system

Abstract

Provide a system. The method includes: receiving a text message sent by a user from a communication terminal; A means for connecting to the database and verifying or registering user information; means for selecting an appropriate message within a predefined category based on a user request; means for formatting and transmitting the selected message to the communication terminal; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the 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] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] For students and other test-takers, maintaining motivation is an important issue when continuing to study for long periods of time. However, studying alone can be lonely, which can lead to a decline in motivation. Conventional methods have limited the means by which test-takers can maintain their own motivation, and in particular, there is a lack of means to provide encouraging and uplifting messages that provide emotional support. This has made it difficult for them to receive encouragement from outside at the right time. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. First, a server is provided with means for receiving text messages sent by a user from a communication terminal. Next, the server is provided with means for connecting to a database and confirming or registering user information. Furthermore, the server is provided with means for selecting an appropriate message from a pre-defined category based on the user's request. This allows, for example, a quote from a famous person or an uplifting song to be appropriately selected. The server then provides means for formatting the selected message and sending it to the communication terminal. This allows the user to receive appropriate encouragement between study sessions and helps them maintain their motivation. Furthermore, by adding means for analyzing text messages sent by the user and extracting the requested content, more accurate message delivery becomes possible. In addition, by providing means for randomly selecting an appropriate message, a variety of messages can be provided to the user, allowing them to always receive fresh encouragement.

[0006] A "communication terminal" refers to a device that can send and receive data via the Internet or wireless communication.

[0007] "Text message" refers to a means of communication consisting of textual information, and refers to a message in a format that allows a user to input and send information.

[0008] "Means for receiving" refers to the functions and methods for taking in data sent from outside.

[0009] A "server" refers to a computer system that manages and processes data via a network and provides services to client terminals.

[0010] A "database" refers to a system that organizes and stores information in a format that allows it to be searched and updated.

[0011] "User information" refers to all data about a user, such as user identifiers, history, and settings.

[0012] "Means of selection" refers to the functions and methods for extracting a specific element from multiple options.

[0013] "Formatting means" refers to the functions and methods for converting data or messages into a specific format and outputting them.

[0014] A "request" refers to the content of information or services requested by a user.

[0015] An "appropriate message" refers to a message selected according to pre-defined criteria or conditions.

[0016] "Means for random selection" refers to a function or method for making random selections without setting any fixed criteria. [Brief explanation of the drawings]

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

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

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

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

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

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

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

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

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0034] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This invention is an automated LINE messaging tool that helps test-takers maintain their motivation to study. When a user sends a motivational request message via a communication device, the system selects an appropriate message and replies to the user.

[0039] The embodiment for implementing this system will be described below.

[0040] User operations

[0041] First, a user connects to the system using the LINE app. The user can enter any text message and press the send button. For example, a user can send a message such as, "I'm not motivated to study. Please send me a quote."

[0042] Server Processing

[0043] 1. Receiving a message

[0044] The server receives the text message sent by the user, along with the message data (user ID, content) from the LINE platform.

[0045] 2. User information confirmation and registration

[0046] The server accesses the database and checks the user information. If it is a first-time user, the user information is registered in the database. If it is an existing user, the server checks the past request history and settings.

[0047] 3. Parsing the Request

[0048] The server analyzes the content of the received message. For example, if the message contains a request such as "Please send me a quote," the system selects the "Quote" category.

[0049] 4. Message Selection

[0050] Based on the request, the server randomly or by a specific algorithm selects an appropriate message from pre-defined categories (e.g., famous quotes, uplifting lyrics, questions and answers).

[0051] 5. Message Formatting

[0052] The server formats the selected message into a format that can be sent via LINE. For example, it formats the famous quote, "Success comes from overcoming failure."

[0053] 6. Sending a Message

[0054] The server uses the LINE API to send the formatted message to the user's device.

[0055] Reply to the user

[0056] The user receives the message sent from the server through the LINE app. For example, the message "Success comes from overcoming failure" is displayed on the LINE app.

[0057] Specific examples

[0058] As a specific example, if a user sends a message saying, "I'm not motivated to study. Please send me some great quotes," the server will process the message as follows:

[0059] 1. Reception and Analysis

[0060] User ID: 12345

[0061] Request: "Please send me a quote."

[0062] 2. Verify your user information

[0063] Register as a new user and request a "quote."

[0064] 3. Select a message

[0065] Randomly select the message "Success comes from overcoming failure" from the "Quotes" category in the database.

[0066] 4. Formatting and sending

[0067] The selected message is formatted in LINE format and sent to user ID 12345.

[0068] 5. User receives

[0069] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[0070] In this way, the system sends appropriate messages to the user and helps them maintain their motivation to study.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] A user connects to the system using the LINE app, enters a text message, and presses the send button. For example, a user sends a message saying, "I'm not motivated to study. Please send me a quote."

[0074] Step 2:

[0075] The server receives the user's text message from the LINE platform. The received message data includes the user ID and the message content.

[0076] Step 3:

[0077] The server accesses the database and checks the user information. If it is a first-time user, the user ID and the details of the first request are registered in the database. If it is an existing user, the server checks the past request history and settings.

[0078] Step 4:

[0079] The server analyzes the content of the received message. For example, if the message contains a request to "send me a quote," the server selects the "Quote" category.

[0080] Step 5:

[0081] The server selects appropriate messages from a database based on the specified category. The messages are either randomly selected or extracted using a specific algorithm.

[0082] Step 6:

[0083] The server formats the selected message into a format that can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[0084] Step 7:

[0085] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained in step 2.

[0086] Step 8:

[0087] The user receives a message sent from the server through the LINE app. The message content is intended to motivate the user, such as "Success comes from overcoming failure."

[0088] Step 9:

[0089] Check the messages the user has received. For example, reading the message can make the user feel like, "Okay, let's try again!"

[0090] Example 1

[0091] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0092] In today's world, it is extremely difficult for students preparing for exams to maintain their motivation to study. In particular, when studying independently, there is a lack of timely encouragement or guidance, leaving students with limited means to maintain their sagging motivation. This results in a decline in learning efficiency and hinders the improvement of academic performance. To solve this problem, a method that is both easy for students to use and effective in maintaining their motivation is needed.

[0093] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0094] In this invention, the server includes: means for receiving text messages sent by users from their communication terminals; means for connecting to a database and confirming or registering user information; means for selecting an appropriate message from a preset category based on a user request; means for formatting the selected message and sending it to the communication terminal; means for adding identification information for identifying the user information; and means including an algorithm for randomly or specifically selecting an appropriate message from a specified category. This allows test-takers to always receive appropriate encouragement and guidance, thereby maintaining their motivation to study.

[0095] A "communication terminal" refers to an information communication device used by a user, and includes smartphones, tablets, personal computers, etc.

[0096] A "text message" is text information that a user sends through a communication terminal.

[0097] A "server" is a computing device that processes data received from a communication terminal and transmits necessary information.

[0098] A "database" is an information management system for storing user information and message contents.

[0099] "User information" refers to information about users of the system, including user IDs and request history.

[0100] A "request" is an action or information that a user requests from a system.

[0101] A "category" is a group of messages categorized according to the request content.

[0102] "Message formatting" refers to the act of converting a selected message into a format that can be sent.

[0103] "Identification information" refers to information for uniquely identifying a user.

[0104] An "algorithm" is a procedure or computational method for solving a particular problem.

[0105] "Random" means chosen at random without any set rules.

[0106] "Analysis" means detailed analysis of the content of received text messages.

[0107] The present invention is a LINE automatic messaging tool that helps test-takers maintain their motivation to study. When a user sends a request message to improve their motivation through a communication terminal, a server selects an appropriate message and sends it back to the user. A specific embodiment of the tool is described below.

[0108] Hardware and Software

[0109] The hardware and software required to implement the present invention are as follows:

[0110] Hardware:

[0111] 1. Communication devices: smartphones, tablets, computers, etc.

[0112] 2. Server: A high-performance computing device (e.g., cloud server, dedicated server).

[0113] software:

[0114] 1. LINE app: An application that allows users to send messages.

[0115] 2. Database Management System: A system for storing user information and message data (e.g., MySQL (registered trademark), PostgreSQL).

[0116] 3. Text analysis library: A library for analyzing the received message content (e.g., NLTK, SpaCy).

[0117] 4. Generative AI model: The AI ​​model used to select and shape appropriate messages (e.g., GPT-3®).

[0118] 5. LINE Platform API: API for receiving and sending messages through LINE.

[0119] Operation and processing flow

[0120] User operations

[0121] First, the user connects to the system using the LINE app installed on their device. The user can enter any text message and press the send button. For example, to send a message like this:

[0122] "I'm not motivated to study. Please send me some famous quotes."

[0123] Server Processing

[0124] 1. Receiving a message

[0125] The server receives text messages sent by users through the LINE Platform API. This data includes the user ID and message content.

[0126] 2. User information confirmation and registration

[0127] The server connects to the database and checks the user's information. If it is a first-time user, the server registers the user as a new user and saves the user ID and other basic information. If it is an existing user, the server reads and updates the user's past request history and settings.

[0128] 3. Parsing the Request

[0129] The server uses a text analysis library to analyze the content of the received message, for example, to extract the request content such as "Please send me a quote."

[0130] 4. Message Selection

[0131] The server selects appropriate messages from pre-defined categories (e.g., famous quotes, uplifting lyrics, questions and answers), using a generative AI model to select messages randomly or based on a specific algorithm.

[0132] 5. Message Formatting

[0133] The server formats the selected message into a format that can be sent in LINE format, and can also use a generative AI model to convert it into the appropriate format.

[0134] 6. Sending a Message

[0135] The server uses the LINE API to send the formatted message to the user's device. For example, the following message is sent:

[0136] "Success comes from overcoming failure." - Albert Einstein

[0137] Specific examples

[0138] For example, if a user uses a communication device to send a message to the LINE app saying, "I'm not motivated to study. Please send me some famous quotes.", the server processes the message as follows:

[0139] 1. Reception and Analysis

[0140] User ID: 12345

[0141] Request: "Please send me a quote."

[0142] 2. Verify your user information

[0143] The server registers the user as a new user and sets the request content as a "quote."

[0144] 3. Select a message

[0145] The server randomly selects the message "Success comes from overcoming failure" from the "Quotes" category in the database.

[0146] 4. Formatting and sending

[0147] The selected message is formatted in LINE format and sent to user ID 12345.

[0148] 5. User Reception

[0149] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[0150] This system helps test takers maintain their motivation to study by automatically replying to users with appropriate messages.

[0151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0152] Step 1:

[0153] Receiving messages

[0154] Specific operation: The user uses a communication device to type a message into the LINE app. The user presses the send button to send a message such as, "I'm not motivated to study. Please send me a quote."

[0155] Input: The text message entered by the user into the LINE app.

[0156] Output: Message data (user ID, message content) received by the server via the LINE Platform API.

[0157] Processing content: The server receives message data using the LINE API and temporarily stores it.

[0158] Step 2:

[0159] User information confirmation and registration

[0160] Specific operation: The server connects to the database and searches for user information using the received user ID as a key.

[0161] Input: Received user ID.

[0162] Output: User information in the database or registration of new user information.

[0163] Processing content: The server checks the user information in the database, and if it is a new user, it registers the user ID and basic information in the database. If it is an existing user, it reads the past request history and settings.

[0164] Step 3:

[0165] Parsing the request

[0166] What happens: The server uses a text analysis library (e.g., NLTK or SpaCy) to parse the received message.

[0167] Input: Received text message content.

[0168] Output: Request details (specific category).

[0169] Processing details: The server performs text analysis, extracts the user's request from the message content, and classifies the request into one of three categories: "famous quote," "uplifting lyrics," or "question and answer."

[0170] Step 4:

[0171] Message Selection

[0172] What happens: The server connects to the database and selects messages from the appropriate category.

[0173] Input: Parsed request content (category).

[0174] Output: The selected message.

[0175] What it does: The server randomly or algorithmically selects the best message from a specified category. It may also use a generative AI model (e.g., GPT-3) to select the message. For example, it selects the message "Success comes from overcoming failure" from the "Quotes" category.

[0176] Step 5:

[0177] Message Formatting

[0178] Specific operation: The server formats the selected message into a format that can be sent in LINE format.

[0179] Input: The selected message.

[0180] Output: The formatted message.

[0181] Processing: The server uses a formatting function to format the selected message. It may also input a prompt to the generative AI model to generate the formatted result.

[0182] Step 6:

[0183] Sending a message

[0184] Specific operation: The server sends the formatted message to the user.

[0185] Input: A formatted message and a user ID.

[0186] Output: The message that is displayed on the user's communication terminal.

[0187] Processing content: The server uses the LINE API to send the formatted message to the user's communication device. For example, the message "Success comes from overcoming failure" is displayed in the user's LINE app.

[0188] (Application example 1)

[0189] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0190] Modern food delivery services provide users with the convenience of ordering, but unique and value-added services are required. Furthermore, if users lack motivation or psychological support, their quality of life may decline. It is necessary to solve this issue and provide more value-added food delivery services to improve the user experience.

[0191] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0192] In this invention, the server includes means for receiving text messages sent by users from their communication terminals, means for connecting to a database and confirming or registering user information, means for selecting an appropriate message from a preset category based on a user request, means for formatting the selected message and sending it to the communication terminal, means for providing motivational messages to users when ordering food delivery, and means for automatically translating messages in multiple languages ​​and displaying them in a way that suits the user interface. This allows users to receive mental support when ordering food delivery, thereby improving their quality of life.

[0193] A "communication terminal" is a device that allows a user to send and receive messages, such as a smartphone or tablet.

[0194] A "database" is an information management system that stores user information, message data, etc., and can retrieve and update them as needed.

[0195] "Request" refers to an instruction or request sent by a user through a communication terminal to receive a motivation message, etc.

[0196] "Predefined categories" are categories into which motivational messages are categorized, and include different themes such as quotes, personal experiences, and encouragement.

[0197] "Formatting" refers to the process of formatting a selected message for proper display on a communications terminal.

[0198] "Food delivery" refers to a service that delivers food from restaurants to a location specified by the user.

[0199] "Motivational messages" are messages intended to improve the user's mental motivation, and include famous quotes, words of encouragement, success stories, and the like.

[0200] "Multilingual" refers to the ability to accommodate different languages ​​and provide messages in the user's language of choice.

[0201] "Automatic translation" means the process of converting a message written in one language into another language.

[0202] A "user interface" refers to the screens and operating methods that allow a user to interact with an application, and is designed to enhance user convenience.

[0203] The system for implementing this invention allows users to receive motivational messages when placing an order in a food delivery service. This system is composed of the following main components:

[0204] First, a user accesses a food delivery application using a communication terminal (e.g., a smartphone or tablet) and orders food. The communication terminal then sends the user's request along with order information to the server.

[0205] The server processes the transaction using the following means:

[0206] 1. Receiving means:

[0207] The server receives a text message sent by the user from the communication terminal, the message including the category of motivation message requested by the user.

[0208] 2. Database connection method:

[0209] The server connects to the database to check user information and register new user information if necessary. For existing users, it checks past request history and settings.

[0210] 3. Message selection method:

[0211] Based on the user's request, the server selects an appropriate message from pre-defined categories (e.g., quotes, experiences, encouragement).

[0212] 4. Shaping means:

[0213] Formats the selected message for proper display on the communication device, and automatically translates the message into the user's preferred language if multilingual support is available.

