy."

[1457] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for this. The server parses the received JSON data to identify the user's areas of interest, personality, and emotions. For example, it might parse JSON data like the following:

[1458] json

[1459] {

[1460] "interest": "music",

[1461] "personality": "adventurous",

[1462] "emotion": "joy"

[1463] }

[1464] Next, the server searches the database and selects the most suitable application based on the user's input information and sentiment analysis results. The database categorizes applications by interest, personality, and sentiment tags. For example, it searches for applications tagged with "music," "adventure," and "joy." At this point, applications such as "adventure music app" or "live music event participation app" may be selected.

[1465] The server generates a list of suitable applications from the search results, converts this list to JSON format, and sends it to the terminal. The list includes detailed information such as the application name, description, and download link. The terminal parses the received application information and displays it in the user interface. The user can browse the list of recommended applications and view detailed information. This allows the user to easily find the best application based on their interests, personality, and real-time emotions.

[1466] As a concrete example, the user opens an application on their device and enters their area of ​​interest, "music," and their personality, "adventurous." While the user is entering the information, the emotion engine analyzes their voice and facial expressions and detects that the user is experiencing the emotion of "joy." The device formats the input data and emotion analysis results and sends them to the server. The server performs the analysis and retrieves "music," "adventurous," and "joy" from the user's data. The server searches its database and finds the corresponding "adventure music app." The server generates a list of these apps and sends it to the device. The device displays the received information to the user, who can then review the details and install the application.

[1467] Examples of prompt statements include the following forms:

[1468] "Users use their smartphones to input information about their interests and personality, and an emotion engine analyzes their emotions in real time. For example, if they input 'music' and 'adventure,' it will indicate a feeling of joy. The device then sends the input data and analysis results to a server, which selects and recommends the most suitable applications to the user."

[1469] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1470] Step 1:

[1471] The system uses a means for users to input information about their areas of interest and personality. Specifically, users enter information such as "music" or "adventure-loving" into input fields on their smartphone or PC. The entered information is then passed to the system (input data: areas of interest, personality).

[1472] Step 2:

[1473] The device collects the input information for analysis. In this process, it uses its microphone and camera to collect the user's voice and facial expression data. For example, suppose the camera captures a scene where the user is smiling and talking while inputting data (input data: areas of interest, personality, voice data, facial expression data).

[1474] Step 3:

[1475] The emotion engine built into the device analyzes collected voice and facial expression data in real time to identify the user's emotions. Specifically, it uses an emotion recognition algorithm to identify emotions such as "joy" from voice tone and facial expressions (input data: voice data, facial expression data; output data: emotion).

[1476] Step 4:

[1477] The device formats the user's entered areas of interest and personality information, along with the sentiment analysis results, into JSON format. For example, it might be formatted as follows:

[1478] json

[1479] {

[1480] "interest": "music",

[1481] "personality": "adventurous",

[1482] "emotion": "joy"

[1483] }

[1484] Then, this JSON data is sent to the server as a secure HTTP request (input data: areas of interest, personality, emotions; output data: JSON data).

[1485] Step 5:

[1486] The server parses the received JSON data. Specifically, the server parses the received data, stores each part in an internal variable, and records it in the debug log (input data: JSON data, output data: areas of interest, personality, emotions).

[1487] Step 6:

[1488] The server searches the database based on the analyzed interests, personality, and emotions to select the most suitable software. For example, it might execute a database query to find applications that match "music," "adventurous," and "joy" (input data: interests, personality, emotions; output data: software list).

[1489] Step 7:

[1490] The server generates a list of the found software and converts it into JSON format as a list containing detailed descriptions. For example, it may look like this:

[1491] json

[1492] {

[1493] "recommendations": [

[1494] {

[1495] "name": "Adventure Music App",

[1496] "Description": "An app for enjoying the latest adventure music."

[1497] "link": "http: / / example.com / app1"

[1498] },

[1499] {

[1500] "name": "Live music event participation app",

[1501] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[1502] "link": "http: / / example.com / app2"

[1503] }

[1504] ]

[1505] }

[1506] Then, this JSON data is sent to the terminal as an HTTP response (input data: software list, output data: JSON data).

[1507] Step 8:

[1508] The terminal parses the received JSON data and displays it on the user interface. Specifically, it visually presents the application name, description, and download link (input data: JSON data, output data: user interface display). Based on the displayed information, the user can check detailed information and install the application by clicking the download link.

[1509] (Application Example 2)

[1510] 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."

[1511] Traditional content recommendation systems primarily rely on user interests and personality traits, and none have taken real-time emotions into account. Therefore, they fail to recommend content that matches the user's current emotional state, resulting in low user satisfaction.

[1512] 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.

[1513] In this invention, the server includes means for inputting information about the user's areas of interest and personality; means for collecting emotional data in real time using an emotional engine that analyzes the input information and the user's emotions; means for transmitting the input information and emotional data to the server; means for the server to analyze the received information and select the most suitable content from a database; means for transmitting information about the selected content to a terminal; and means for displaying the transmitted content information to the user. This enables real-time content recommendations that take the user's emotions into account.

[1514] "User" refers to consumers or users who use the system to input information about their areas of interest and personality.

[1515] "Areas of interest" refers to specific categories or themes that the user is interested in.

[1516] "Personality" refers to a user's personal characteristics and preferences.

[1517] An "emotion engine" refers to a technology that analyzes a user's voice and facial expression data to identify their emotions in real time.

[1518] "Emotional data" refers to information that quantifies or stringifies the user's emotional state as analyzed by the emotion engine.

[1519] A "server" refers to a computer system that receives and analyzes information sent by users.

[1520] A "database" refers to a storage device or system in which a server stores information about applications and content.

[1521] "Content" refers to information and media that users can enjoy, such as movies, music, videos, and podcasts.

[1522] "Recommendation" refers to the act of selecting and presenting the most suitable content based on the user's areas of interest, personality, and emotional data.

[1523] A "terminal" refers to a device used by a user to input information, such as a smartphone or smart glasses.

[1524] "Display" refers to the act of visually presenting content or recommendation results on a device's screen.

[1525] This invention is a system that recommends optimal content based on the user's areas of interest, personality, and real-time sentiment data. The system provides means for the user to input information about their areas of interest and personality, and for collecting and analyzing sentiment data using a sentiment engine.

[1526] System-wide configuration

[1527] 1. User input means

[1528] Users input information about their interests and personality through a dedicated application using devices such as smartphones or smart glasses. For example, a user might input "horror movies" and "adventure lover."

[1529] 2. Collection and analysis of emotional data using an emotion engine

[1530] The emotion engine uses the microphone and camera built into the device to collect the user's voice and facial expressions, and analyzes their emotions in real time. For example, it can detect the emotion of "excitement."

[1531] 3. Transmission method

[1532] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. This step uses a secure protocol to protect the data.

[1533] 4. Server-based analysis and selection methods

[1534] The server analyzes the received JSON data to identify the user's areas of interest, personality, and emotions. Based on this data, the server searches a database and selects the most suitable content based on the user's input and the emotion analysis results. For example, "horror adventure movies" or "adventure podcasts."

[1535] 5. Result generation and transmission means

[1536] The server generates a list of relevant content from the search results, converts it back to JSON format, and sends it to the terminal. The generated list includes detailed information such as the content name, description, and links.

[1537] 6. Display means

[1538] The terminal analyzes content information received from the server and displays it on the user interface. Users can view a list of recommended content and check detailed information.

[1539] Hardware and software to be used

[1540] Hardware:

[1541] The devices include smartphones and smart glasses. These devices are equipped with microphones and cameras and are used to collect emotional data.

[1542] software:

[1543] The frontend uses React to build the user interface, while the backend uses Node.js and Express for server-side processing. Additionally, an emotion engine analyzes speech and facial expressions, utilizing image recognition and natural language processing algorithms.

[1544] Explanation of specific examples

[1545] For example, if a user enters "horror movies" and "adventure lover" through a smartphone app, and the sentiment analysis identifies this as "excited," that information will be sent to the server in the following JSON format:

[1546] json

[1547] {

[1548] "interest": "Horror movies",

[1549] "personality": "adventurous",

[1550] "emotion": "excitement"

[1551] }

[1552] The server analyzes this data and selects content such as "horror adventure movies" and "adventure podcasts" from the database. This result is sent to the device and displayed visually to the user.

[1553] Example of a prompt

[1554] A user entered "horror movies" and "adventure" through a smartphone app, and sentiment analysis identified their mood as "excited." Please use this data to recommend appropriate content. For example, we expect responses like the following:

[1555] Horror Adventure Movie: An exciting film where horror and adventure intertwine.

[1556] Adventure Podcasts: Podcasts that will awaken your adventurous spirit.

[1557] As a result, users can smoothly find content that suits their interests and personality, while also taking their real-time emotions into consideration.

[1558] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1559] Step 1:

[1560] The user opens the smartphone app and enters their areas of interest (e.g., "horror movies") and personality traits (e.g., "adventurous"). The data entered at this point is information about the user's interests and personality.

[1561] Step 2:

[1562] As the user completes their input, the device's emotion engine analyzes their voice and facial expressions to identify their real-time emotions (e.g., "excitement"). This analysis is performed using an emotion analysis algorithm based on the collected audio and video data. The output data is then tagged with emotion tags.

[1563] Step 3:

[1564] The terminal formats the user's input information on areas of interest and personality, along with the sentiment data analyzed by the sentiment engine, into JSON format and sends it to the server using an HTTP POST request. The input data consists of the user's interests, personality, and sentiment, while the output data is a request in JSON format.

[1565] Step 4:

[1566] The server receives JSON data sent from the terminal. It parses the received input data and divides it into individual data items (interests, personality, emotions). The output data consists of these parsed data items.

[1567] Step 5:

[1568] The server searches the database based on the analyzed data items and selects the most suitable content that matches the user's interests, personality, and emotions. This selection uses a database where content information is pre-tagged. The input data consists of segmented data items, and the output data is a list of recommended content.

[1569] Step 6:

[1570] The server generates a list of selected content, converts it back into JSON format, and sends it to the terminal. This list includes content names, descriptions, links, etc. The input data is the recommended content list, and the output data is a JSON response.

[1571] Step 7:

[1572] The terminal parses the received JSON-formatted content information and displays it on the user interface. Based on this displayed information, the user can select content and view detailed information. The input data is a JSON-formatted response, while the output data is a visually represented content information.

[1573] 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.

[1574] 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.

[1575] 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.

[1576] [Fourth Embodiment]

[1577] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1578] 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.

[1579] 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).

[1580] 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.

[1581] 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.

[1582] 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).

[1583] 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.

[1584] 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.

[1585] 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.

[1586] 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.

[1587] 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.

[1588] 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.

[1589] 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".

[1590] This invention relates to a system that takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Specific embodiments of this system are described below.

[1591] 1. User input

[1592] Users use smartphones or other devices to input information about their areas of interest and personality through a dedicated application or web interface. For example, consider a case where a user inputs information such as "reading" and "introverted."

[1593] 2. Transmission method of the terminal

[1594] The terminal formats the information entered by the user into JSON or XML format and sends it to the server as an HTTP request. User input data is protected by a secure protocol.

[1595] 3. Server analysis methods

[1596] The server parses the JSON data received from the terminal. For example, it retrieves data like the following:

[1597] json

[1598] {

[1599] "interest": "reading",

[1600] "personality": "introverted"

[1601] }

[1602] The server analyzes this data to identify the user's areas of interest and personality.

[1603] 4. Server Selection Methods

[1604] The server searches the database for application information and selects the most suitable application based on the user's input. The database is categorized by application areas of interest and personality tags.

[1605] For example, search for applications tagged with "reading" and "introverted." Applications found in this step might include reading community apps or reading list management apps.

[1606] 5. Server result generation means

[1607] The server generates a list of appropriate applications from the search results. This list includes detailed information such as the application name, description, and download link.

[1608] The generated list is then converted back into JSON or XML format and sent to the terminal.

[1609] 6. Display methods for the terminal

[1610] The terminal analyzes application information received from the server and displays it on the user interface. Users can view a list of recommended applications and check detailed information.

[1611] Specific example

[1612] 1. User input

[1613] The user opens the application on their device and enters their area of ​​interest, "reading," and their personality type, "introverted."

[1614] 2. Sending from the device

[1615] The terminal formats the input data as follows and sends it to the server:

[1616] json

[1617] {

[1618] "interest": "reading",

[1619] "personality": "introverted"

[1620] }

[1621] 3. Server analysis

[1622] The server performs analysis and extracts "reading" and "introversion" from the user's data.

[1623] 4. Server Selection

[1624] The server searches the database and finds the relevant application. For example, "reading community app" might be the relevant one.