[0214] 5. Motivational message delivery methods:

[0215] The formatted message is provided to users through the food delivery order confirmation screen or messaging apps such as LINE.

[0216] 6. Multilingual support methods:

[0217] The message is automatically translated and displayed appropriately in the language displayed on the user's communication terminal.

[0218] As a concrete example, we will explain the process when a user requests a "success story." When a user places an order on a food delivery application and requests a "success story," this information is sent from the communication terminal to the server. The server randomly selects a message that falls into the "success story" category from the database, formats it, and automatically translates it into the user's language. The selected message is then sent to the user via LINE. The user's LINE will display the message "How I passed my university entrance exam..."

[0219] Example prompt:

[0220] User ID: 12345

[0221] Category: "Success Stories"

[0222] The hardware used is mainly smartphones and tablets, and the software used is LINE Messaging API, Python 3.6+, and the required json and random modules. This system allows users to receive mental support when ordering food delivery, improving their quality of life.

[0223] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0224] Step 1:

[0225] A user selects a dish and places an order in a food delivery app.

[0226] Input: User order information and motivation message category request

[0227] Specific operation: The user uses a communication terminal to order food and drink, and at the end, enters the category of the motivational message (e.g., "famous quote") into the request form.

[0228] Step 2:

[0229] The communication terminal transmits the order information and request data to the server.

[0230] Input: User's order information and category request

[0231] Output: Order information and category request data sent to the server

[0232] Specific operation: Once the order is confirmed, the communication terminal sends the input information, including the user ID, order details, and requested category, to the server.

[0233] Step 3:

[0234] The server checks the user information in the database and registers the user if he is a new user.

[0235] Input: User ID

[0236] Output: User information confirmation result, new registration or existing confirmation

[0237] Specific operation: The server accesses the database and checks the user information based on the user ID. If it is a first-time user, the user information is newly registered in the database.

[0238] Step 4:

[0239] The server analyzes the user's request and selects the appropriate category of message.

[0240] Input: Request content (e.g. "Famous quote")

[0241] Output: An appropriate message (e.g., "Success comes from overcoming failure.")

[0242] Specific operation: The server analyzes the request content and randomly selects messages within a pre-defined category from a database.

[0243] Step 5:

[0244] The selected message is formatted so that it can be displayed appropriately on the communication terminal.

[0245] Input: Selected message

[0246] Output: Formatted message

[0247] Specific operation: The server formats the selected message to match the LINE format or application display format, and if multilingual, automatically translates it into the user's language.

[0248] Step 6:

[0249] The formatted message is sent from the server to the communication terminal.

[0250] Input: Formatted message

[0251] Output: Message sent to the user's communication device

[0252] Specific operation: The server uses the LINE Messaging API to send the formatted message to the user's LINE account or application.

[0253] Step 7:

[0254] The user checks the message received on the communication terminal.

[0255] Input: Received message

[0256] Output: User confirmation

[0257] Specific actions: The user opens the message received on the communication device, checks the contents, and receives encouragement and motivation.

[0258] Through each step, users can receive psychological support when using food delivery services and improve their quality of life.

[0259] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0260] This system receives text messages sent by users through the LINE app, analyzes the message content and emotions, and automatically replies with appropriate encouraging or uplifting messages. Furthermore, the system stores the user's emotional history in a database and reflects this in the next message selection, providing a more personalized service.

[0261] User operations

[0262] First, the user connects to the system using the LINE app. For example, the user types a text message such as "I'm not motivated to study. Please send me a quote," and presses the send button.

[0263] Server Processing

[0264] 1. Receiving a message

[0265] The server receives the user's text message from the LINE platform. The received message contains the user ID and message content.

[0266] 2. User information confirmation and registration

[0267] The server accesses the database and checks the user information. If the user is using the service for the first time, the user ID and the details of the first request are registered in the database. If the user is an existing user, the server checks the past request history and settings.

[0268] 3. Parsing the Request

[0269] The server analyzes the content of the received text message. For example, if the message contains a request to "send me a quote," the system selects the "Quotes" category.

[0270] 4. Analysis by Emotion Engine

[0271] The emotion engine installed on the server analyzes the emotions in the user's text message. Based on this analysis, it selects a message from a category that matches the user's current emotion. For example, if the user is feeling unmotivated, an encouraging message will be selected.

[0272] 5. Message Selection

[0273] The server selects an appropriate message from a database based on the user's sentiment and request, which can be chosen randomly or extracted by a specific algorithm.

[0274] 6. Message Formatting

[0275] The server formats the selected message so that it can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[0276] 7. Sending a Message

[0277] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained initially.

[0278] 8. Emotional history storage

[0279] The server stores the results of the user's emotion analysis and the sent message in a database, allowing the user's emotion history to be used as a reference when selecting a message next time.

[0280] Reply to the user

[0281] The user receives a reply message from the server through the LINE app. For example, a famous quote such as "Success comes from overcoming failure" is displayed in the user's LINE app.

[0282] Specific examples

[0283] As a specific example, if a user sends a message saying, "I'm not motivated to study. Please send me some famous quotes," the server will process it as follows:

[0284] 1. Reception and Analysis

[0285] User ID: 12345

[0286] Request: "Please send me a quote."

[0287] 2. Verify your user information

[0288] Register as a new user and confirm your request.

[0289] 3. Emotion analysis

[0290] Extract the emotion of "lack of motivation" from the message.

[0291] 4. Message Selection

[0292] From the database, select the message "Success comes from overcoming failure" from the "famous quotes" category that is appropriate for the state of "lack of motivation."

[0293] 5. Formatting and sending

[0294] The selected message is formatted in LINE format and sent to user ID 12345.

[0295] 6. Emotion history storage

[0296] The user's sentiment analysis results and the sent message are stored in a database.

[0297] 7. User receives and confirms

[0298] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[0299] In this way, the present invention provides users with an effective means of receiving messages optimized for their emotions and maintaining their motivation to study, thereby enabling personalized support tailored to the needs of each individual user.

[0300] The processing flow will be explained below.

[0301] Step 1:

[0302] A user connects to the system using the LINE app. The user types a text message and presses the send button. For example, the user sends a message saying, "I'm not motivated to study. Please send me a quote."

[0303] Step 2:

[0304] The server receives the user's text message from the LINE platform. The received message data includes the user ID and the message content.

[0305] Step 3:

[0306] The server accesses the database and checks the user information. If the user is a new user, the user ID and the details of the first request are registered in the database. If the user is an existing user, the server checks the past request history and settings.

[0307] Step 4:

[0308] The server analyzes the content of the received message. For example, if the message contains a request to "send me a quote," the server selects the "Quote" category.

[0309] Step 5:

[0310] The emotion engine installed on the server analyzes the user's text messages and recognizes their emotions, such as "unmotivated" or "tired."

[0311] Step 6:

[0312] The server selects a message from a category that matches the user's current emotion based on the analysis results of the emotion engine. For example, if the user is feeling unmotivated, an encouraging message will be selected.

[0313] Step 7:

[0314] The server selects appropriate messages from the database based on the sentiment analysis results and the user's request. The messages are either randomly selected or extracted using a specific algorithm.

[0315] Step 8:

[0316] The server formats the selected message into a format that can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[0317] Step 9:

[0318] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained in step 2.

[0319] Step 10:

[0320] The user receives the message sent from the server through the LINE app. For example, the message "Success comes from overcoming failure" is displayed on the LINE app.

[0321] Step 11:

[0322] The user checks the messages they receive. For example, they read the message and feel like, "Okay, let's try again!"

[0323] Step 12:

[0324] The server stores the user's emotion analysis results and the sent message in a database, allowing the server to refer to the user's emotion history when selecting a message next time.

[0325] Example 2

[0326] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0327] Conventional message response systems often use standardized replies without considering the user's emotions, making it difficult to provide appropriate messages that reflect the user's situation and mood. As a result, users are not fully satisfied, and the system's usability is reduced. In addition, the lack of a function to save the user's emotional history means that the next time a message is selected, a non-personalized response may be sent.

[0328] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving a text message sent by a user from a communication terminal, a means for connecting to a database and confirming or registering user information, a means for selecting an appropriate message from a preset category based on a user request, a means for formatting the selected message and sending it to the communication terminal, a means for analyzing emotions from the user's text message, and a means for saving the emotion analysis result in the database. This makes it possible to provide a message optimized for the user's emotions and to realize a personalized service by using the user's emotion history for the next message selection.

[0329] A "communication terminal" is a device that a user uses to send and receive text messages, and includes smartphones, tablets, personal computers, etc.

[0330] A "text message" is information in the form of text that a user sends via a communication terminal.

[0331] A "database" is a system that systematically stores and manages data such as user information, messages, and emotion analysis results.

[0332] "Sentiment analysis" is the process of identifying and assessing a user's current emotions from a text message.

[0333] "Message selection" refers to extracting the most suitable message from a pre-defined category based on the user's request and sentiment.

[0334] "Message formatting" refers to converting a selected message into a format suitable for transmission to a communication terminal.

[0335] "Emotion history" is data that records the results of a user's emotion analysis and related messages in chronological order.

[0336] This system receives text messages sent by users through communication applications, analyzes the content and emotions of the messages, and automatically replies with appropriate encouraging or uplifting messages. It also stores the user's emotional history in a database and reflects this in the next message selection, providing a more personalized service.

[0337] User operations

[0338] First, the user connects to the system using a communication application. For example, the user types a text message such as "I'm not motivated to study. Please send me a quote," and presses the send button. This message is then sent via a platform such as LINE. At this point, the user does not need to perform any particularly complicated settings or operations; the system works simply by sending a message as usual.

[0339] Hardware and software used

[0340] server

[0341] The server is mainly configured using the following hardware and software:

[0342] Hardware:

[0343] A server machine with high-speed internet connection

[0344] High-performance processor and sufficient memory capacity

[0345] software:

[0346] LINE Messaging API: Used to receive and reply to text messages

[0347] MySQL or PostgreSQL: A database that stores user information and emotion history

[0348] IBM Watson® and Google® Cloud Natural Language API: Natural language processing engines for sentiment analysis

[0349] Python and Node.js: the main implementation languages ​​for the program

[0350] Server Processing

[0351] When the server receives a text message sent by a user through a communication application (e.g., LINE), it analyzes it and generates an appropriate reply message. The server first extracts the user ID and message content from the received message. It then accesses a database to confirm or register the user's information. If the user is not registered, the server records the user ID and the content of the initial request in the database.

[0352] The server then analyzes the content of the text message to identify the user's request and emotion. For example, a request such as "Please send me a quote" would be assigned to the "Quote" category. Sentiment analysis also identifies the user's emotional state as "unmotivated."

[0353] The server then selects an appropriate message from its database based on the user's emotions and requests. The selected message is then formatted by the server again and sent back to the user's device. This entire process is automated, and the user waits again until they receive the reply message in the LINE app.

[0354] Specific examples

[0355] As a concrete example, consider the case where a user sends a message saying, "I'm not motivated to study. Please send me some famous quotes." When this message arrives at the server, the server processes it as follows:

[0356] 1. The server receives the message via the LINE Messaging API and extracts the user ID and text content.

[0357] 2. The server accesses the database and registers the user as a new user or checks for an existing user.

[0358] 3. The server analyzes the content of the text message using a natural language processing engine to identify the request and sentiment.

[0359] 4. The server selects a message from the database that best matches the user's emotion.

[0360] 5. The server formats the selected message for transmission to the communication terminal.

[0361] 6. Finally, the user sentiment analysis results and the sent message are stored in the database.

[0362] For example, in response to a prompt message sent by a user such as "I'm not motivated to study. Please send me a quote," the reply message displayed on the user's communication device is "Success comes from overcoming failure." In this way, the system can continue to provide personalized services to users by using the emotion history when selecting the next message.

[0363] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0364] Step 1:

[0365] The server receives text messages sent by users using the API of a communication application (for example, the LINE Messaging API). The input is the user ID and message content, and the output is the received message data. Specifically, the message data is sent to the server by Webhook via an HTTP POST request from the LINE platform.

[0366] Step 2:

[0367] The server accesses the database and verifies or registers the user's information. The input is the user ID and text content received in step 1, and the output is a record of the user information. Specifically, it queries the database (MySQL or PostgreSQL) for existing user information, and if it is a new user, it records the user ID and the content of the initial request.

[0368] Step 3:

[0369] The server analyzes the received text message to identify the user's request. The input is the message content received in step 1, and the output is the classification result of the request. Specifically, a natural language processing library (e.g., NLTK or spaCy) is used to extract keywords from the text and analyze the request.

[0370] Step 4:

[0371] The server analyzes emotions from text messages. The input is the message content received in step 1, and the output is the emotion analysis result. Specifically, it uses a natural language understanding API (e.g., IBM Watson or Google Cloud Natural Language) to identify and evaluate emotions from text.

[0372] Step 5:

[0373] The server selects an appropriate message from the database based on the user request and the results of sentiment analysis. The input is the analysis results from steps 3 and 4, and the output is the selected message. Specifically, it searches the database for messages that match the request and sentiment, and randomly selects one if necessary.

[0374] Step 6:

[0375] The server formats the selected message for transmission to the communication terminal. The input is the message selected in step 5, and the output is the formatted message data. Specifically, the message is converted into an appropriate transmission format such as JSON format.

[0376] Step 7:

[0377] The server sends the formatted message to the user's communication device using the communication application's API (for example, the LINE Messaging API). The input is the message data formatted in step 6, and the output is the transmission result. Specifically, the message is sent using the API's push method.

[0378] Step 8:

[0379] The server stores the user's emotion analysis results and the sent message in a database. The input is the data from steps 1, 4, and 5, and the output is the updated user emotion history. Specifically, the emotion analysis results and the sent message content are recorded in the corresponding tables in the database.

[0380] (Application example 2)

[0381] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0382] In modern society, users' stress, anxiety, and lack of motivation are becoming common problems. This creates a need for timely and encouraging messages. However, current systems have difficulty fully understanding a user's emotional state and recommending personalized content based on that understanding.

[0383] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a text message sent by a user from a communication terminal, means for connecting to a database and confirming or registering user information, means for selecting an appropriate message from a preset category based on a user request, means for formatting the selected message and sending it to the communication terminal, means for analyzing the emotional state of the user from the text message using an emotion analysis engine, and means for recommending content according to the user's emotional state based on the analysis results. This makes it possible to provide timely and personalized messages and content that are in line with the user's emotional state.

[0384] The "means for a user to receive a text message sent from a communication terminal" refers to a function for receiving a text message sent by a user through a communication device such as a mobile terminal or computer.

[0385] The "means for connecting to a database and confirming or registering user information" is a function for accessing a database and confirming existing user information or a function for recording new user information.

[0386] "Means for selecting an appropriate message within a predefined category based on a user request" is a function for selecting an optimal message from a predefined message category based on request data received from a user.

[0387] The "means for formatting the selected message and sending it to the communication terminal" is a function for converting the selected message into a format that can be displayed on the user's device and sending the message to the communication terminal.

[0388] "Means for analyzing a user's emotional state from text messages using an emotion analysis engine" refers to a function that uses an emotion analysis engine such as an AI or machine learning algorithm to analyze a user's emotions and feelings from sent text messages.

[0389] "Means for recommending content according to the user's emotional state based on the analysis results" refers to a function that selects and recommends content such as movies, music, and articles that are appropriate to the user's emotions based on the results of emotion analysis.

[0390] The system for realizing this application example analyzes text messages sent by users from their communication terminals and recommends content based on their emotional state. To implement this, the following hardware and software are used:

[0391] Hardware and software used

[0392] Hardware: communication devices (smartphones, tablets, PCs), servers, database servers

[0393] Software: Flask (web framework), SQLite (database management system), TextBlob (sentiment analysis library), LINE Messaging API (communication API)

[0394] System Operation Overview

[0395] 1. Receiving a message:

[0396] The server receives text messages sent by users from their communication devices (smartphones or tablets) via the LINE API. The received messages contain the user ID and message content.

[0397] 2. User information confirmation and registration:

[0398] The server accesses the database to check whether the user is an existing user or a new user. If the user is new, the server registers the user ID and the details of the first request in the database. If the user is an existing user, the server checks the past request history and settings.

[0399] 3. Message analysis:

[0400] The server uses TextBlob to analyze the sentiment of the received text message and determines the user's emotional state (positive or negative) based on the analysis result.

[0401] 4. Message Formatting and Recommendations:

[0402] The server then recommends content based on the user's emotional state based on the results of the emotion analysis. For example, if the user's emotional state is negative, it recommends encouraging and uplifting content. The content is appropriately selected from various categories, such as movies, music, and articles.

[0403] 5. Sending a message:

[0404] The server formats the selected content and sends it to the user's communication device using the LINE API.

[0405] 6. Emotion history storage:

[0406] The results of the user's emotion analysis and the content sent are stored in a database, allowing the system to refer to the user's emotion history and past requests when making recommendations next time.

[0407] Specific examples

[0408] For example, if a user sends a message from a communication terminal saying, "I've been feeling depressed lately," the server processes the message as follows.

[0409] The server receives the message and analyzes the content: "I'm feeling depressed."

[0410] Sentiment analysis detects negative emotional states.

[0411] The server selects appropriate cheer-up content from a database (e.g., "When you're feeling down, listen to 'Hey Jude' by the Beatles!").

[0412] The selected content is formatted in LINE format and sent to the user's communication device.

[0413] Prompt Sentence Examples

[0414] Generate a sample program for your first application that receives text messages from the front end, performs sentiment analysis, and recommends encouraging content if the user is sad.

[0415] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0416] Step 1:

[0417] Receiving messages

[0418] The server receives text messages sent from the user's device via the LINE API. The input is the text message and user ID, and the output is to pass them on to the server for processing. At this stage, the server temporarily stores the received data.

[0419] Step 2:

[0420] User information confirmation and registration

[0421] The server connects to the database and checks the user information based on the received user ID. The input is the user ID, and the output is the user information for an existing user, or the new registration procedure for a new user. The server registers the new user's information in the database, and for existing users, retrieves the past request history.

[0422] Step 3:

[0423] Emotion analysis

[0424] The server uses the TextBlob library to analyze the sentiment of received text messages. The input is the text message, and the output is the sentiment analysis result (positive, negative, neutral, etc.). The server extracts the emotional state of the message and stores the analysis data.

[0425] Step 4:

[0426] Message Selection

[0427] The server selects appropriate content from a database based on the results of sentiment analysis. The input is the sentiment analysis results and the user's request, and the output is recommended content based on the user's emotional state. The server extracts the optimal content from the database based on an algorithm.

[0428] Step 5:

[0429] Formatting and sending messages

[0430] The server formats the selected content into LINE format and sends it to the communication device. The input is the recommended content and the user ID, and the output is the formatted message sent. The server uses the LINE API to return the content message to the user.

[0431] Step 6:

[0432] Emotion history storage

[0433] The server stores the user's sentiment analysis results and submitted content in a database. The input is the sentiment analysis results and recommended content, and the output is an updated user sentiment history. The server records this data in the database so that it can be used for the next recommendation.

[0434] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0435] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0436] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0437] [Second embodiment]

[0438] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0439] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0440] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0441] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0442] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0443] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0444] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0445] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0446] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0447] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0448] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0449] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0450] This invention is an automated LINE messaging tool that helps test-takers maintain their motivation to study. When a user sends a motivational request message via a communication device, the system selects an appropriate message and replies to the user.

[0451] The embodiment for implementing this system will be described below.

[0452] User operations

[0453] First, a user connects to the system using the LINE app. The user can enter any text message and press the send button. For example, a user can send a message such as, "I'm not motivated to study. Please send me a quote."

[0454] Server Processing

[0455] 1. Receiving a message

[0456] The server receives the text message sent by the user, along with the message data (user ID, content) from the LINE platform.

[0457] 2. User information confirmation and registration

[0458] The server accesses the database and checks the user information. If it is a first-time user, the user information is registered in the database. If it is an existing user, the server checks the past request history and settings.

[0459] 3. Parsing the Request

[0460] The server analyzes the content of the received message. For example, if the message contains a request such as "Please send me a quote," the system selects the "Quote" category.

[0461] 4. Message Selection

[0462] Based on the request, the server randomly or by a specific algorithm selects an appropriate message from pre-defined categories (e.g., famous quotes, uplifting lyrics, questions and answers).

[0463] 5. Message Formatting

[0464] The server formats the selected message into a format that can be sent via LINE. For example, it formats the famous quote, "Success comes from overcoming failure."

[0465] 6. Sending a Message

[0466] The server uses the LINE API to send the formatted message to the user's device.

[0467] Reply to the user

[0468] The user receives the message sent from the server through the LINE app. For example, the message "Success comes from overcoming failure" is displayed on the LINE app.

[0469] Specific examples

[0470] As a specific example, if a user sends a message saying, "I'm not motivated to study. Please send me some great quotes," the server will process the message as follows:

[0471] 1. Reception and Analysis

[0472] User ID: 12345

[0473] Request: "Please send me a quote."

[0474] 2. Verify your user information

[0475] Register as a new user and request a "quote."

[0476] 3. Select a message

[0477] Randomly select the message "Success comes from overcoming failure" from the "Quotes" category in the database.

[0478] 4. Formatting and sending

[0479] The selected message is formatted in LINE format and sent to user ID 12345.

[0480] 5. User receives

[0481] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[0482] In this way, the system sends appropriate messages to the user and helps them maintain their motivation to study.

[0483] The processing flow will be explained below.

[0484] Step 1:

[0485] A user connects to the system using the LINE app, enters a text message, and presses the send button. For example, a user sends a message saying, "I'm not motivated to study. Please send me a quote."

[0486] Step 2:

[0487] The server receives the user's text message from the LINE platform. The received message data includes the user ID and the message content.

[0488] Step 3:

[0489] The server accesses the database and checks the user information. If it is a first-time user, the user ID and the details of the first request are registered in the database. If it is an existing user, the server checks the past request history and settings.

[0490] Step 4:

[0491] The server analyzes the content of the received message. For example, if the message contains a request to "send me a quote," the server selects the "Quote" category.

[0492] Step 5:

[0493] The server selects appropriate messages from a database based on the specified category. The messages are either randomly selected or extracted using a specific algorithm.

[0494] Step 6:

[0495] The server formats the selected message into a format that can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[0496] Step 7:

[0497] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained in step 2.

[0498] Step 8:

[0499] The user receives a message sent from the server through the LINE app. The message content is intended to motivate the user, such as "Success comes from overcoming failure."

[0500] Step 9:

[0501] Check the messages the user has received. For example, reading the message can make the user feel like, "Okay, let's try again!"

[0502] Example 1

[0503] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0504] In today's world, it is extremely difficult for students preparing for exams to maintain their motivation to study. In particular, when studying independently, there is a lack of timely encouragement or guidance, leaving students with limited means to maintain their sagging motivation. This results in a decline in learning efficiency and hinders the improvement of academic performance. To solve this problem, a method that is both easy for students to use and effective in maintaining their motivation is needed.

[0505] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0506] In this invention, the server includes: means for receiving text messages sent by users from their communication terminals; means for connecting to a database and confirming or registering user information; means for selecting an appropriate message from a preset category based on a user request; means for formatting the selected message and sending it to the communication terminal; means for adding identification information for identifying the user information; and means including an algorithm for randomly or specifically selecting an appropriate message from a specified category. This allows test-takers to always receive appropriate encouragement and guidance, thereby maintaining their motivation to study.

[0507] A "communication terminal" refers to an information communication device used by a user, and includes smartphones, tablets, personal computers, etc.

[0508] A "text message" is text information that a user sends through a communication terminal.

[0509] A "server" is a computing device that processes data received from a communication terminal and transmits necessary information.

[0510] A "database" is an information management system for storing user information and message contents.

[0511] "User information" refers to information about users of the system, including user IDs and request history.

[0512] A "request" is an action or information that a user requests from a system.

[0513] A "category" is a group of messages categorized according to the request content.

[0514] "Message formatting" refers to the act of converting a selected message into a format that can be sent.

[0515] "Identification information" refers to information for uniquely identifying a user.

[0516] An "algorithm" is a procedure or computational method for solving a particular problem.

[0517] "Random" means chosen at random without any set rules.

[0518] "Analysis" means detailed analysis of the content of received text messages.

[0519] The present invention is a LINE automatic messaging tool that helps test-takers maintain their motivation to study. When a user sends a request message to improve their motivation through a communication terminal, a server selects an appropriate message and sends it back to the user. A specific embodiment of the tool is described below.

[0520] Hardware and Software

[0521] The hardware and software required to implement the present invention are as follows:

[0522] Hardware:

[0523] 1. Communication devices: smartphones, tablets, computers, etc.

[0524] 2. Server: A high-performance computing device (e.g., cloud server, dedicated server).

[0525] software:

[0526] 1. LINE app: An application that allows users to send messages.

[0527] 2. Database Management System: A system for storing user information and message data (e.g., MySQL, PostgreSQL).

[0528] 3. Text analysis library: A library for analyzing the received message content (e.g., NLTK, SpaCy).

[0529] 4. Generative AI model: The AI ​​model (e.g., GPT-3) used to select and shape the appropriate message.

[0530] 5. LINE Platform API: API for receiving and sending messages through LINE.

[0531] Operation and processing flow

[0532] User operations

[0533] First, the user connects to the system using the LINE app installed on their device. The user can enter any text message and press the send button. For example, to send a message like this:

[0534] "I'm not motivated to study. Please send me some famous quotes."

[0535] Server Processing

[0536] 1. Receiving a message

[0537] The server receives text messages sent by users through the LINE Platform API. This data includes the user ID and message content.

[0538] 2. User information confirmation and registration

[0539] The server connects to the database and checks the user's information. If it is a first-time user, the server registers the user as a new user and saves the user ID and other basic information. If it is an existing user, the server reads and updates the user's past request history and settings.

[0540] 3. Parsing the Request

[0541] The server uses a text analysis library to analyze the content of the received message, for example, to extract the request content such as "Please send me a quote."

[0542] 4. Message Selection

[0543] The server selects appropriate messages from pre-defined categories (e.g., famous quotes, uplifting lyrics, questions and answers), using a generative AI model to select messages randomly or based on a specific algorithm.

[0544] 5. Message Formatting

[0545] The server formats the selected message into a format that can be sent in LINE format, and can also use a generative AI model to convert it into the appropriate format.

[0546] 6. Sending a Message

[0547] The server uses the LINE API to send the formatted message to the user's device. For example, the following message is sent:

[0548] "Success comes from overcoming failure." - Albert Einstein

[0549] Specific examples

[0550] For example, if a user uses a communication device to send a message to the LINE app saying, "I'm not motivated to study. Please send me some famous quotes.", the server processes the message as follows:

[0551] 1. Reception and Analysis

[0552] User ID: 12345

[0553] Request: "Please send me a quote."

[0554] 2. Verify your user information

[0555] The server registers the user as a new user and sets the request content as a "quote."

[0556] 3. Select a message

[0557] The server randomly selects the message "Success comes from overcoming failure" from the "Quotes" category in the database.

[0558] 4. Formatting and sending

[0559] The selected message is formatted in LINE format and sent to user ID 12345.

[0560] 5. User Reception

[0561] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[0562] This system helps test takers maintain their motivation to study by automatically replying to users with appropriate messages.

[0563] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0564] Step 1:

[0565] Receiving messages

[0566] Specific operation: The user uses a communication device to type a message into the LINE app. The user presses the send button to send a message such as, "I'm not motivated to study. Please send me a quote."

[0567] Input: The text message entered by the user into the LINE app.

[0568] Output: Message data (user ID, message content) received by the server via the LINE Platform API.

[0569] Processing content: The server receives message data using the LINE API and temporarily stores it.

[0570] Step 2:

[0571] User information confirmation and registration

[0572] Specific operation: The server connects to the database and searches for user information using the received user ID as a key.

[0573] Input: Received user ID.

[0574] Output: User information in the database or registration of new user information.

[0575] Processing content: The server checks the user information in the database, and if it is a new user, it registers the user ID and basic information in the database. If it is an existing user, it reads the past request history and settings.

[0576] Step 3:

[0577] Parsing the request

[0578] What happens: The server uses a text analysis library (e.g., NLTK or SpaCy) to parse the received message.

[0579] Input: Received text message content.

[0580] Output: Request details (specific category).

[0581] Processing details: The server performs text analysis, extracts the user's request from the message content, and classifies the request into one of three categories: "famous quote," "uplifting lyrics," or "question and answer."

[0582] Step 4:

[0583] Message Selection

[0584] What happens: The server connects to the database and selects messages from the appropriate category.

[0585] Input: Parsed request content (category).

[0586] Output: The selected message.

[0587] What it does: The server randomly or algorithmically selects the best message from a specified category. It may also use a generative AI model (e.g., GPT-3) to select the message. For example, it selects the message "Success comes from overcoming failure" from the "Quotes" category.

[0588] Step 5:

[0589] Message Formatting

[0590] Specific operation: The server formats the selected message into a format that can be sent in LINE format.

[0591] Input: The selected message.

[0592] Output: The formatted message.

[0593] Processing: The server uses a formatting function to format the selected message. It may also input a prompt to the generative AI model to generate the formatted result.

[0594] Step 6:

[0595] Sending a message

[0596] Specific operation: The server sends the formatted message to the user.

[0597] Input: A formatted message and a user ID.

[0598] Output: The message that is displayed on the user's communication terminal.

[0599] Processing content: The server uses the LINE API to send the formatted message to the user's communication device. For example, the message "Success comes from overcoming failure" is displayed in the user's LINE app.

[0600] (Application example 1)

[0601] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0602] Modern food delivery services provide users with the convenience of ordering, but unique and value-added services are required. Furthermore, if users lack motivation or psychological support, their quality of life may decline. It is necessary to solve this issue and provide more value-added food delivery services to improve the user experience.

[0603] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0604] In this invention, the server includes means for receiving text messages sent by users from their communication terminals, means for connecting to a database and confirming or registering user information, means for selecting an appropriate message from a preset category based on a user request, means for formatting the selected message and sending it to the communication terminal, means for providing motivational messages to users when ordering food delivery, and means for automatically translating messages in multiple languages ​​and displaying them in a way that suits the user interface. This allows users to receive mental support when ordering food delivery, thereby improving their quality of life.

[0605] A "communication terminal" is a device that allows a user to send and receive messages, such as a smartphone or tablet.

[0606] A "database" is an information management system that stores user information, message data, etc., and can retrieve and update them as needed.

[0607] "Request" refers to an instruction or request sent by a user through a communication terminal to receive a motivation message, etc.