[1625] 5. Generating the results

[1626] The server generates a list of found applications and sends it to the terminal in the following format:

[1627] json

[1628] {

[1629] "recommendations": [

[1630] {

[1631] "name": "Reading community app",

[1632] "Description": "An app that allows you to connect with people who love reading."

[1633] "link": "http: / / example.com / app1"

[1634] }

[1635] ]

[1636] }

[1637] 6. Display on the device

[1638] The device analyzes the received information and displays details about the "Reading Community App" to the user. The user can read the application description and click the download link to install the application.

[1639] This system aims to improve user satisfaction by allowing users to easily find the most suitable applications based on their interests and personality.

[1640] The following describes the processing flow.

[1641] Step 1:

[1642] The user enters information about their areas of interest and personality. For example, the user might use a smartphone application to enter information such as "sports" and "sociable."

[1643] Step 2:

[1644] The terminal formats the user's input information into JSON format. Specifically, it converts it to the following data format:

[1645] json

[1646] {

[1647] "interest": "sports",

[1648] "personality": "social"

[1649] }

[1650] Step 3:

[1651] The device formats the JSON data and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for transmission.

[1652] Step 4:

[1653] The server receives an HTTP request and parses the JSON data. The analysis extracts the information "sports" and "sociable."

[1654] Step 5:

[1655] The server queries the database based on the information it extracts. The query includes searching for applications tagged with "sports" and "sociable".

[1656] Step 6:

[1657] The server analyzes the query results and generates a list of applications best suited to the user's interests and personality. For example, the following applications might be selected:

[1658] Sports event participation app

[1659] Team sports matching app

[1660] Step 7:

[1661] The application list generated by the server is converted back into JSON format and sent to the terminal. The JSON data will be in the following format:

[1662] json

[1663] {

[1664] "recommendations": [

[1665] {

[1666] "name": "Sports event participation app",

[1667] "Description": "An app that makes it easy to participate in sports events held in your neighborhood."

[1668] "link": "http: / / example.com / app1"

[1669] },

[1670] {

[1671] "name": "Team Sports Matching App",

[1672] "Description": "An app that allows you to match with people who share the same interest in the same sport and form a team."

[1673] "link": "http: / / example.com / app2"

[1674] }

[1675] ]

[1676] }

[1677] Step 8:

[1678] The terminal parses the JSON data received from the server. Based on the analysis results, it prepares to display information about recommended applications in the user interface.

[1679] Step 9:

[1680] The device displays an application list to the user through its user interface. The user can view details of the recommended applications and obtain them using the download links.

[1681] This process makes it easy for users to find applications that perfectly match their interests and personality.

[1682] (Example 1)

[1683] 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".

[1684] Traditional application recommendation systems have struggled to effectively provide users with appropriate applications that are sufficiently based on their interests and personalities. In particular, it takes considerable time and effort for users to find the best fit from a vast number of applications. There is a need for a system that can solve this problem and provide users with the most suitable applications quickly and efficiently.

[1685] 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.

[1686] In this invention, the server includes means for inputting information about the user's areas of interest and personality; means for converting the input information into a data format and transmitting it to the server; means for the server to analyze the received information and select the most suitable software from a database based on the user's areas of interest and personality; means for generating a list of selected software, converting it into a data format including detailed information and transmitting it to a terminal; and means for displaying the transmitted software information to the user. This enables the user to quickly and accurately find applications that match their interests and personality.

[1687] "User" refers to an individual or group that uses a computer system or digital service.

[1688] "Areas of interest" refers to themes and topics that users are interested in and in which they gather information and engage in activities.

[1689] "Personality" refers to psychological attributes that indicate an individual's tendencies in behavior and thinking.

[1690] "Means of input" refers to the devices or interfaces that users use to provide information.

[1691] "Terminal" refers to an electronic device (e.g., smartphone, PC) that a user uses to input and receive information.

[1692] "Converting to a data format" refers to the act of changing information into a structured format (e.g., JSON, XML) that follows certain rules.

[1693] A "server" refers to a computer system that receives and processes requests from users.

[1694] "Analyzing received information" refers to the act of a server reading data sent by a user, understanding its contents, and processing it.

[1695] A "database" refers to a system for efficiently storing and retrieving information.

[1696] "Selecting software" refers to the act of choosing the most suitable application based on specified criteria.

[1697] "Software" refers to a computer program that runs on an electronic device and provides a specific function.

[1698] "Generating a list" refers to the act of organizing selected items (e.g., applications) into a list format.

[1699] "Detailed information" refers to additional and specific data (e.g., name, description, link) related to the selected item (e.g., software).

[1700] "Converting to a data format" refers to the act of structuring information into a different, defined format.

[1701] "To display" refers to the act of visually presenting information through the user interface of a device.

[1702] This invention relates to a system that takes user information about their areas of interest and personality and recommends appropriate software based on that information. Specific embodiments of this system are described below.

[1703] 1. User input

[1704] Users open a dedicated application or web interface using a device such as a smartphone or PC. The user interface displays forms for entering information about their areas of interest and personality. For example, the user might enter "reading" and "introverted."

[1705] 2. Data transmission from the terminal

[1706] The terminal formats the data entered by the user into JSON format. The formatted data is then sent to the server using the HTTPS protocol. For example, the data is sent as follows:

[1707] json

[1708] {

[1709] "interest": "reading",

[1710] "personality": "introverted"

[1711] }

[1712] 3. Server data analysis

[1713] The server parses the received JSON data and extracts the user's areas of interest (e.g., "reading") and personality traits (e.g., "introverted"). A JSON parser library is used for this analysis.

[1714] 4. Server application selection

[1715] The server searches the database and selects the most suitable software based on the user's input data. The database contains software information categorized by areas of interest and personality tags. For example, it searches for software tagged with "reading" and "introverted."

[1716] 5. Server result generation

[1717] The server generates a list of recommended software from the search results. This list includes the software name, description, and download link. The generated list is then converted back into JSON format and sent to the terminal.

[1718] 6. Display on the device

[1719] The terminal parses the JSON data received from the server and displays a list of recommended software in the user interface. The user can view detailed information about the software and, if necessary, click the download link to install it.

[1720] Specific example:

[1721] 1. User input

[1722] The user opens the application on their smartphone and enters their area of ​​interest, "reading," and their personality type, "introverted."

[1723] 2. Sending from the device

[1724] The terminal formats the input data into JSON format and sends it to the server:

[1725] {

[1726] "interest": "reading",

[1727] "personality": "introverted"

[1728] }

[1729] 3. Server analysis

[1730] The server performs analysis and extracts "reading" and "introversion" from the user's data.