[0608] "Predefined categories" are categories into which motivational messages are categorized, and include different themes such as quotes, personal experiences, and encouragement.

[0609] "Formatting" refers to the process of formatting a selected message for proper display on a communications terminal.

[0610] "Food delivery" refers to a service that delivers food from restaurants to a location specified by the user.

[0611] "Motivational messages" are messages intended to improve the user's mental motivation, and include famous quotes, words of encouragement, success stories, and the like.

[0612] "Multilingual" refers to the ability to accommodate different languages ​​and provide messages in the user's language of choice.

[0613] "Automatic translation" means the process of converting a message written in one language into another language.

[0614] A "user interface" refers to the screens and operating methods that allow a user to interact with an application, and is designed to enhance user convenience.

[0615] The system for implementing this invention allows users to receive motivational messages when placing an order in a food delivery service. This system is composed of the following main components:

[0616] First, a user accesses a food delivery application using a communication terminal (e.g., a smartphone or tablet) and orders food. The communication terminal then sends the user's request along with order information to the server.

[0617] The server processes the transaction using the following means:

[0618] 1. Receiving means:

[0619] The server receives a text message sent by the user from the communication terminal, the message including the category of motivation message requested by the user.

[0620] 2. Database connection method:

[0621] The server connects to the database to check user information and register new user information if necessary. For existing users, it checks past request history and settings.

[0622] 3. Message selection method:

[0623] Based on the user's request, the server selects an appropriate message from pre-defined categories (e.g., quotes, experiences, encouragement).

[0624] 4. Shaping means:

[0625] Formats the selected message for proper display on the communication device, and automatically translates the message into the user's preferred language if multilingual support is available.

[0626] 5. Motivational message delivery methods:

[0627] The formatted message is provided to users through the food delivery order confirmation screen or messaging apps such as LINE.

[0628] 6. Multilingual support methods:

[0629] The message is automatically translated and displayed appropriately in the language displayed on the user's communication terminal.

[0630] As a concrete example, we will explain the process when a user requests a "success story." When a user places an order on a food delivery application and requests a "success story," this information is sent from the communication terminal to the server. The server randomly selects a message that falls into the "success story" category from the database, formats it, and automatically translates it into the user's language. The selected message is then sent to the user via LINE. The user's LINE will display the message "How I passed my university entrance exam..."

[0631] Example prompt:

[0632] User ID: 12345

[0633] Category: "Success Stories"

[0634] The hardware used is mainly smartphones and tablets, and the software used is LINE Messaging API, Python 3.6+, and the required json and random modules. This system allows users to receive mental support when ordering food delivery, improving their quality of life.

[0635] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0636] Step 1:

[0637] A user selects a dish and places an order in a food delivery app.

[0638] Input: User order information and motivation message category request

[0639] Specific operation: The user uses a communication terminal to order food and drink, and at the end, enters the category of the motivational message (e.g., "famous quote") into the request form.

[0640] Step 2:

[0641] The communication terminal transmits the order information and request data to the server.

[0642] Input: User's order information and category request

[0643] Output: Order information and category request data sent to the server

[0644] Specific operation: Once the order is confirmed, the communication terminal sends the input information, including the user ID, order details, and requested category, to the server.

[0645] Step 3:

[0646] The server checks the user information in the database and registers the user if he is a new user.

[0647] Input: User ID

[0648] Output: User information confirmation result, new registration or existing confirmation

[0649] Specific operation: The server accesses the database and checks the user information based on the user ID. If it is a first-time user, the user information is newly registered in the database.

[0650] Step 4:

[0651] The server analyzes the user's request and selects the appropriate category of message.

[0652] Input: Request content (e.g. "Famous quote")

[0653] Output: An appropriate message (e.g., "Success comes from overcoming failure.")

[0654] Specific operation: The server analyzes the request content and randomly selects messages within a pre-defined category from a database.

[0655] Step 5:

[0656] The selected message is formatted so that it can be displayed appropriately on the communication terminal.

[0657] Input: Selected message

[0658] Output: Formatted message

[0659] Specific operation: The server formats the selected message to match the LINE format or application display format, and if multilingual, automatically translates it into the user's language.

[0660] Step 6:

[0661] The formatted message is sent from the server to the communication terminal.

[0662] Input: Formatted message

[0663] Output: Message sent to the user's communication device

[0664] Specific operation: The server uses the LINE Messaging API to send the formatted message to the user's LINE account or application.

[0665] Step 7:

[0666] The user checks the message received on the communication terminal.

[0667] Input: Received message

[0668] Output: User confirmation

[0669] Specific actions: The user opens the message received on the communication device, checks the contents, and receives encouragement and motivation.

[0670] Through each step, users can receive psychological support when using food delivery services and improve their quality of life.

[0671] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0672] This system receives text messages sent by users through the LINE app, analyzes the message content and emotions, and automatically replies with appropriate encouraging or uplifting messages. Furthermore, the system stores the user's emotional history in a database and reflects this in the next message selection, providing a more personalized service.

[0673] User operations

[0674] First, the user connects to the system using the LINE app. For example, the user types a text message such as "I'm not motivated to study. Please send me a quote," and presses the send button.

[0675] Server Processing

[0676] 1. Receiving a message

[0677] The server receives the user's text message from the LINE platform. The received message contains the user ID and message content.

[0678] 2. User information confirmation and registration

[0679] The server accesses the database and checks the user information. If the user is using the service for the first time, the user ID and the details of the first request are registered in the database. If the user is an existing user, the server checks the past request history and settings.

[0680] 3. Parsing the Request

[0681] The server analyzes the content of the received text message. For example, if the message contains a request to "send me a quote," the system selects the "Quotes" category.

[0682] 4. Analysis by Emotion Engine

[0683] The emotion engine installed on the server analyzes the emotions in the user's text message. Based on this analysis, it selects a message from a category that matches the user's current emotion. For example, if the user is feeling unmotivated, an encouraging message will be selected.

[0684] 5. Message Selection

[0685] The server selects an appropriate message from a database based on the user's sentiment and request, which can be chosen randomly or extracted by a specific algorithm.

[0686] 6. Message Formatting

[0687] The server formats the selected message so that it can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[0688] 7. Sending a Message

[0689] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained initially.

[0690] 8. Emotional history storage

[0691] The server stores the results of the user's emotion analysis and the sent message in a database, allowing the user's emotion history to be used as a reference when selecting a message next time.

[0692] Reply to the user

[0693] The user receives a reply message from the server through the LINE app. For example, a famous quote such as "Success comes from overcoming failure" is displayed in the user's LINE app.

[0694] Specific examples

[0695] As a specific example, if a user sends a message saying, "I'm not motivated to study. Please send me some famous quotes," the server will process it as follows:

[0696] 1. Reception and Analysis

[0697] User ID: 12345

[0698] Request: "Please send me a quote."

[0699] 2. Verify your user information

[0700] Register as a new user and confirm your request.

[0701] 3. Emotion analysis

[0702] Extract the emotion of "lack of motivation" from the message.

[0703] 4. Message Selection

[0704] From the database, select the message "Success comes from overcoming failure" from the "famous quotes" category that is appropriate for the state of "lack of motivation."

[0705] 5. Formatting and sending

[0706] The selected message is formatted in LINE format and sent to user ID 12345.

[0707] 6. Emotion history storage

[0708] The user's sentiment analysis results and the sent message are stored in a database.

[0709] 7. User receives and confirms

[0710] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[0711] In this way, the present invention provides users with an effective means of receiving messages optimized for their emotions and maintaining their motivation to study, thereby enabling personalized support tailored to the needs of each individual user.

[0712] The processing flow will be explained below.

[0713] Step 1:

[0714] A user connects to the system using the LINE app. The user types a text message and presses the send button. For example, the user sends a message saying, "I'm not motivated to study. Please send me a quote."

[0715] Step 2:

[0716] The server receives the user's text message from the LINE platform. The received message data includes the user ID and the message content.

[0717] Step 3:

[0718] The server accesses the database and checks the user information. If the user is a new user, the user ID and the details of the first request are registered in the database. If the user is an existing user, the server checks the past request history and settings.

[0719] Step 4:

[0720] The server analyzes the content of the received message. For example, if the message contains a request to "send me a quote," the server selects the "Quote" category.

[0721] Step 5:

[0722] The emotion engine installed on the server analyzes the user's text messages and recognizes their emotions, such as "unmotivated" or "tired."

[0723] Step 6:

[0724] The server selects a message from a category that matches the user's current emotion based on the analysis results of the emotion engine. For example, if the user is feeling unmotivated, an encouraging message will be selected.

[0725] Step 7:

[0726] The server selects appropriate messages from the database based on the sentiment analysis results and the user's request. The messages are either randomly selected or extracted using a specific algorithm.

[0727] Step 8:

[0728] The server formats the selected message into a format that can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[0729] Step 9:

[0730] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained in step 2.

[0731] Step 10:

[0732] The user receives the message sent from the server through the LINE app. For example, the message "Success comes from overcoming failure" is displayed on the LINE app.

[0733] Step 11:

[0734] The user checks the messages they receive. For example, they read the message and feel like, "Okay, let's try again!"

[0735] Step 12:

[0736] The server stores the user's emotion analysis results and the sent message in a database, allowing the server to refer to the user's emotion history when selecting a message next time.

[0737] Example 2

[0738] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0739] Conventional message response systems often use standardized replies without considering the user's emotions, making it difficult to provide appropriate messages that reflect the user's situation and mood. As a result, users are not fully satisfied, and the system's usability is reduced. In addition, the lack of a function to save the user's emotional history means that the next time a message is selected, a non-personalized response may be sent.

[0740] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving a text message sent by a user from a communication terminal, a means for connecting to a database and confirming or registering user information, a means for selecting an appropriate message from a preset category based on a user request, a means for formatting the selected message and sending it to the communication terminal, a means for analyzing emotions from the user's text message, and a means for saving the emotion analysis result in the database. This makes it possible to provide a message optimized for the user's emotions and to realize a personalized service by using the user's emotion history for the next message selection.

[0741] A "communication terminal" is a device that a user uses to send and receive text messages, and includes smartphones, tablets, personal computers, etc.

[0742] A "text message" is information in the form of text that a user sends via a communication terminal.

[0743] A "database" is a system that systematically stores and manages data such as user information, messages, and emotion analysis results.

[0744] "Sentiment analysis" is the process of identifying and assessing a user's current emotions from a text message.

[0745] "Message selection" refers to extracting the most suitable message from a pre-defined category based on the user's request and sentiment.

[0746] "Message formatting" refers to converting a selected message into a format suitable for transmission to a communication terminal.

[0747] "Emotion history" is data that records the results of a user's emotion analysis and related messages in chronological order.

[0748] This system receives text messages sent by users through communication applications, analyzes the content and emotions of the messages, and automatically replies with appropriate encouraging or uplifting messages. It also stores the user's emotional history in a database and reflects this in the next message selection, providing a more personalized service.

[0749] User operations

[0750] First, the user connects to the system using a communication application. For example, the user types a text message such as "I'm not motivated to study. Please send me a quote," and presses the send button. This message is then sent via a platform such as LINE. At this point, the user does not need to perform any particularly complicated settings or operations; the system works simply by sending a message as usual.

[0751] Hardware and software used

[0752] server

[0753] The server is mainly configured using the following hardware and software:

[0754] Hardware:

[0755] A server machine with high-speed internet connection

[0756] High-performance processor and sufficient memory capacity

[0757] software:

[0758] LINE Messaging API: Used to receive and reply to text messages

[0759] MySQL or PostgreSQL: A database that stores user information and emotion history

[0760] IBM Watson and Google Cloud Natural Language API: Natural language processing engines for sentiment analysis

[0761] Python and Node.js: the main implementation languages ​​for the program

[0762] Server Processing

[0763] When the server receives a text message sent by a user through a communication application (e.g., LINE), it analyzes it and generates an appropriate reply message. The server first extracts the user ID and message content from the received message. It then accesses a database to confirm or register the user's information. If the user is not registered, the server records the user ID and the content of the initial request in the database.

[0764] The server then analyzes the content of the text message to identify the user's request and emotion. For example, a request such as "Please send me a quote" would be assigned to the "Quote" category. Sentiment analysis also identifies the user's emotional state as "unmotivated."

[0765] The server then selects an appropriate message from its database based on the user's emotions and requests. The selected message is then formatted by the server again and sent back to the user's device. This entire process is automated, and the user waits again until they receive the reply message in the LINE app.

[0766] Specific examples

[0767] As a concrete example, consider the case where a user sends a message saying, "I'm not motivated to study. Please send me some famous quotes." When this message arrives at the server, the server processes it as follows:

[0768] 1. The server receives the message via the LINE Messaging API and extracts the user ID and text content.

[0769] 2. The server accesses the database and registers the user as a new user or checks for an existing user.

[0770] 3. The server analyzes the content of the text message using a natural language processing engine to identify the request and sentiment.

[0771] 4. The server selects a message from the database that best matches the user's emotion.

[0772] 5. The server formats the selected message for transmission to the communication terminal.

[0773] 6. Finally, the user sentiment analysis results and the sent message are stored in the database.

[0774] For example, in response to a prompt message sent by a user such as "I'm not motivated to study. Please send me a quote," the reply message displayed on the user's communication device is "Success comes from overcoming failure." In this way, the system can continue to provide personalized services to users by using the emotion history when selecting the next message.

[0775] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0776] Step 1:

[0777] The server receives text messages sent by users using the API of a communication application (for example, the LINE Messaging API). The input is the user ID and message content, and the output is the received message data. Specifically, the message data is sent to the server by Webhook via an HTTP POST request from the LINE platform.

[0778] Step 2:

[0779] The server accesses the database and verifies or registers the user's information. The input is the user ID and text content received in step 1, and the output is a record of the user information. Specifically, it queries the database (MySQL or PostgreSQL) for existing user information, and if it is a new user, it records the user ID and the content of the initial request.

[0780] Step 3:

[0781] The server analyzes the received text message to identify the user's request. The input is the message content received in step 1, and the output is the classification result of the request. Specifically, a natural language processing library (e.g., NLTK or spaCy) is used to extract keywords from the text and analyze the request.

[0782] Step 4:

[0783] The server analyzes emotions from text messages. The input is the message content received in step 1, and the output is the emotion analysis result. Specifically, it uses a natural language understanding API (e.g., IBM Watson or Google Cloud Natural Language) to identify and evaluate emotions from text.

[0784] Step 5:

[0785] The server selects an appropriate message from the database based on the user request and the results of sentiment analysis. The input is the analysis results from steps 3 and 4, and the output is the selected message. Specifically, it searches the database for messages that match the request and sentiment, and randomly selects one if necessary.

[0786] Step 6:

[0787] The server formats the selected message for transmission to the communication terminal. The input is the message selected in step 5, and the output is the formatted message data. Specifically, the message is converted into an appropriate transmission format such as JSON format.

[0788] Step 7:

[0789] The server sends the formatted message to the user's communication device using the communication application's API (for example, the LINE Messaging API). The input is the message data formatted in step 6, and the output is the transmission result. Specifically, the message is sent using the API's push method.

[0790] Step 8:

[0791] The server stores the user's emotion analysis results and the sent message in a database. The input is the data from steps 1, 4, and 5, and the output is the updated user emotion history. Specifically, the emotion analysis results and the sent message content are recorded in the corresponding tables in the database.

[0792] (Application example 2)

[0793] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0794] In modern society, users' stress, anxiety, and lack of motivation are becoming common problems. This creates a need for timely and encouraging messages. However, current systems have difficulty fully understanding a user's emotional state and recommending personalized content based on that understanding.

[0795] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a text message sent by a user from a communication terminal, means for connecting to a database and confirming or registering user information, means for selecting an appropriate message from a preset category based on a user request, means for formatting the selected message and sending it to the communication terminal, means for analyzing the emotional state of the user from the text message using an emotion analysis engine, and means for recommending content according to the user's emotional state based on the analysis results. This makes it possible to provide timely and personalized messages and content that are in line with the user's emotional state.

[0796] The "means for a user to receive a text message sent from a communication terminal" refers to a function for receiving a text message sent by a user through a communication device such as a mobile terminal or computer.

[0797] The "means for connecting to a database and confirming or registering user information" is a function for accessing a database and confirming existing user information or a function for recording new user information.

[0798] "Means for selecting an appropriate message within a predefined category based on a user request" is a function for selecting an optimal message from a predefined message category based on request data received from a user.

[0799] The "means for formatting the selected message and sending it to the communication terminal" is a function for converting the selected message into a format that can be displayed on the user's device and sending the message to the communication terminal.

[0800] "Means for analyzing a user's emotional state from text messages using an emotion analysis engine" refers to a function that uses an emotion analysis engine such as an AI or machine learning algorithm to analyze a user's emotions and feelings from sent text messages.

[0801] "Means for recommending content according to the user's emotional state based on the analysis results" refers to a function that selects and recommends content such as movies, music, and articles that are appropriate to the user's emotions based on the results of emotion analysis.

[0802] The system for realizing this application example analyzes text messages sent by users from their communication terminals and recommends content based on their emotional state. To implement this, the following hardware and software are used:

[0803] Hardware and software used

[0804] Hardware: communication devices (smartphones, tablets, PCs), servers, database servers

[0805] Software: Flask (web framework), SQLite (database management system), TextBlob (sentiment analysis library), LINE Messaging API (communication API)

[0806] System Operation Overview

[0807] 1. Receiving a message:

[0808] The server receives text messages sent by users from their communication devices (smartphones or tablets) via the LINE API. The received messages contain the user ID and message content.

[0809] 2. User information confirmation and registration:

[0810] The server accesses the database to check whether the user is an existing user or a new user. If the user is new, the server registers the user ID and the details of the first request in the database. If the user is an existing user, the server checks the past request history and settings.

[0811] 3. Message analysis:

[0812] The server uses TextBlob to analyze the sentiment of the received text message and determines the user's emotional state (positive or negative) based on the analysis result.

[0813] 4. Message Formatting and Recommendations:

[0814] The server then recommends content based on the user's emotional state based on the results of the emotion analysis. For example, if the user's emotional state is negative, it recommends encouraging and uplifting content. The content is appropriately selected from various categories, such as movies, music, and articles.

[0815] 5. Sending a message:

[0816] The server formats the selected content and sends it to the user's communication device using the LINE API.

[0817] 6. Emotion history storage:

[0818] The results of the user's emotion analysis and the content sent are stored in a database, allowing the system to refer to the user's emotion history and past requests when making recommendations next time.

[0819] Specific examples

[0820] For example, if a user sends a message from a communication terminal saying, "I've been feeling depressed lately," the server processes the message as follows.

[0821] The server receives the message and analyzes the content: "I'm feeling depressed."

[0822] Sentiment analysis detects negative emotional states.

[0823] The server selects appropriate cheer-up content from a database (e.g., "When you're feeling down, listen to 'Hey Jude' by the Beatles!").

[0824] The selected content is formatted in LINE format and sent to the user's communication device.

[0825] Prompt Sentence Examples

[0826] Generate a sample program for your first application that receives text messages from the front end, performs sentiment analysis, and recommends encouraging content if the user is sad.

[0827] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0828] Step 1:

[0829] Receiving messages

[0830] The server receives text messages sent from the user's device via the LINE API. The input is the text message and user ID, and the output is to pass them on to the server for processing. At this stage, the server temporarily stores the received data.

[0831] Step 2:

[0832] User information confirmation and registration

[0833] The server connects to the database and checks the user information based on the received user ID. The input is the user ID, and the output is the user information for an existing user, or the new registration procedure for a new user. The server registers the new user's information in the database, and for existing users, retrieves the past request history.

[0834] Step 3:

[0835] Emotion analysis

[0836] The server uses the TextBlob library to analyze the sentiment of received text messages. The input is the text message, and the output is the sentiment analysis result (positive, negative, neutral, etc.). The server extracts the emotional state of the message and stores the analysis data.

[0837] Step 4:

[0838] Message Selection

[0839] The server selects appropriate content from a database based on the results of sentiment analysis. The input is the sentiment analysis results and the user's request, and the output is recommended content based on the user's emotional state. The server extracts the optimal content from the database based on an algorithm.

[0840] Step 5:

[0841] Formatting and sending messages

[0842] The server formats the selected content into LINE format and sends it to the communication device. The input is the recommended content and the user ID, and the output is the formatted message sent. The server uses the LINE API to return the content message to the user.

[0843] Step 6:

[0844] Emotion history storage

[0845] The server stores the user's sentiment analysis results and submitted content in a database. The input is the sentiment analysis results and recommended content, and the output is an updated user sentiment history. The server records this data in the database so that it can be used for the next recommendation.

[0846] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0847] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0848] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0849] [Third embodiment]

[0850] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0851] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0852] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0853] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0854] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0855] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0856] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0857] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0858] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0859] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0860] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0861] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0862] This invention is an automated LINE messaging tool that helps test-takers maintain their motivation to study. When a user sends a motivational request message via a communication device, the system selects an appropriate message and replies to the user.

[0863] The embodiment for implementing this system will be described below.

[0864] User operations

[0865] First, a user connects to the system using the LINE app. The user can enter any text message and press the send button. For example, a user can send a message such as, "I'm not motivated to study. Please send me a quote."

[0866] Server Processing

[0867] 1. Receiving a message

[0868] The server receives the text message sent by the user, along with the message data (user ID, content) from the LINE platform.

[0869] 2. User information confirmation and registration

[0870] The server accesses the database and checks the user information. If it is a first-time user, the user information is registered in the database. If it is an existing user, the server checks the past request history and settings.

[0871] 3. Parsing the Request

[0872] The server analyzes the content of the received message. For example, if the message contains a request such as "Please send me a quote," the system selects the "Quote" category.

[0873] 4. Message Selection

[0874] Based on the request, the server randomly or by a specific algorithm selects an appropriate message from pre-defined categories (e.g., famous quotes, uplifting lyrics, questions and answers).

[0875] 5. Message Formatting

[0876] The server formats the selected message into a format that can be sent via LINE. For example, it formats the famous quote, "Success comes from overcoming failure."

[0877] 6. Sending a Message

[0878] The server uses the LINE API to send the formatted message to the user's device.

[0879] Reply to the user

[0880] The user receives the message sent from the server through the LINE app. For example, the message "Success comes from overcoming failure" is displayed on the LINE app.

[0881] Specific examples

[0882] As a specific example, if a user sends a message saying, "I'm not motivated to study. Please send me some great quotes," the server will process the message as follows:

[0883] 1. Reception and Analysis

[0884] User ID: 12345

[0885] Request: "Please send me a quote."

[0886] 2. Verify your user information

[0887] Register as a new user and request a "quote."

[0888] 3. Select a message

[0889] Randomly select the message "Success comes from overcoming failure" from the "Quotes" category in the database.

[0890] 4. Formatting and sending

[0891] The selected message is formatted in LINE format and sent to user ID 12345.

[0892] 5. User receives

[0893] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[0894] In this way, the system sends appropriate messages to the user and helps them maintain their motivation to study.

[0895] The processing flow will be explained below.

[0896] Step 1:

[0897] A user connects to the system using the LINE app, enters a text message, and presses the send button. For example, a user sends a message saying, "I'm not motivated to study. Please send me a quote."

[0898] Step 2:

[0899] The server receives the user's text message from the LINE platform. The received message data includes the user ID and the message content.

[0900] Step 3:

[0901] The server accesses the database and checks the user information. If it is a first-time user, the user ID and the details of the first request are registered in the database. If it is an existing user, the server checks the past request history and settings.

[0902] Step 4:

[0903] The server analyzes the content of the received message. For example, if the message contains a request to "send me a quote," the server selects the "Quote" category.

[0904] Step 5:

[0905] The server selects appropriate messages from a database based on the specified category. The messages are either randomly selected or extracted using a specific algorithm.

[0906] Step 6:

[0907] The server formats the selected message into a format that can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[0908] Step 7:

[0909] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained in step 2.

[0910] Step 8:

[0911] The user receives a message sent from the server through the LINE app. The message content is intended to motivate the user, such as "Success comes from overcoming failure."

[0912] Step 9:

[0913] Check the messages the user has received. For example, reading the message can make the user feel like, "Okay, let's try again!"

[0914] Example 1

[0915] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0916] In today's world, it is extremely difficult for students preparing for exams to maintain their motivation to study. In particular, when studying independently, there is a lack of timely encouragement or guidance, leaving students with limited means to maintain their sagging motivation. This results in a decline in learning efficiency and hinders the improvement of academic performance. To solve this problem, a method that is both easy for students to use and effective in maintaining their motivation is needed.

[0917] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0918] In this invention, the server includes: means for receiving text messages sent by users from their communication terminals; means for connecting to a database and confirming or registering user information; means for selecting an appropriate message from a preset category based on a user request; means for formatting the selected message and sending it to the communication terminal; means for adding identification information for identifying the user information; and means including an algorithm for randomly or specifically selecting an appropriate message from a specified category. This allows test-takers to always receive appropriate encouragement and guidance, thereby maintaining their motivation to study.

[0919] A "communication terminal" refers to an information communication device used by a user, and includes smartphones, tablets, personal computers, etc.

[0920] A "text message" is text information that a user sends through a communication terminal.

[0921] A "server" is a computing device that processes data received from a communication terminal and transmits necessary information.

[0922] A "database" is an information management system for storing user information and message contents.

[0923] "User information" refers to information about users of the system, including user IDs and request history.

[0924] A "request" is an action or information that a user requests from a system.

[0925] A "category" is a group of messages categorized according to the request content.

[0926] "Message formatting" refers to the act of converting a selected message into a format that can be sent.

[0927] "Identification information" refers to information for uniquely identifying a user.

[0928] An "algorithm" is a procedure or computational method for solving a particular problem.

[0929] "Random" means chosen at random without any set rules.

[0930] "Analysis" means detailed analysis of the content of received text messages.

[0931] The present invention is a LINE automatic messaging tool that helps test-takers maintain their motivation to study. When a user sends a request message to improve their motivation through a communication terminal, a server selects an appropriate message and sends it back to the user. A specific embodiment of the tool is described below.

[0932] Hardware and Software

[0933] The hardware and software required to implement the present invention are as follows:

[0934] Hardware:

[0935] 1. Communication devices: smartphones, tablets, computers, etc.

[0936] 2. Server: A high-performance computing device (e.g., cloud server, dedicated server).

[0937] software:

[0938] 1. LINE app: An application that allows users to send messages.

[0939] 2. Database Management System: A system for storing user information and message data (e.g., MySQL, PostgreSQL).

[0940] 3. Text analysis library: A library for analyzing the received message content (e.g., NLTK, SpaCy).

[0941] 4. Generative AI model: The AI ​​model (e.g., GPT-3) used to select and shape the appropriate message.

[0942] 5. LINE Platform API: API for receiving and sending messages through LINE.

[0943] Operation and processing flow

[0944] User operations

[0945] First, the user connects to the system using the LINE app installed on their device. The user can enter any text message and press the send button. For example, to send a message like this:

[0946] "I'm not motivated to study. Please send me some famous quotes."

[0947] Server Processing

[0948] 1. Receiving a message

[0949] The server receives text messages sent by users through the LINE Platform API. This data includes the user ID and message content.

[0950] 2. User information confirmation and registration

[0951] The server connects to the database and checks the user's information. If it is a first-time user, the server registers the user as a new user and saves the user ID and other basic information. If it is an existing user, the server reads and updates the user's past request history and settings.

[0952] 3. Parsing the Request

[0953] The server uses a text analysis library to analyze the content of the received message, for example, to extract the request content such as "Please send me a quote."

[0954] 4. Message Selection

[0955] The server selects appropriate messages from pre-defined categories (e.g., famous quotes, uplifting lyrics, questions and answers), using a generative AI model to select messages randomly or based on a specific algorithm.

[0956] 5. Message Formatting

[0957] The server formats the selected message into a format that can be sent in LINE format, and can also use a generative AI model to convert it into the appropriate format.

[0958] 6. Sending a Message

[0959] The server uses the LINE API to send the formatted message to the user's device. For example, the following message is sent:

[0960] "Success comes from overcoming failure." - Albert Einstein

[0961] Specific examples

[0962] For example, if a user uses a communication device to send a message to the LINE app saying, "I'm not motivated to study. Please send me some famous quotes.", the server processes the message as follows:

[0963] 1. Reception and Analysis

[0964] User ID: 12345

[0965] Request: "Please send me a quote."

[0966] 2. Verify your user information

[0967] The server registers the user as a new user and sets the request content as a "quote."

[0968] 3. Select a message

[0969] The server randomly selects the message "Success comes from overcoming failure" from the "Quotes" category in the database.

[0970] 4. Formatting and sending

[0971] The selected message is formatted in LINE format and sent to user ID 12345.

[0972] 5. User Reception

[0973] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[0974] This system helps test takers maintain their motivation to study by automatically replying to users with appropriate messages.

[0975] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0976] Step 1:

[0977] Receiving messages

[0978] Specific operation: The user uses a communication device to type a message into the LINE app. The user presses the send button to send a message such as, "I'm not motivated to study. Please send me a quote."

[0979] Input: The text message entered by the user into the LINE app.

[0980] Output: Message data (user ID, message content) received by the server via the LINE Platform API.

[0981] Processing content: The server receives message data using the LINE API and temporarily stores it.

[0982] Step 2:

[0983] User information confirmation and registration

[0984] Specific operation: The server connects to the database and searches for user information using the received user ID as a key.

[0985] Input: Received user ID.

[0986] Output: User information in the database or registration of new user information.

[0987] Processing content: The server checks the user information in the database, and if it is a new user, it registers the user ID and basic information in the database. If it is an existing user, it reads the past request history and settings.

[0988] Step 3:

[0989] Parsing the request

[0990] What happens: The server uses a text analysis library (e.g., NLTK or SpaCy) to parse the received message.

[0991] Input: Received text message content.

[0992] Output: Request details (specific category).

[0993] Processing details: The server performs text analysis, extracts the user's request from the message content, and classifies the request into one of three categories: "famous quote," "uplifting lyrics," or "question and answer."

[0994] Step 4:

[0995] Message Selection

[0996] What happens: The server connects to the database and selects messages from the appropriate category.

[0997] Input: Parsed request content (category).

[0998] Output: The selected message.

[0999] What it does: The server randomly or algorithmically selects the best message from a specified category. It may also use a generative AI model (e.g., GPT-3) to select the message. For example, it selects the message "Success comes from overcoming failure" from the "Quotes" category.

[1000] Step 5:

[1001] Message Formatting

[1002] Specific operation: The server formats the selected message into a format that can be sent in LINE format.