[1731] 4. Server Selection

[1732] The server searches the database and finds software tagged as "reading" and "introverted."

[1733] 5. Generating the results

[1734] The server generates a list of the found software and sends it to the terminal in the following format:

[1735] {

[1736] "recommendations": [

[1737] {

[1738] "name": "Reading community app",

[1739] "Description": "An app that allows you to connect with people who love reading."

[1740] "link": "http: / / example.com / app1"

[1741] }

[1742] ]

[1743] }

[1744] 6. Display on the device

[1745] The device analyzes the received information and displays details about the "Reading Community App" to the user. The user can then read the application description and click the download link to install the application.

[1746] This system aims to improve user satisfaction by allowing them to easily find the most suitable software based on their interests and personality.

[1747] Example of a prompt:

[1748] Please describe a system that takes user input information about their areas of interest and personality, and then recommends appropriate applications based on that information.

[1749] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1750] Step 1:

[1751] User input

[1752] Users open a dedicated application or web interface using a device such as a smartphone or PC. The user interface displays forms for entering information about their areas of interest and personality. For example, the user might enter "reading" and "introverted."

[1753] Input: User information about areas of interest and personality.

[1754] Process: The user enters information into a form on their device.

[1755] Output: Input data is retained on the terminal.

[1756] Step 2:

[1757] Data transmission from the device

[1758] The terminal formats the data entered by the user into JSON format. The JSON-formatted data is then sent to the server using the HTTPS protocol. For example, the data is sent in the following format:

[1759] json

[1760] {

[1761] "interest": "reading",

[1762] "personality": "introverted"

[1763] }

[1764] Input: User input data

[1765] Processing: Convert input data to JSON format and send it to the server via HTTPS.

[1766] Output: Data sent as an HTTP request to the server

[1767] Step 3:

[1768] Server Data Analysis

[1769] The server parses the received JSON data and extracts the user's areas of interest (e.g., "reading") and personality traits (e.g., "introverted"). A JSON parser library is used for this analysis.

[1770] Input: JSON data sent from the device

[1771] Processing: Analyze the data using a JSON parser library and extract areas of interest and personality traits.

[1772] Output: Analyzed areas of interest and personality data

[1773] Step 4:

[1774] Server application selection

[1775] The server searches the database and selects the most suitable software based on the user's input data. The database contains software information categorized by areas of interest and personality tags. For example, it searches for software tagged with "reading" and "introverted."

[1776] Input: Extracted areas of interest and personality data

[1777] Process: Execute database queries and search for software based on tags.

[1778] Output: List of applicable software

[1779] Step 5:

[1780] Server result generation

[1781] The server generates a list of recommended software from the search results. This list includes the software name, description, and download link. The generated list is then converted back into JSON format and sent to the terminal.

[1782] Input: Software list from search results

[1783] Processing: Format the recommended software list into JSON format and send it to the terminal.

[1784] Output: Recommended software list in JSON format

[1785] Step 6:

[1786] Terminal display

[1787] The terminal parses the JSON data received from the server and displays a list of recommended software in the user interface. The user can browse this list, identify the necessary software, and click the download link to install it.

[1788] Input: JSON data received from the server

[1789] Processing: The data is parsed using a JSON parser library and displayed in the user interface.

[1790] Output: Recommended software list displayed in the user interface

[1791] Through these steps, users can easily find the optimal software based on their interests and personality, leading to increased satisfaction.

[1792] (Application Example 1)

[1793] 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".

[1794] Traditional security measures have been uniform, failing to adequately provide personalized information tailored to individual user interests and personalities. Furthermore, limited means of providing real-time security information instantly made it difficult for users to obtain necessary information immediately. Therefore, there is a need for a personalized and rapid security information delivery system that enables users to conduct their daily activities more safely.

[1795] 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.

[1796] In this invention, the server includes means for providing personalized security measures based on user input information, means including a smart device for providing security information visually in real time, and means for analysis means for tagging and matching software based on the user's areas of interest and personality. This enables the user to obtain optimal security measures tailored to their own characteristics in real time.

[1797] "Means for inputting information" refers to the means by which users input data about their areas of interest and personality.

[1798] "Means for sending information to the server" refers to the means for sending entered user information to the server.

[1799] "Means for analyzing received information" refers to the means by which a server analyzes received data to identify the user's areas of interest and personality.

[1800] "A method for selecting the optimal software from a database" refers to a method for searching a database based on analyzed information and selecting the most suitable software for the user.

[1801] "Means for transmitting information about selected software to a terminal" refers to the means for transmitting information about selected software to the user's terminal.

[1802] "Means for displaying transmitted software information to the user" refers to means for displaying transmitted software information on the user's terminal.

[1803] "Means of providing personalized security measures" refers to means of providing individualized security measures based on user input information.

[1804] A "smart device that provides security information visually in real time" is a smart device that provides security-related information to users visually in real time.

[1805] "Analysis means" refers to a means of tagging and matching software based on the user's areas of interest and personality.

[1806] This invention is a system that allows users to input information about their areas of interest and personality, and then provides appropriate security measures based on that information. The following describes embodiments for carrying out this invention.

[1807] First, users input information about their areas of interest and personality via devices such as smart glasses or smartphones. This information is formatted digitally and sent to the server via a secure protocol. For example, if a user inputs "jogging" and "highly cautious," this information is sent to the server in JSON or XML format.

[1808] The server analyzes the received information to identify the user's areas of interest and personality. This analysis is performed using a pre-trained generative AI model. Based on the analysis results, the server selects appropriate security measures and related software from its database. This database stores various security measures and software information and is tagged, allowing for quick matching.

[1809] The selected security measures and software information are converted back into JSON or XML format and sent to the device. The device analyzes the received information and displays it visually to the user. When using smart glasses, security information is provided visually in real time. For example, while the user is jogging, a warning might appear saying, "Crime has been increasing in this area recently, please choose a different route."

[1810] This system will allow users to receive personalized security information in real time, based on their interests and personality. This is expected to improve user safety and increase user satisfaction.

[1811] As a concrete example, the following is an example of a prompt message when a user enters "jogging" as an area of ​​interest and "cautious" as a personality trait:

[1812] "The user's interest is jogging, and their personality is cautious. Please recommend an application that provides the most suitable security measures for them in real time."

[1813] As described above, the present invention is a system that provides optimal security measures based on the user's interests and personality, and is extremely effective in improving user safety.

[1814] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1815] Step 1:

[1816] Users input information about their areas of interest and personality using devices such as smart glasses or smartphones.

[1817] Input: User's areas of interest and personality information (e.g., "Jogging", "Highly cautious")

[1818] Output: User information formatted in JSON or XML format.

[1819] Operation: The user enters data into each field through the application interface, and this data is converted into a digital format.

[1820] Step 2:

[1821] The terminal sends formatted user information to the server via a secure protocol.

[1822] Input: Formatted user information

[1823] Output: HTTP request sent to the server

[1824] Operation: The terminal software converts user information into JSON or XML format and sends it to the server using a secure protocol (e.g., HTTPS).

[1825] Step 3:

[1826] The server analyzes the received user information to identify the user's areas of interest and personality.

[1827] Input: User information received by the server (in JSON or XML format)

[1828] Output: Analyzed user information (areas of interest and personality)

[1829] Operation: The server software uses a generated AI model (e.g., a model built with Scikit-learn) to analyze user information and identify areas of interest and personality.

[1830] Step 4:

[1831] Based on the analyzed information, the server selects appropriate security measures and related software from the database.

[1832] Input: Analyzed user information (areas of interest and personality)

[1833] Output: List of optimal security measures and related software

[1834] Operation: The server's database search function searches for tagged security measures and software information, identifying items that match the user's areas of interest and personality.

[1835] Step 5:

[1836] The server converts the selected security measures and software information into JSON or XML format and sends it back to the terminal.

[1837] Input: List of optimal security measures and software

[1838] Output: Data in JSON or XML format sent to the terminal.

[1839] Operation: The server software formats the selected security measures and software information and sends it to the terminal as an HTTP response.

[1840] Step 6:

[1841] The device analyzes received security measures and software information and displays it visually to the user.

[1842] Input: Information received in JSON or XML format

[1843] Output: Security information and software displayed on the user interface

[1844] Operation: The terminal software analyzes the received data and displays it on the screen of smart glasses or a smartphone. For example, while a user is jogging, a message might appear saying, "Crime has been increasing in this area recently, please choose a different route."

[1845] Through these steps, users can obtain appropriate security measures in real time based on their interests and personality.

[1846] 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.

[1847] This invention combines an emotion engine with a system that takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Specific embodiments of this system are described below.

[1848] 1. User input

[1849] Users use smartphones or other devices to input information about their interests and personality through a dedicated application or web interface. For example, a user might input information such as "music" and "adventure-loving."

[1850] 2. Emotional Engine

[1851] The device is equipped with a microphone and camera to collect user voice and facial expression data. The emotion engine collects this data and analyzes the user's emotions in real time. For example, if the user is smiling while speaking, the emotion engine identifies the emotion as "joy."

[1852] 3. Transmission method of the terminal

[1853] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. The user's input data and sentiment analysis data are protected by a secure protocol.

[1854] 4. Server analysis methods

[1855] The server parses the JSON data received from the terminal. For example, it retrieves data like the following:

[1856] json

[1857] {

[1858] "interest": "music",

[1859] "personality": "adventurous",

[1860] "emotion": "joy"

[1861] }

[1862] The server analyzes this data to identify the user's areas of interest, personality, and emotions.

[1863] 5. Server Selection Methods

[1864] The server searches the database for application information and selects the most suitable application based on user input and sentiment analysis results. The database is categorized by application areas of interest, personality, and sentiment tags.

[1865] For example, search for applications tagged with "music," "adventure," and "joy." The applications found in this step might include the latest adventure music apps or apps for participating in live music events.

[1866] 6. Server result generation means

[1867] The server generates a list of appropriate applications from the search results. This list includes detailed information such as the application name, description, and download link.

[1868] The generated list is converted back to JSON format and sent to the terminal.

[1869] 7. Display methods for the terminal

[1870] The terminal analyzes application information received from the server and displays it on the user interface. Users can view a list of recommended applications and check detailed information.

[1871] Specific example

[1872] 1. User input

[1873] The user opens the application on their device and enters their area of ​​interest, "Music," and their personality, "Adventurous."

[1874] 2. Analysis of the Emotion Engine

[1875] While the user is inputting, the emotion engine analyzes their voice and facial expressions to detect if the user is experiencing the emotion of "joy."

[1876] 3. Sending from the device

[1877] The terminal formats the input data and sentiment analysis results as follows and sends them to the server:

[1878] json

[1879] {

[1880] "interest": "music",

[1881] "personality": "adventurous",

[1882] "emotion": "joy"

[1883] }

[1884] 4. Server analysis

[1885] The server performs analysis and extracts "music," "adventure," and "joy" from the user's data.

[1886] 5. Server Selection

[1887] The server searches the database and finds the relevant application. For example, "Adventure Music App" might be the relevant entry.

[1888] 6. Generating Results

[1889] The server generates a list of found applications and sends it to the terminal in the following format:

[1890] json

[1891] {

[1892] "recommendations": [

[1893] {

[1894] "name": "Adventure Music App",

[1895] "Description": "An app for enjoying the latest adventure music."

[1896] "link": "http: / / example.com / app1"

[1897] },

[1898] {

[1899] "name": "Live music event participation app",

[1900] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[1901] "link": "http: / / example.com / app2"

[1902] }

[1903] ]

[1904] }

[1905] 7. Display on the device

[1906] The device analyzes the received information and displays details about the "Adventure Music App" and the "Live Music Event Participation App" to the user. The user can read the application description and click the download link to install the application.

[1907] This system aims to improve user satisfaction by making it easy for users to find the most suitable applications based on their interests, personality, and emotions.

[1908] The following describes the processing flow.

[1909] Step 1:

[1910] The user enters information about their areas of interest and personality. For example, the user might use a smartphone application to enter information such as "music" and "adventure-loving."

[1911] Step 2:

[1912] The device captures the user's voice and facial expressions in real time. It uses the built-in microphone and camera to collect user emotion data.

[1913] Step 3:

[1914] The emotion engine analyzes the collected voice and facial expression data. For example, the emotion engine analyzes the tone of voice and facial movements to determine that the user's emotion is "joy."

[1915] Step 4:

[1916] The device formats the user's input information and the sentiment engine's analysis results into JSON format. Specifically, it converts the data to the following format:

[1917] json

[1918] {

[1919] "interest": "music",

[1920] "personality": "adventurous",

[1921] "emotion": "joy"

[1922] }

[1923] Step 5:

[1924] The device formats the JSON data and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for transmission.