[1003] Input: The selected message.

[1004] Output: The formatted message.

[1005] Processing: The server uses a formatting function to format the selected message. It may also input a prompt to the generative AI model to generate the formatted result.

[1006] Step 6:

[1007] Sending a message

[1008] Specific operation: The server sends the formatted message to the user.

[1009] Input: A formatted message and a user ID.

[1010] Output: The message that is displayed on the user's communication terminal.

[1011] Processing content: The server uses the LINE API to send the formatted message to the user's communication device. For example, the message "Success comes from overcoming failure" is displayed in the user's LINE app.

[1012] (Application example 1)

[1013] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1014] Modern food delivery services provide users with the convenience of ordering, but unique and value-added services are required. Furthermore, if users lack motivation or psychological support, their quality of life may decline. It is necessary to solve this issue and provide more value-added food delivery services to improve the user experience.

[1015] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1016] In this invention, the server includes means for receiving text messages sent by users from their communication terminals, means for connecting to a database and confirming or registering user information, means for selecting an appropriate message from a preset category based on a user request, means for formatting the selected message and sending it to the communication terminal, means for providing motivational messages to users when ordering food delivery, and means for automatically translating messages in multiple languages ​​and displaying them in a way that suits the user interface. This allows users to receive mental support when ordering food delivery, thereby improving their quality of life.

[1017] A "communication terminal" is a device that allows a user to send and receive messages, such as a smartphone or tablet.

[1018] A "database" is an information management system that stores user information, message data, etc., and can retrieve and update them as needed.

[1019] "Request" refers to an instruction or request sent by a user through a communication terminal to receive a motivation message, etc.

[1020] "Predefined categories" are categories into which motivational messages are categorized, and include different themes such as quotes, personal experiences, and encouragement.

[1021] "Formatting" refers to the process of formatting a selected message for proper display on a communications terminal.

[1022] "Food delivery" refers to a service that delivers food from restaurants to a location specified by the user.

[1023] "Motivational messages" are messages intended to improve the user's mental motivation, and include famous quotes, words of encouragement, success stories, and the like.

[1024] "Multilingual" refers to the ability to accommodate different languages ​​and provide messages in the user's language of choice.

[1025] "Automatic translation" means the process of converting a message written in one language into another language.

[1026] A "user interface" refers to the screens and operating methods that allow a user to interact with an application, and is designed to enhance user convenience.

[1027] The system for implementing this invention allows users to receive motivational messages when placing an order in a food delivery service. This system is composed of the following main components:

[1028] First, a user accesses a food delivery application using a communication terminal (e.g., a smartphone or tablet) and orders food. The communication terminal then sends the user's request along with order information to the server.

[1029] The server processes the transaction using the following means:

[1030] 1. Receiving means:

[1031] The server receives a text message sent by the user from the communication terminal, the message including the category of motivation message requested by the user.

[1032] 2. Database connection method:

[1033] The server connects to the database to check user information and register new user information if necessary. For existing users, it checks past request history and settings.

[1034] 3. Message selection method:

[1035] Based on the user's request, the server selects an appropriate message from pre-defined categories (e.g., quotes, experiences, encouragement).

[1036] 4. Shaping means:

[1037] Formats the selected message for proper display on the communication device, and automatically translates the message into the user's preferred language if multilingual support is available.

[1038] 5. Motivational message delivery methods:

[1039] The formatted message is provided to users through the food delivery order confirmation screen or messaging apps such as LINE.

[1040] 6. Multilingual support methods:

[1041] The message is automatically translated and displayed appropriately in the language displayed on the user's communication terminal.

[1042] As a concrete example, we will explain the process when a user requests a "success story." When a user places an order on a food delivery application and requests a "success story," this information is sent from the communication terminal to the server. The server randomly selects a message that falls into the "success story" category from the database, formats it, and automatically translates it into the user's language. The selected message is then sent to the user via LINE. The user's LINE will display the message "How I passed my university entrance exam..."

[1043] Example prompt:

[1044] User ID: 12345

[1045] Category: "Success Stories"

[1046] The hardware used is mainly smartphones and tablets, and the software used is LINE Messaging API, Python 3.6+, and the required json and random modules. This system allows users to receive mental support when ordering food delivery, improving their quality of life.

[1047] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1048] Step 1:

[1049] A user selects a dish and places an order in a food delivery app.

[1050] Input: User order information and motivation message category request

[1051] Specific operation: The user uses a communication terminal to order food and drink, and at the end, enters the category of the motivational message (e.g., "famous quote") into the request form.

[1052] Step 2:

[1053] The communication terminal transmits the order information and request data to the server.

[1054] Input: User's order information and category request

[1055] Output: Order information and category request data sent to the server

[1056] Specific operation: Once the order is confirmed, the communication terminal sends the input information, including the user ID, order details, and requested category, to the server.

[1057] Step 3:

[1058] The server checks the user information in the database and registers the user if he is a new user.

[1059] Input: User ID

[1060] Output: User information confirmation result, new registration or existing confirmation

[1061] Specific operation: The server accesses the database and checks the user information based on the user ID. If it is a first-time user, the user information is newly registered in the database.

[1062] Step 4:

[1063] The server analyzes the user's request and selects the appropriate category of message.

[1064] Input: Request content (e.g. "Famous quote")

[1065] Output: An appropriate message (e.g., "Success comes from overcoming failure.")

[1066] Specific operation: The server analyzes the request content and randomly selects messages within a pre-defined category from a database.

[1067] Step 5:

[1068] The selected message is formatted so that it can be displayed appropriately on the communication terminal.

[1069] Input: Selected message

[1070] Output: Formatted message

[1071] Specific operation: The server formats the selected message to match the LINE format or application display format, and if multilingual, automatically translates it into the user's language.

[1072] Step 6:

[1073] The formatted message is sent from the server to the communication terminal.

[1074] Input: Formatted message

[1075] Output: Message sent to the user's communication device

[1076] Specific operation: The server uses the LINE Messaging API to send the formatted message to the user's LINE account or application.

[1077] Step 7:

[1078] The user checks the message received on the communication terminal.

[1079] Input: Received message

[1080] Output: User confirmation

[1081] Specific actions: The user opens the message received on the communication device, checks the contents, and receives encouragement and motivation.

[1082] Through each step, users can receive psychological support when using food delivery services and improve their quality of life.

[1083] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1084] This system receives text messages sent by users through the LINE app, analyzes the message content and emotions, and automatically replies with appropriate encouraging or uplifting messages. Furthermore, the system stores the user's emotional history in a database and reflects this in the next message selection, providing a more personalized service.

[1085] User operations

[1086] First, the user connects to the system using the LINE app. For example, the user types a text message such as "I'm not motivated to study. Please send me a quote," and presses the send button.

[1087] Server Processing

[1088] 1. Receiving a message

[1089] The server receives the user's text message from the LINE platform. The received message contains the user ID and message content.

[1090] 2. User information confirmation and registration

[1091] The server accesses the database and checks the user information. If the user is using the service for the first time, the user ID and the details of the first request are registered in the database. If the user is an existing user, the server checks the past request history and settings.

[1092] 3. Parsing the Request

[1093] The server analyzes the content of the received text message. For example, if the message contains a request to "send me a quote," the system selects the "Quotes" category.

[1094] 4. Analysis by Emotion Engine

[1095] The emotion engine installed on the server analyzes the emotions in the user's text message. Based on this analysis, it selects a message from a category that matches the user's current emotion. For example, if the user is feeling unmotivated, an encouraging message will be selected.

[1096] 5. Message Selection

[1097] The server selects an appropriate message from a database based on the user's sentiment and request, which can be chosen randomly or extracted by a specific algorithm.

[1098] 6. Message Formatting

[1099] The server formats the selected message so that it can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[1100] 7. Sending a Message

[1101] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained initially.

[1102] 8. Emotional history storage

[1103] The server stores the results of the user's emotion analysis and the sent message in a database, allowing the user's emotion history to be used as a reference when selecting a message next time.

[1104] Reply to the user

[1105] The user receives a reply message from the server through the LINE app. For example, a famous quote such as "Success comes from overcoming failure" is displayed in the user's LINE app.

[1106] Specific examples

[1107] As a specific example, if a user sends a message saying, "I'm not motivated to study. Please send me some famous quotes," the server will process it as follows:

[1108] 1. Reception and Analysis

[1109] User ID: 12345

[1110] Request: "Please send me a quote."

[1111] 2. Verify your user information

[1112] Register as a new user and confirm your request.

[1113] 3. Emotion analysis

[1114] Extract the emotion of "lack of motivation" from the message.

[1115] 4. Message Selection

[1116] From the database, select the message "Success comes from overcoming failure" from the "famous quotes" category that is appropriate for the state of "lack of motivation."

[1117] 5. Formatting and sending

[1118] The selected message is formatted in LINE format and sent to user ID 12345.

[1119] 6. Emotion history storage

[1120] The user's sentiment analysis results and the sent message are stored in a database.

[1121] 7. User receives and confirms

[1122] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[1123] In this way, the present invention provides users with an effective means of receiving messages optimized for their emotions and maintaining their motivation to study, thereby enabling personalized support tailored to the needs of each individual user.

[1124] The processing flow will be explained below.

[1125] Step 1:

[1126] A user connects to the system using the LINE app. The user types a text message and presses the send button. For example, the user sends a message saying, "I'm not motivated to study. Please send me a quote."

[1127] Step 2:

[1128] The server receives the user's text message from the LINE platform. The received message data includes the user ID and the message content.

[1129] Step 3:

[1130] The server accesses the database and checks the user information. If the user is a new user, the user ID and the details of the first request are registered in the database. If the user is an existing user, the server checks the past request history and settings.

[1131] Step 4:

[1132] The server analyzes the content of the received message. For example, if the message contains a request to "send me a quote," the server selects the "Quote" category.

[1133] Step 5:

[1134] The emotion engine installed on the server analyzes the user's text messages and recognizes their emotions, such as "unmotivated" or "tired."

[1135] Step 6:

[1136] The server selects a message from a category that matches the user's current emotion based on the analysis results of the emotion engine. For example, if the user is feeling unmotivated, an encouraging message will be selected.

[1137] Step 7:

[1138] The server selects appropriate messages from the database based on the sentiment analysis results and the user's request. The messages are either randomly selected or extracted using a specific algorithm.

[1139] Step 8:

[1140] The server formats the selected message into a format that can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[1141] Step 9:

[1142] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained in step 2.

[1143] Step 10:

[1144] The user receives the message sent from the server through the LINE app. For example, the message "Success comes from overcoming failure" is displayed on the LINE app.

[1145] Step 11:

[1146] The user checks the messages they receive. For example, they read the message and feel like, "Okay, let's try again!"

[1147] Step 12:

[1148] The server stores the user's emotion analysis results and the sent message in a database, allowing the server to refer to the user's emotion history when selecting a message next time.

[1149] Example 2

[1150] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1151] Conventional message response systems often use standardized replies without considering the user's emotions, making it difficult to provide appropriate messages that reflect the user's situation and mood. As a result, users are not fully satisfied, and the system's usability is reduced. In addition, the lack of a function to save the user's emotional history means that the next time a message is selected, a non-personalized response may be sent.

[1152] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving a text message sent by a user from a communication terminal, a means for connecting to a database and confirming or registering user information, a means for selecting an appropriate message from a preset category based on a user request, a means for formatting the selected message and sending it to the communication terminal, a means for analyzing emotions from the user's text message, and a means for saving the emotion analysis result in the database. This makes it possible to provide a message optimized for the user's emotions and to realize a personalized service by using the user's emotion history for the next message selection.

[1153] A "communication terminal" is a device that a user uses to send and receive text messages, and includes smartphones, tablets, personal computers, etc.

[1154] A "text message" is information in the form of text that a user sends via a communication terminal.

[1155] A "database" is a system that systematically stores and manages data such as user information, messages, and emotion analysis results.

[1156] "Sentiment analysis" is the process of identifying and assessing a user's current emotions from a text message.

[1157] "Message selection" refers to extracting the most suitable message from a pre-defined category based on the user's request and sentiment.

[1158] "Message formatting" refers to converting a selected message into a format suitable for transmission to a communication terminal.

[1159] "Emotion history" is data that records the results of a user's emotion analysis and related messages in chronological order.

[1160] This system receives text messages sent by users through communication applications, analyzes the content and emotions of the messages, and automatically replies with appropriate encouraging or uplifting messages. It also stores the user's emotional history in a database and reflects this in the next message selection, providing a more personalized service.

[1161] User operations

[1162] First, the user connects to the system using a communication application. For example, the user types a text message such as "I'm not motivated to study. Please send me a quote," and presses the send button. This message is then sent via a platform such as LINE. At this point, the user does not need to perform any particularly complicated settings or operations; the system works simply by sending a message as usual.

[1163] Hardware and software used

[1164] server

[1165] The server is mainly configured using the following hardware and software:

[1166] Hardware:

[1167] A server machine with high-speed internet connection

[1168] High-performance processor and sufficient memory capacity

[1169] software:

[1170] LINE Messaging API: Used to receive and reply to text messages

[1171] MySQL or PostgreSQL: A database that stores user information and emotion history

[1172] IBM Watson and Google Cloud Natural Language API: Natural language processing engines for sentiment analysis

[1173] Python and Node.js: the main implementation languages ​​for the program

[1174] Server Processing

[1175] When the server receives a text message sent by a user through a communication application (e.g., LINE), it analyzes it and generates an appropriate reply message. The server first extracts the user ID and message content from the received message. It then accesses a database to confirm or register the user's information. If the user is not registered, the server records the user ID and the content of the initial request in the database.

[1176] The server then analyzes the content of the text message to identify the user's request and emotion. For example, a request such as "Please send me a quote" would be assigned to the "Quote" category. Sentiment analysis also identifies the user's emotional state as "unmotivated."

[1177] The server then selects an appropriate message from its database based on the user's emotions and requests. The selected message is then formatted by the server again and sent back to the user's device. This entire process is automated, and the user waits again until they receive the reply message in the LINE app.

[1178] Specific examples

[1179] As a concrete example, consider the case where a user sends a message saying, "I'm not motivated to study. Please send me some famous quotes." When this message arrives at the server, the server processes it as follows:

[1180] 1. The server receives the message via the LINE Messaging API and extracts the user ID and text content.

[1181] 2. The server accesses the database and registers the user as a new user or checks for an existing user.

[1182] 3. The server analyzes the content of the text message using a natural language processing engine to identify the request and sentiment.

[1183] 4. The server selects a message from the database that best matches the user's emotion.

[1184] 5. The server formats the selected message for transmission to the communication terminal.

[1185] 6. Finally, the user sentiment analysis results and the sent message are stored in the database.

[1186] For example, in response to a prompt message sent by a user such as "I'm not motivated to study. Please send me a quote," the reply message displayed on the user's communication device is "Success comes from overcoming failure." In this way, the system can continue to provide personalized services to users by using the emotion history when selecting the next message.

[1187] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1188] Step 1:

[1189] The server receives text messages sent by users using the API of a communication application (for example, the LINE Messaging API). The input is the user ID and message content, and the output is the received message data. Specifically, the message data is sent to the server by Webhook via an HTTP POST request from the LINE platform.

[1190] Step 2:

[1191] The server accesses the database and verifies or registers the user's information. The input is the user ID and text content received in step 1, and the output is a record of the user information. Specifically, it queries the database (MySQL or PostgreSQL) for existing user information, and if it is a new user, it records the user ID and the content of the initial request.

[1192] Step 3:

[1193] The server analyzes the received text message to identify the user's request. The input is the message content received in step 1, and the output is the classification result of the request. Specifically, a natural language processing library (e.g., NLTK or spaCy) is used to extract keywords from the text and analyze the request.

[1194] Step 4:

[1195] The server analyzes emotions from text messages. The input is the message content received in step 1, and the output is the emotion analysis result. Specifically, it uses a natural language understanding API (e.g., IBM Watson or Google Cloud Natural Language) to identify and evaluate emotions from text.

[1196] Step 5:

[1197] The server selects an appropriate message from the database based on the user request and the results of sentiment analysis. The input is the analysis results from steps 3 and 4, and the output is the selected message. Specifically, it searches the database for messages that match the request and sentiment, and randomly selects one if necessary.

[1198] Step 6:

[1199] The server formats the selected message for transmission to the communication terminal. The input is the message selected in step 5, and the output is the formatted message data. Specifically, the message is converted into an appropriate transmission format such as JSON format.

[1200] Step 7:

[1201] The server sends the formatted message to the user's communication device using the communication application's API (for example, the LINE Messaging API). The input is the message data formatted in step 6, and the output is the transmission result. Specifically, the message is sent using the API's push method.

[1202] Step 8:

[1203] The server stores the user's emotion analysis results and the sent message in a database. The input is the data from steps 1, 4, and 5, and the output is the updated user emotion history. Specifically, the emotion analysis results and the sent message content are recorded in the corresponding tables in the database.

[1204] (Application example 2)

[1205] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1206] In modern society, users' stress, anxiety, and lack of motivation are becoming common problems. This creates a need for timely and encouraging messages. However, current systems have difficulty fully understanding a user's emotional state and recommending personalized content based on that understanding.

[1207] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a text message sent by a user from a communication terminal, means for connecting to a database and confirming or registering user information, means for selecting an appropriate message from a preset category based on a user request, means for formatting the selected message and sending it to the communication terminal, means for analyzing the emotional state of the user from the text message using an emotion analysis engine, and means for recommending content according to the user's emotional state based on the analysis results. This makes it possible to provide timely and personalized messages and content that are in line with the user's emotional state.

[1208] The "means for a user to receive a text message sent from a communication terminal" refers to a function for receiving a text message sent by a user through a communication device such as a mobile terminal or computer.

[1209] The "means for connecting to a database and confirming or registering user information" is a function for accessing a database and confirming existing user information or a function for recording new user information.

[1210] "Means for selecting an appropriate message within a predefined category based on a user request" is a function for selecting an optimal message from a predefined message category based on request data received from a user.

[1211] The "means for formatting the selected message and sending it to the communication terminal" is a function for converting the selected message into a format that can be displayed on the user's device and sending the message to the communication terminal.

[1212] "Means for analyzing a user's emotional state from text messages using an emotion analysis engine" refers to a function that uses an emotion analysis engine such as an AI or machine learning algorithm to analyze a user's emotions and feelings from sent text messages.

[1213] "Means for recommending content according to the user's emotional state based on the analysis results" refers to a function that selects and recommends content such as movies, music, and articles that are appropriate to the user's emotions based on the results of emotion analysis.

[1214] The system for realizing this application example analyzes text messages sent by users from their communication terminals and recommends content based on their emotional state. To implement this, the following hardware and software are used:

[1215] Hardware and software used

[1216] Hardware: communication devices (smartphones, tablets, PCs), servers, database servers

[1217] Software: Flask (web framework), SQLite (database management system), TextBlob (sentiment analysis library), LINE Messaging API (communication API)

[1218] System Operation Overview

[1219] 1. Receiving a message:

[1220] The server receives text messages sent by users from their communication devices (smartphones or tablets) via the LINE API. The received messages contain the user ID and message content.

[1221] 2. User information confirmation and registration:

[1222] The server accesses the database to check whether the user is an existing user or a new user. If the user is new, the server registers the user ID and the details of the first request in the database. If the user is an existing user, the server checks the past request history and settings.

[1223] 3. Message analysis:

[1224] The server uses TextBlob to analyze the sentiment of the received text message and determines the user's emotional state (positive or negative) based on the analysis result.

[1225] 4. Message Formatting and Recommendations:

[1226] The server then recommends content based on the user's emotional state based on the results of the emotion analysis. For example, if the user's emotional state is negative, it recommends encouraging and uplifting content. The content is appropriately selected from various categories, such as movies, music, and articles.

[1227] 5. Sending a message:

[1228] The server formats the selected content and sends it to the user's communication device using the LINE API.

[1229] 6. Emotion history storage:

[1230] The results of the user's emotion analysis and the content sent are stored in a database, allowing the system to refer to the user's emotion history and past requests when making recommendations next time.

[1231] Specific examples

[1232] For example, if a user sends a message from a communication terminal saying, "I've been feeling depressed lately," the server processes the message as follows.

[1233] The server receives the message and analyzes the content: "I'm feeling depressed."

[1234] Sentiment analysis detects negative emotional states.

[1235] The server selects appropriate cheer-up content from a database (e.g., "When you're feeling down, listen to 'Hey Jude' by the Beatles!").

[1236] The selected content is formatted in LINE format and sent to the user's communication device.

[1237] Prompt Sentence Examples

[1238] Generate a sample program for your first application that receives text messages from the front end, performs sentiment analysis, and recommends encouraging content if the user is sad.

[1239] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1240] Step 1:

[1241] Receiving messages

[1242] The server receives text messages sent from the user's device via the LINE API. The input is the text message and user ID, and the output is to pass them on to the server for processing. At this stage, the server temporarily stores the received data.

[1243] Step 2:

[1244] User information confirmation and registration

[1245] The server connects to the database and checks the user information based on the received user ID. The input is the user ID, and the output is the user information for an existing user, or the new registration procedure for a new user. The server registers the new user's information in the database, and for existing users, retrieves the past request history.

[1246] Step 3:

[1247] Emotion analysis

[1248] The server uses the TextBlob library to analyze the sentiment of received text messages. The input is the text message, and the output is the sentiment analysis result (positive, negative, neutral, etc.). The server extracts the emotional state of the message and stores the analysis data.

[1249] Step 4:

[1250] Message Selection

[1251] The server selects appropriate content from a database based on the results of sentiment analysis. The input is the sentiment analysis results and the user's request, and the output is recommended content based on the user's emotional state. The server extracts the optimal content from the database based on an algorithm.

[1252] Step 5:

[1253] Formatting and sending messages

[1254] The server formats the selected content into LINE format and sends it to the communication device. The input is the recommended content and the user ID, and the output is the formatted message sent. The server uses the LINE API to return the content message to the user.

[1255] Step 6:

[1256] Emotion history storage

[1257] The server stores the user's sentiment analysis results and submitted content in a database. The input is the sentiment analysis results and recommended content, and the output is an updated user sentiment history. The server records this data in the database so that it can be used for the next recommendation.

[1258] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1259] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1260] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1261] [Fourth embodiment]

[1262] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1263] 7, a 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.

[1264] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1265] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1266] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1267] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1268] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1269] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1270] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1271] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1272] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1273] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1274] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1275] This invention is an automated LINE messaging tool that helps test-takers maintain their motivation to study. When a user sends a motivational request message via a communication device, the system selects an appropriate message and replies to the user.

[1276] The embodiment for implementing this system will be described below.

[1277] User operations

[1278] First, a user connects to the system using the LINE app. The user can enter any text message and press the send button. For example, a user can send a message such as, "I'm not motivated to study. Please send me a quote."

[1279] Server Processing

[1280] 1. Receiving a message

[1281] The server receives the text message sent by the user, along with the message data (user ID, content) from the LINE platform.

[1282] 2. User information confirmation and registration

[1283] The server accesses the database and checks the user information. If it is a first-time user, the user information is registered in the database. If it is an existing user, the server checks the past request history and settings.

[1284] 3. Parsing the Request

[1285] The server analyzes the content of the received message. For example, if the message contains a request such as "Please send me a quote," the system selects the "Quote" category.

[1286] 4. Message Selection

[1287] Based on the request, the server randomly or by a specific algorithm selects an appropriate message from pre-defined categories (e.g., famous quotes, uplifting lyrics, questions and answers).

[1288] 5. Message Formatting

[1289] The server formats the selected message into a format that can be sent via LINE. For example, it formats the famous quote, "Success comes from overcoming failure."

[1290] 6. Sending a Message

[1291] The server uses the LINE API to send the formatted message to the user's device.

[1292] Reply to the user

[1293] The user receives the message sent from the server through the LINE app. For example, the message "Success comes from overcoming failure" is displayed on the LINE app.

[1294] Specific examples

[1295] As a specific example, if a user sends a message saying, "I'm not motivated to study. Please send me some great quotes," the server will process the message as follows:

[1296] 1. Reception and Analysis

[1297] User ID: 12345

[1298] Request: "Please send me a quote."

[1299] 2. Verify your user information

[1300] Register as a new user and request a "quote."

[1301] 3. Select a message

[1302] Randomly select the message "Success comes from overcoming failure" from the "Quotes" category in the database.

[1303] 4. Formatting and sending

[1304] The selected message is formatted in LINE format and sent to user ID 12345.

[1305] 5. User receives

[1306] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[1307] In this way, the system sends appropriate messages to the user and helps them maintain their motivation to study.

[1308] The processing flow will be explained below.

[1309] Step 1:

[1310] A user connects to the system using the LINE app, enters a text message, and presses the send button. For example, a user sends a message saying, "I'm not motivated to study. Please send me a quote."

[1311] Step 2:

[1312] The server receives the user's text message from the LINE platform. The received message data includes the user ID and the message content.

[1313] Step 3:

[1314] The server accesses the database and checks the user information. If it is a first-time user, the user ID and the details of the first request are registered in the database. If it is an existing user, the server checks the past request history and settings.

[1315] Step 4:

[1316] The server analyzes the content of the received message. For example, if the message contains a request to "send me a quote," the server selects the "Quote" category.

[1317] Step 5:

[1318] The server selects appropriate messages from a database based on the specified category. The messages are either randomly selected or extracted using a specific algorithm.

[1319] Step 6:

[1320] The server formats the selected message into a format that can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[1321] Step 7:

[1322] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained in step 2.

[1323] Step 8:

[1324] The user receives a message sent from the server through the LINE app. The message content is intended to motivate the user, such as "Success comes from overcoming failure."

[1325] Step 9:

[1326] Check the messages the user has received. For example, reading the message can make the user feel like, "Okay, let's try again!"

[1327] Example 1

[1328] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1329] In today's world, it is extremely difficult for students preparing for exams to maintain their motivation to study. In particular, when studying independently, there is a lack of timely encouragement or guidance, leaving students with limited means to maintain their sagging motivation. This results in a decline in learning efficiency and hinders the improvement of academic performance. To solve this problem, a method that is both easy for students to use and effective in maintaining their motivation is needed.

[1330] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1331] In this invention, the server includes: means for receiving text messages sent by users from their communication terminals; means for connecting to a database and confirming or registering user information; means for selecting an appropriate message from a preset category based on a user request; means for formatting the selected message and sending it to the communication terminal; means for adding identification information for identifying the user information; and means including an algorithm for randomly or specifically selecting an appropriate message from a specified category. This allows test-takers to always receive appropriate encouragement and guidance, thereby maintaining their motivation to study.

[1332] A "communication terminal" refers to an information communication device used by a user, and includes smartphones, tablets, personal computers, etc.

[1333] A "text message" is text information that a user sends through a communication terminal.

[1334] A "server" is a computing device that processes data received from a communication terminal and transmits necessary information.

[1335] A "database" is an information management system for storing user information and message contents.

[1336] "User information" refers to information about users of the system, including user IDs and request history.

[1337] A "request" is an action or information that a user requests from a system.

[1338] A "category" is a group of messages categorized according to the request content.

[1339] "Message formatting" refers to the act of converting a selected message into a format that can be sent.

[1340] "Identification information" refers to information for uniquely identifying a user.

[1341] An "algorithm" is a procedure or computational method for solving a particular problem.

[1342] "Random" means chosen at random without any set rules.

[1343] "Analysis" means detailed analysis of the content of received text messages.

[1344] The present invention is a LINE automatic messaging tool that helps test-takers maintain their motivation to study. When a user sends a request message to improve their motivation through a communication terminal, a server selects an appropriate message and sends it back to the user. A specific embodiment of the tool is described below.

[1345] Hardware and Software

[1346] The hardware and software required to implement the present invention are as follows:

[1347] Hardware:

[1348] 1. Communication devices: smartphones, tablets, computers, etc.

[1349] 2. Server: A high-performance computing device (e.g., cloud server, dedicated server).

[1350] software:

[1351] 1. LINE app: An application that allows users to send messages.

[1352] 2. Database Management System: A system for storing user information and message data (e.g., MySQL, PostgreSQL).

[1353] 3. Text analysis library: A library for analyzing the received message content (e.g., NLTK, SpaCy).

[1354] 4. Generative AI model: The AI ​​model (e.g., GPT-3) used to select and shape the appropriate message.

[1355] 5. LINE Platform API: API for receiving and sending messages through LINE.

[1356] Operation and processing flow

[1357] User operations

[1358] First, the user connects to the system using the LINE app installed on their device. The user can enter any text message and press the send button. For example, to send a message like this:

[1359] "I'm not motivated to study. Please send me some famous quotes."

[1360] Server Processing

[1361] 1. Receiving a message

[1362] The server receives text messages sent by users through the LINE Platform API. This data includes the user ID and message content.

[1363] 2. User information confirmation and registration

[1364] The server connects to the database and checks the user's information. If it is a first-time user, the server registers the user as a new user and saves the user ID and other basic information. If it is an existing user, the server reads and updates the user's past request history and settings.

[1365] 3. Parsing the Request

[1366] The server uses a text analysis library to analyze the content of the received message, for example, to extract the request content such as "Please send me a quote."

[1367] 4. Message Selection

[1368] The server selects appropriate messages from pre-defined categories (e.g., famous quotes, uplifting lyrics, questions and answers), using a generative AI model to select messages randomly or based on a specific algorithm.

[1369] 5. Message Formatting

[1370] The server formats the selected message into a format that can be sent in LINE format, and can also use a generative AI model to convert it into the appropriate format.

[1371] 6. Sending a Message

[1372] The server uses the LINE API to send the formatted message to the user's device. For example, the following message is sent:

[1373] "Success comes from overcoming failure." - Albert Einstein

[1374] Specific examples

[1375] For example, if a user uses a communication device to send a message to the LINE app saying, "I'm not motivated to study. Please send me some famous quotes.", the server processes the message as follows:

[1376] 1. Reception and Analysis

[1377] User ID: 12345

[1378] Request: "Please send me a quote."

[1379] 2. Verify your user information

[1380] The server registers the user as a new user and sets the request content as a "quote."

[1381] 3. Select a message

[1382] The server randomly selects the message "Success comes from overcoming failure" from the "Quotes" category in the database.

[1383] 4. Formatting and sending

[1384] The selected message is formatted in LINE format and sent to user ID 12345.

[1385] 5. User Reception

[1386] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[1387] This system helps test takers maintain their motivation to study by automatically replying to users with appropriate messages.

[1388] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1389] Step 1:

[1390] Receiving messages

[1391] Specific operation: The user uses a communication device to type a message into the LINE app. The user presses the send button to send a message such as, "I'm not motivated to study. Please send me a quote."