[1925] Step 6:

[1926] The server receives an HTTP request and parses the JSON data. As a result of the parsing, the server extracts the information "music," "adventure," and "joy."

[1927] Step 7:

[1928] The server queries the database based on the information it extracts. This query includes searching for applications tagged with "music," "adventure," and "joy."

[1929] Step 8:

[1930] The server analyzes the query results and generates a list of applications best suited to the user's interests, personality, and emotions. For example, the following applications might be selected:

[1931] Adventure Music App

[1932] Live music event participation app

[1933] Step 9:

[1934] The application list generated by the server is converted back into JSON format and sent to the terminal. The JSON data will be in the following format:

[1935] json

[1936] {

[1937] "recommendations": [

[1938] {

[1939] "name": "Adventure Music App",

[1940] "Description": "An app for enjoying the latest adventure music."

[1941] "link": "http: / / example.com / app1"

[1942] },

[1943] {

[1944] "name": "Live music event participation app",

[1945] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[1946] "link": "http: / / example.com / app2"

[1947] }

[1948] ]

[1949] }

[1950] Step 10:

[1951] The terminal parses the JSON data received from the server. Based on the analysis results, it prepares to display information about recommended applications in the user interface.

[1952] Step 11:

[1953] The device displays an application list to the user through its user interface. The user can view details of the recommended applications and obtain them using the download links.

[1954] This detailed process allows users to easily find the optimal application based on their interests, personality, and emotions.

[1955] (Example 2)

[1956] 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".

[1957] Traditional recommendation systems are limited to recommending applications based on user interests and personality traits, lacking recommendations that take user emotions into account. This resulted in users not receiving recommendations that matched their current emotional state, making it difficult to improve user satisfaction.

[1958] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting information about the user's areas of interest and personality, means for collecting the input information for analysis, and means for analyzing the collected data in real time and identifying the user's emotions. This makes it possible to recommend the most suitable application based on the user's interests, personality, and real-time emotion analysis.

[1959] A "user" refers to an individual who uses the system to input information about their areas of interest and personality, and receives recommendations for applications.

[1960] "Areas of interest" refers to the categories or themes that the user is interested in.

[1961] "Personality" refers to a user's behavioral patterns and psychological characteristics, and is used in systems to capture the user's preferences.

[1962] "Means of inputting information" refers to interfaces or devices that allow users to provide data about their interests and personality to a system.

[1963] "Means of collecting information for analysis" refers to devices and systems that collect user-input data internally and further collect real-time sentiment data.

[1964] "Means of identifying emotions" refers to algorithms and devices that analyze collected data such as voice and facial expressions to identify the user's current emotional state.

[1965] A "server" refers to a computer system that receives information and sentiment analysis results entered by users, and then analyzes and processes them.

[1966] A "database" refers to a storage device or system used to store and manage application information that corresponds to a user's areas of interest, personality, and emotions.

[1967] "Means for selecting the optimal software" refers to algorithms and devices that allow a server to select the most suitable application from a database based on user input information and sentiment analysis results.

[1968] "Means for transmitting software information to a terminal" refers to communication methods and protocols for transmitting detailed information about a selected application to the user's terminal.

[1969] "Means for displaying software information" refers to interfaces or devices that visually present and display detailed information about applications received on a user's terminal.

[1970] "Tagging" refers to the technique of assigning specific categories or attributes to applications to facilitate organization and searching.

[1971] A "list" refers to a format that compiles information on multiple selected applications into a single entity.

[1972] "Detailed information" refers to supplementary information that helps users understand the application, such as the application's name, description, and download link.

[1973] Specific embodiments of this invention will now be described. The program of this system takes user input information about their areas of interest and personality, and recommends appropriate applications based on that information. Furthermore, by combining it with an emotion engine, it also provides recommendations based on the user's emotions.

[1974] First, users use a device such as a smartphone or PC to input information about their areas of interest and personality through a dedicated application or web interface. For example, a user might input information such as "music" and "adventure-loving."

[1975] Next, the device is equipped with a microphone and camera, which collect voice and facial expression data while the user is entering information. The emotion engine analyzes this data in real time to identify the user's emotions. For example, if the user is smiling while speaking, the emotion engine will identify the emotion as "joy."

[1976] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. A secure protocol (e.g., HTTPS) is used for this. The server parses the received JSON data to identify the user's areas of interest, personality, and emotions. For example, it might parse JSON data like the following:

[1977] json

[1978] {

[1979] "interest": "music",

[1980] "personality": "adventurous",

[1981] "emotion": "joy"

[1982] }

[1983] Next, the server searches the database and selects the most suitable application based on the user's input information and sentiment analysis results. The database categorizes applications by interest, personality, and sentiment tags. For example, it searches for applications tagged with "music," "adventure," and "joy." At this point, applications such as "adventure music app" or "live music event participation app" may be selected.

[1984] The server generates a list of suitable applications from the search results, converts this list to JSON format, and sends it to the terminal. The list includes detailed information such as the application name, description, and download link. The terminal parses the received application information and displays it in the user interface. The user can browse the list of recommended applications and view detailed information. This allows the user to easily find the best application based on their interests, personality, and real-time emotions.

[1985] As a concrete example, the user opens an application on their device and enters their area of ​​interest, "music," and their personality, "adventurous." While the user is entering the information, the emotion engine analyzes their voice and facial expressions and detects that the user is experiencing the emotion of "joy." The device formats the input data and emotion analysis results and sends them to the server. The server performs the analysis and retrieves "music," "adventurous," and "joy" from the user's data. The server searches its database and finds the corresponding "adventure music app." The server generates a list of these apps and sends it to the device. The device displays the received information to the user, who can then review the details and install the application.

[1986] Examples of prompt statements include the following forms:

[1987] "Users use their smartphones to input information about their interests and personality, and an emotion engine analyzes their emotions in real time. For example, if they input 'music' and 'adventure,' it will indicate a feeling of joy. The device then sends the input data and analysis results to a server, which selects and recommends the most suitable applications to the user."

[1988] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1989] Step 1:

[1990] The system uses a means for users to input information about their areas of interest and personality. Specifically, users enter information such as "music" or "adventure-loving" into input fields on their smartphone or PC. The entered information is then passed to the system (input data: areas of interest, personality).

[1991] Step 2:

[1992] The device collects the input information for analysis. In this process, it uses its microphone and camera to collect the user's voice and facial expression data. For example, suppose the camera captures a scene where the user is smiling and talking while inputting data (input data: areas of interest, personality, voice data, facial expression data).

[1993] Step 3:

[1994] The emotion engine built into the device analyzes collected voice and facial expression data in real time to identify the user's emotions. Specifically, it uses an emotion recognition algorithm to identify emotions such as "joy" from voice tone and facial expressions (input data: voice data, facial expression data; output data: emotion).

[1995] Step 4:

[1996] The device formats the user's entered areas of interest and personality information, along with the sentiment analysis results, into JSON format. For example, it might be formatted as follows:

[1997] json

[1998] {

[1999] "interest": "music",

[2000] "personality": "adventurous",

[2001] "emotion": "joy"

[2002] }

[2003] Then, this JSON data is sent to the server as a secure HTTP request (input data: areas of interest, personality, emotions; output data: JSON data).

[2004] Step 5:

[2005] The server parses the received JSON data. Specifically, the server parses the received data, stores each part in an internal variable, and records it in the debug log (input data: JSON data, output data: areas of interest, personality, emotions).

[2006] Step 6:

[2007] The server searches the database based on the analyzed interests, personality, and emotions to select the most suitable software. For example, it might execute a database query to find applications that match "music," "adventurous," and "joy" (input data: interests, personality, emotions; output data: software list).

[2008] Step 7:

[2009] The server generates a list of the found software and converts it into JSON format as a list containing detailed descriptions. For example, it may look like this:

[2010] json

[2011] {

[2012] "recommendations": [

[2013] {

[2014] "name": "Adventure Music App",

[2015] "Description": "An app for enjoying the latest adventure music."

[2016] "link": "http: / / example.com / app1"

[2017] },

[2018] {

[2019] "name": "Live music event participation app",

[2020] "Description": "An app that makes it easy to participate in live music events held in your neighborhood."

[2021] "link": "http: / / example.com / app2"

[2022] }

[2023] ]

[2024] }

[2025] Then, this JSON data is sent to the terminal as an HTTP response (input data: software list, output data: JSON data).

[2026] Step 8:

[2027] The terminal parses the received JSON data and displays it on the user interface. Specifically, it visually presents the application name, description, and download link (input data: JSON data, output data: user interface display). Based on the displayed information, the user can check detailed information and install the application by clicking the download link.

[2028] (Application Example 2)

[2029] 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".

[2030] Traditional content recommendation systems primarily rely on user interests and personality traits, and none have taken real-time emotions into account. Therefore, they fail to recommend content that matches the user's current emotional state, resulting in low user satisfaction.

[2031] 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.

[2032] In this invention, the server includes means for inputting information about the user's areas of interest and personality; means for collecting emotional data in real time using an emotional engine that analyzes the input information and the user's emotions; means for transmitting the input information and emotional data to the server; means for the server to analyze the received information and select the most suitable content from a database; means for transmitting information about the selected content to a terminal; and means for displaying the transmitted content information to the user. This enables real-time content recommendations that take the user's emotions into account.

[2033] "User" refers to consumers or users who use the system to input information about their areas of interest and personality.

[2034] "Areas of interest" refers to specific categories or themes that the user is interested in.

[2035] "Personality" refers to a user's personal characteristics and preferences.

[2036] An "emotion engine" refers to a technology that analyzes a user's voice and facial expression data to identify their emotions in real time.

[2037] "Emotional data" refers to information that quantifies or stringifies the user's emotional state as analyzed by the emotion engine.

[2038] A "server" refers to a computer system that receives and analyzes information sent by users.

[2039] A "database" refers to a storage device or system in which a server stores information about applications and content.

[2040] "Content" refers to information and media that users can enjoy, such as movies, music, videos, and podcasts.

[2041] "Recommendation" refers to the act of selecting and presenting the most suitable content based on the user's areas of interest, personality, and emotional data.

[2042] A "terminal" refers to a device used by a user to input information, such as a smartphone or smart glasses.

[2043] "Display" refers to the act of visually presenting content or recommendation results on a device's screen.

[2044] This invention is a system that recommends optimal content based on the user's areas of interest, personality, and real-time sentiment data. The system provides means for the user to input information about their areas of interest and personality, and for collecting and analyzing sentiment data using a sentiment engine.

[2045] System-wide configuration

[2046] 1. User input means

[2047] Users input information about their interests and personality through a dedicated application using devices such as smartphones or smart glasses. For example, a user might input "horror movies" and "adventure lover."

[2048] 2. Collection and analysis of emotional data using an emotion engine

[2049] The emotion engine uses the microphone and camera built into the device to collect the user's voice and facial expressions, and analyzes their emotions in real time. For example, it can detect the emotion of "excitement."

[2050] 3. Transmission method

[2051] The terminal formats the information entered by the user and the sentiment analysis results obtained from the sentiment engine into JSON format and sends it to the server as an HTTP request. This step uses a secure protocol to protect the data.

[2052] 4. Server-based analysis and selection methods

[2053] The server analyzes the received JSON data to identify the user's areas of interest, personality, and emotions. Based on this data, the server searches a database and selects the most suitable content based on the user's input and the emotion analysis results. For example, "horror adventure movies" or "adventure podcasts."

[2054] 5. Result generation and transmission means

[2055] The server generates a list of relevant content from the search results, converts it back to JSON format, and sends it to the terminal. The generated list includes detailed information such as the content name, description, and links.

[2056] 6. Display means

[2057] The terminal analyzes content information received from the server and displays it on the user interface. Users can view a list of recommended content and check detailed information.

[2058] Hardware and software to be used

[2059] Hardware:

[2060] The devices include smartphones and smart glasses. These devices are equipped with microphones and cameras and are used to collect emotional data.

[2061] software:

[2062] The frontend uses React to build the user interface, while the backend uses Node.js and Express for server-side processing. Additionally, an emotion engine analyzes speech and facial expressions, utilizing image recognition and natural language processing algorithms.

[2063] Explanation of specific examples

[2064] For example, if a user enters "horror movies" and "adventure lover" through a smartphone app, and the sentiment analysis identifies this as "excited," that information will be sent to the server in the following JSON format:

[2065] json

[2066] {

[2067] "interest": "Horror movies",

[2068] "personality": "adventurous",

[2069] "emotion": "excitement"

[2070] }

[2071] The server analyzes this data and selects content such as "horror adventure movies" and "adventure podcasts" from the database. This result is sent to the device and displayed visually to the user.

[2072] Example of a prompt

[2073] A user entered "horror movies" and "adventure" through a smartphone app, and sentiment analysis identified their mood as "excited." Please use this data to recommend appropriate content. For example, we expect responses like the following:

[2074] Horror Adventure Movie: An exciting film where horror and adventure intertwine.

[2075] Adventure Podcasts: Podcasts that will awaken your adventurous spirit.

[2076] As a result, users can smoothly find content that suits their interests and personality, while also taking their real-time emotions into consideration.

[2077] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2078] Step 1:

[2079] The user opens the smartphone app and enters their areas of interest (e.g., "horror movies") and personality traits (e.g., "adventurous"). The data entered at this point is information about the user's interests and personality.

[2080] Step 2:

[2081] As the user completes their input, the device's emotion engine analyzes their voice and facial expressions to identify their real-time emotions (e.g., "excitement"). This analysis is performed using an emotion analysis algorithm based on the collected audio and video data. The output data is then tagged with emotion tags.

[2082] Step 3:

[2083] The terminal formats the user's input information on areas of interest and personality, along with the sentiment data analyzed by the sentiment engine, into JSON format and sends it to the server using an HTTP POST request. The input data consists of the user's interests, personality, and sentiment, while the output data is a request in JSON format.

[2084] Step 4:

[2085] The server receives JSON data sent from the terminal. It parses the received input data and divides it into individual data items (interests, personality, emotions). The output data consists of these parsed data items.

[2086] Step 5:

[2087] The server searches the database based on the analyzed data items and selects the most suitable content that matches the user's interests, personality, and emotions. This selection uses a database where content information is pre-tagged. The input data consists of segmented data items, and the output data is a list of recommended content.

[2088] Step 6:

[2089] The server generates a list of selected content, converts it back into JSON format, and sends it to the terminal. This list includes content names, descriptions, links, etc. The input data is the recommended content list, and the output data is a JSON response.

[2090] Step 7:

[2091] The terminal parses the received JSON-formatted content information and displays it on the user interface. Based on this displayed information, the user can select content and view detailed information. The input data is a JSON-formatted response, while the output data is a visually represented content information.

[2092] 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.

[2093] 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.

[2094] 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.

[2095] 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.

[2096] 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.

[2097] 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.

[2098] 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.

[2099] 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.

[2100] 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."

[2101] 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.

[2102] 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.

[2103] 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.

[2104] 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.

[2105] 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.

[2106] 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.

[2107] 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.

[2108] 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.

[2109] 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.

[2110] 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.

[2111] 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.

[2112] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[2113] The following is further disclosed regarding the embodiments described above.

[2114] (Claim 1)

[2115] A means for users to input information about their areas of interest and personality,

[2116] A means of sending the input information to the server,

[2117] A means of analyzing the information received by the server and selecting the optimal application from the database,

[2118] A means of sending information about the selected application to the terminal,

[2119] A system that includes means for displaying transmitted application information to the user.

[2120] (Claim 2)

[2121] The system according to claim 1, wherein the analysis means includes means for tagging and matching applications based on the user's areas of interest and personality.

[2122] (Claim 3)

[2123] The system according to claim 1, comprising means for generating a list of selected applications and including detailed information thereof.

[2124] "Example 1"

[2125] (Claim 1)

[2126] A means for users to input information about their areas of interest and personality,

[2127] A means of converting the input information into a data format and sending it to the server,

[2128] A means for analyzing the information received by the server and selecting the most suitable software from the database based on the user's areas of interest and personality,

[2129] A means for generating a list of selected software, converting it into a data format containing detailed information, and sending it to a terminal,

[2130] A system that includes means for displaying transmitted software information to the user.

[2131] (Claim 2)

[2132] The system according to claim 1, wherein the analysis means includes means for classifying software based on the user's areas of interest and personality.

[2133] (Claim 3)

[2134] The system according to claim 1, comprising means for generating a list of selected software and including detailed information thereof.

[2135] "Application Example 1"

[2136] (Claim 1)

[2137] A means for users to input information about their areas of interest and personality,

[2138] A means of sending the input information to the server,

[2139] A means of analyzing the information received by the server and selecting the optimal software from the database,

[2140] A means of transmitting information about the selected software to the terminal,

[2141] A means of displaying transmitted software information to the user,

[2142] A means of providing personalized security measures based on user input information,

[2143] A means including a smart device that provides security information visually in real time,

[2144] A system that includes this.

[2145] (Claim 2)

[2146] The system according to claim 1, wherein the analysis means includes means for tagging and matching software based on the user's areas of interest and personality.

[2147] (Claim 3)

[2148] The system according to claim 1, comprising means for generating a list of selected software and including detailed information thereof.

[2149] "Example 2 of combining an emotion engine"

[2150] (Claim 1)

[2151] A means for users to input information about their areas of interest and personality,

[2152] A means of collecting input information for analysis,

[2153] A means to analyze the collected data in real time and identify the user's emotions,

[2154] A means for sending the analyzed information to the server,

[2155] A means of analyzing the information received by the server and selecting the optimal software from the database,

[2156] A means of transmitting information about the selected software to the terminal,

[2157] A system that includes means for displaying transmitted software information to the user.

[2158] (Claim 2)

[2159] The system according to claim 1, wherein the analysis means includes means for tagging and matching software based on the user's areas of interest, personality, and emotions.

[2160] (Claim 3)

[2161] The system according to claim 1, comprising means for generating a list of selected software and including detailed information thereof.

[2162] "Application example 2 when combining with an emotional engine"

[2163] (Claim 1)

[2164] A means for users to input information about their areas of interest and personality,

[2165] A means for collecting emotional data in real time using an emotion engine that analyzes input information and user emotions,

[2166] Means for transmitting input information and sentiment data to a server,

[2167] A means of analyzing the information received by the server and selecting the most suitable content from the database,

[2168] A means of transmitting information about selected content to the terminal,

[2169] A system that includes means for displaying transmitted content information to the user.

[2170] (Claim 2)

[2171] The system according to claim 1, wherein the analysis means includes means for tagging and matching content based on the user's areas of interest, personality, and emotions.

[2172] (Claim 3)

[2173] The system according to claim 1, comprising means for generating a list of selected content and including detailed information thereof. [Explanation of Symbols]

[2174] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input information about their areas of interest and personality, A means of sending the input information to the server, A means of analyzing the information received by the server and selecting the optimal application from the database, A means of sending information about the selected application to the terminal, A system that includes means for displaying transmitted application information to the user.

2. The system according to claim 1, wherein the analysis means includes means for tagging and matching applications based on the user's areas of interest and personality.

3. The system according to claim 1, comprising means for generating a list of selected applications and including detailed information thereof.

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