[1392] Input: The text message entered by the user into the LINE app.

[1393] Output: Message data (user ID, message content) received by the server via the LINE Platform API.

[1394] Processing content: The server receives message data using the LINE API and temporarily stores it.

[1395] Step 2:

[1396] User information confirmation and registration

[1397] Specific operation: The server connects to the database and searches for user information using the received user ID as a key.

[1398] Input: Received user ID.

[1399] Output: User information in the database or registration of new user information.

[1400] Processing content: The server checks the user information in the database, and if it is a new user, it registers the user ID and basic information in the database. If it is an existing user, it reads the past request history and settings.

[1401] Step 3:

[1402] Parsing the request

[1403] What happens: The server uses a text analysis library (e.g., NLTK or SpaCy) to parse the received message.

[1404] Input: Received text message content.

[1405] Output: Request details (specific category).

[1406] Processing details: The server performs text analysis, extracts the user's request from the message content, and classifies the request into one of three categories: "famous quote," "uplifting lyrics," or "question and answer."

[1407] Step 4:

[1408] Message Selection

[1409] What happens: The server connects to the database and selects messages from the appropriate category.

[1410] Input: Parsed request content (category).

[1411] Output: The selected message.

[1412] What it does: The server randomly or algorithmically selects the best message from a specified category. It may also use a generative AI model (e.g., GPT-3) to select the message. For example, it selects the message "Success comes from overcoming failure" from the "Quotes" category.

[1413] Step 5:

[1414] Message Formatting

[1415] Specific operation: The server formats the selected message into a format that can be sent in LINE format.

[1416] Input: The selected message.

[1417] Output: The formatted message.

[1418] Processing: The server uses a formatting function to format the selected message. It may also input a prompt to the generative AI model to generate the formatted result.

[1419] Step 6:

[1420] Sending a message

[1421] Specific operation: The server sends the formatted message to the user.

[1422] Input: A formatted message and a user ID.

[1423] Output: The message that is displayed on the user's communication terminal.

[1424] Processing content: The server uses the LINE API to send the formatted message to the user's communication device. For example, the message "Success comes from overcoming failure" is displayed in the user's LINE app.

[1425] (Application example 1)

[1426] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1427] Modern food delivery services provide users with the convenience of ordering, but unique and value-added services are required. Furthermore, if users lack motivation or psychological support, their quality of life may decline. It is necessary to solve this issue and provide more value-added food delivery services to improve the user experience.

[1428] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1429] In this invention, the server includes means for receiving text messages sent by users from their communication terminals, means for connecting to a database and confirming or registering user information, means for selecting an appropriate message from a preset category based on a user request, means for formatting the selected message and sending it to the communication terminal, means for providing motivational messages to users when ordering food delivery, and means for automatically translating messages in multiple languages ​​and displaying them in a way that suits the user interface. This allows users to receive mental support when ordering food delivery, thereby improving their quality of life.

[1430] A "communication terminal" is a device that allows a user to send and receive messages, such as a smartphone or tablet.

[1431] A "database" is an information management system that stores user information, message data, etc., and can retrieve and update them as needed.

[1432] "Request" refers to an instruction or request sent by a user through a communication terminal to receive a motivation message, etc.

[1433] "Predefined categories" are categories into which motivational messages are categorized, and include different themes such as quotes, personal experiences, and encouragement.

[1434] "Formatting" refers to the process of formatting a selected message for proper display on a communications terminal.

[1435] "Food delivery" refers to a service that delivers food from restaurants to a location specified by the user.

[1436] "Motivational messages" are messages intended to improve the user's mental motivation, and include famous quotes, words of encouragement, success stories, and the like.

[1437] "Multilingual" refers to the ability to accommodate different languages ​​and provide messages in the user's language of choice.

[1438] "Automatic translation" means the process of converting a message written in one language into another language.

[1439] A "user interface" refers to the screens and operating methods that allow a user to interact with an application, and is designed to enhance user convenience.

[1440] The system for implementing this invention allows users to receive motivational messages when placing an order in a food delivery service. This system is composed of the following main components:

[1441] First, a user accesses a food delivery application using a communication terminal (e.g., a smartphone or tablet) and orders food. The communication terminal then sends the user's request along with order information to the server.

[1442] The server processes the transaction using the following means:

[1443] 1. Receiving means:

[1444] The server receives a text message sent by the user from the communication terminal, the message including the category of motivation message requested by the user.

[1445] 2. Database connection method:

[1446] The server connects to the database to check user information and register new user information if necessary. For existing users, it checks past request history and settings.

[1447] 3. Message selection method:

[1448] Based on the user's request, the server selects an appropriate message from pre-defined categories (e.g., quotes, experiences, encouragement).

[1449] 4. Shaping means:

[1450] Formats the selected message for proper display on the communication device, and automatically translates the message into the user's preferred language if multilingual support is available.

[1451] 5. Motivational message delivery methods:

[1452] The formatted message is provided to users through the food delivery order confirmation screen or messaging apps such as LINE.

[1453] 6. Multilingual support methods:

[1454] The message is automatically translated and displayed appropriately in the language displayed on the user's communication terminal.

[1455] As a concrete example, we will explain the process when a user requests a "success story." When a user places an order on a food delivery application and requests a "success story," this information is sent from the communication terminal to the server. The server randomly selects a message that falls into the "success story" category from the database, formats it, and automatically translates it into the user's language. The selected message is then sent to the user via LINE. The user's LINE will display the message "How I passed my university entrance exam..."

[1456] Example prompt:

[1457] User ID: 12345

[1458] Category: "Success Stories"

[1459] The hardware used is mainly smartphones and tablets, and the software used is LINE Messaging API, Python 3.6+, and the required json and random modules. This system allows users to receive mental support when ordering food delivery, improving their quality of life.

[1460] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1461] Step 1:

[1462] A user selects a dish and places an order in a food delivery app.

[1463] Input: User order information and motivation message category request

[1464] Specific operation: The user uses a communication terminal to order food and drink, and at the end, enters the category of the motivational message (e.g., "famous quote") into the request form.

[1465] Step 2:

[1466] The communication terminal transmits the order information and request data to the server.

[1467] Input: User's order information and category request

[1468] Output: Order information and category request data sent to the server

[1469] Specific operation: Once the order is confirmed, the communication terminal sends the input information, including the user ID, order details, and requested category, to the server.

[1470] Step 3:

[1471] The server checks the user information in the database and registers the user if he is a new user.

[1472] Input: User ID

[1473] Output: User information confirmation result, new registration or existing confirmation

[1474] Specific operation: The server accesses the database and checks the user information based on the user ID. If it is a first-time user, the user information is newly registered in the database.

[1475] Step 4:

[1476] The server analyzes the user's request and selects the appropriate category of message.

[1477] Input: Request content (e.g. "Famous quote")

[1478] Output: An appropriate message (e.g., "Success comes from overcoming failure.")

[1479] Specific operation: The server analyzes the request content and randomly selects messages within a pre-defined category from a database.

[1480] Step 5:

[1481] The selected message is formatted so that it can be displayed appropriately on the communication terminal.

[1482] Input: Selected message

[1483] Output: Formatted message

[1484] Specific operation: The server formats the selected message to match the LINE format or application display format, and if multilingual, automatically translates it into the user's language.

[1485] Step 6:

[1486] The formatted message is sent from the server to the communication terminal.

[1487] Input: Formatted message

[1488] Output: Message sent to the user's communication device

[1489] Specific operation: The server uses the LINE Messaging API to send the formatted message to the user's LINE account or application.

[1490] Step 7:

[1491] The user checks the message received on the communication terminal.

[1492] Input: Received message

[1493] Output: User confirmation

[1494] Specific actions: The user opens the message received on the communication device, checks the contents, and receives encouragement and motivation.

[1495] Through each step, users can receive psychological support when using food delivery services and improve their quality of life.

[1496] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1497] This system receives text messages sent by users through the LINE app, analyzes the message content and emotions, and automatically replies with appropriate encouraging or uplifting messages. Furthermore, the system stores the user's emotional history in a database and reflects this in the next message selection, providing a more personalized service.

[1498] User operations

[1499] First, the user connects to the system using the LINE app. For example, the user types a text message such as "I'm not motivated to study. Please send me a quote," and presses the send button.

[1500] Server Processing

[1501] 1. Receiving a message

[1502] The server receives the user's text message from the LINE platform. The received message contains the user ID and message content.

[1503] 2. User information confirmation and registration

[1504] The server accesses the database and checks the user information. If the user is using the service for the first time, the user ID and the details of the first request are registered in the database. If the user is an existing user, the server checks the past request history and settings.

[1505] 3. Parsing the Request

[1506] The server analyzes the content of the received text message. For example, if the message contains a request to "send me a quote," the system selects the "Quotes" category.

[1507] 4. Analysis by Emotion Engine

[1508] The emotion engine installed on the server analyzes the emotions in the user's text message. Based on this analysis, it selects a message from a category that matches the user's current emotion. For example, if the user is feeling unmotivated, an encouraging message will be selected.

[1509] 5. Message Selection

[1510] The server selects an appropriate message from a database based on the user's sentiment and request, which can be chosen randomly or extracted by a specific algorithm.

[1511] 6. Message Formatting

[1512] The server formats the selected message so that it can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[1513] 7. Sending a Message

[1514] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained initially.

[1515] 8. Emotional history storage

[1516] The server stores the results of the user's emotion analysis and the sent message in a database, allowing the user's emotion history to be used as a reference when selecting a message next time.

[1517] Reply to the user

[1518] The user receives a reply message from the server through the LINE app. For example, a famous quote such as "Success comes from overcoming failure" is displayed in the user's LINE app.

[1519] Specific examples

[1520] As a specific example, if a user sends a message saying, "I'm not motivated to study. Please send me some famous quotes," the server will process it as follows:

[1521] 1. Reception and Analysis

[1522] User ID: 12345

[1523] Request: "Please send me a quote."

[1524] 2. Verify your user information

[1525] Register as a new user and confirm your request.

[1526] 3. Emotion analysis

[1527] Extract the emotion of "lack of motivation" from the message.

[1528] 4. Message Selection

[1529] From the database, select the message "Success comes from overcoming failure" from the "famous quotes" category that is appropriate for the state of "lack of motivation."

[1530] 5. Formatting and sending

[1531] The selected message is formatted in LINE format and sent to user ID 12345.

[1532] 6. Emotion history storage

[1533] The user's sentiment analysis results and the sent message are stored in a database.

[1534] 7. User receives and confirms

[1535] User's LINE: "Success comes from overcoming failure." - Albert Einstein

[1536] In this way, the present invention provides users with an effective means of receiving messages optimized for their emotions and maintaining their motivation to study, thereby enabling personalized support tailored to the needs of each individual user.

[1537] The processing flow will be explained below.

[1538] Step 1:

[1539] A user connects to the system using the LINE app. The user types a text message and presses the send button. For example, the user sends a message saying, "I'm not motivated to study. Please send me a quote."

[1540] Step 2:

[1541] The server receives the user's text message from the LINE platform. The received message data includes the user ID and the message content.

[1542] Step 3:

[1543] The server accesses the database and checks the user information. If the user is a new user, the user ID and the details of the first request are registered in the database. If the user is an existing user, the server checks the past request history and settings.

[1544] Step 4:

[1545] The server analyzes the content of the received message. For example, if the message contains a request to "send me a quote," the server selects the "Quote" category.

[1546] Step 5:

[1547] The emotion engine installed on the server analyzes the user's text messages and recognizes their emotions, such as "unmotivated" or "tired."

[1548] Step 6:

[1549] The server selects a message from a category that matches the user's current emotion based on the analysis results of the emotion engine. For example, if the user is feeling unmotivated, an encouraging message will be selected.

[1550] Step 7:

[1551] The server selects appropriate messages from the database based on the sentiment analysis results and the user's request. The messages are either randomly selected or extracted using a specific algorithm.

[1552] Step 8:

[1553] The server formats the selected message into a format that can be sent via LINE. For example, it converts the famous quote, "Success comes from overcoming failure," into the appropriate format.

[1554] Step 9:

[1555] The server uses the LINE API to send the formatted message to the user's device. The destination corresponds to the user ID obtained in step 2.

[1556] Step 10:

[1557] The user receives the message sent from the server through the LINE app. For example, the message "Success comes from overcoming failure" is displayed on the LINE app.

[1558] Step 11:

[1559] The user checks the messages they receive. For example, they read the message and feel like, "Okay, let's try again!"

[1560] Step 12:

[1561] The server stores the user's emotion analysis results and the sent message in a database, allowing the server to refer to the user's emotion history when selecting a message next time.

[1562] Example 2

[1563] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1564] Conventional message response systems often use standardized replies without considering the user's emotions, making it difficult to provide appropriate messages that reflect the user's situation and mood. As a result, users are not fully satisfied, and the system's usability is reduced. In addition, the lack of a function to save the user's emotional history means that the next time a message is selected, a non-personalized response may be sent.

[1565] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for receiving a text message sent by a user from a communication terminal, a means for connecting to a database and confirming or registering user information, a means for selecting an appropriate message from a preset category based on a user request, a means for formatting the selected message and sending it to the communication terminal, a means for analyzing emotions from the user's text message, and a means for saving the emotion analysis result in the database. This makes it possible to provide a message optimized for the user's emotions and to realize a personalized service by using the user's emotion history for the next message selection.

[1566] A "communication terminal" is a device that a user uses to send and receive text messages, and includes smartphones, tablets, personal computers, etc.

[1567] A "text message" is information in the form of text that a user sends via a communication terminal.

[1568] A "database" is a system that systematically stores and manages data such as user information, messages, and emotion analysis results.

[1569] "Sentiment analysis" is the process of identifying and assessing a user's current emotions from a text message.

[1570] "Message selection" refers to extracting the most suitable message from a pre-defined category based on the user's request and sentiment.

[1571] "Message formatting" refers to converting a selected message into a format suitable for transmission to a communication terminal.

[1572] "Emotion history" is data that records the results of a user's emotion analysis and related messages in chronological order.

[1573] This system receives text messages sent by users through communication applications, analyzes the content and emotions of the messages, and automatically replies with appropriate encouraging or uplifting messages. It also stores the user's emotional history in a database and reflects this in the next message selection, providing a more personalized service.

[1574] User operations

[1575] First, the user connects to the system using a communication application. For example, the user types a text message such as "I'm not motivated to study. Please send me a quote," and presses the send button. This message is then sent via a platform such as LINE. At this point, the user does not need to perform any particularly complicated settings or operations; the system works simply by sending a message as usual.

[1576] Hardware and software used

[1577] server

[1578] The server is mainly configured using the following hardware and software:

[1579] Hardware:

[1580] A server machine with high-speed internet connection

[1581] High-performance processor and sufficient memory capacity

[1582] software:

[1583] LINE Messaging API: Used to receive and reply to text messages

[1584] MySQL or PostgreSQL: A database that stores user information and emotion history

[1585] IBM Watson and Google Cloud Natural Language API: Natural language processing engines for sentiment analysis

[1586] Python and Node.js: the main implementation languages ​​for the program

[1587] Server Processing

[1588] When the server receives a text message sent by a user through a communication application (e.g., LINE), it analyzes it and generates an appropriate reply message. The server first extracts the user ID and message content from the received message. It then accesses a database to confirm or register the user's information. If the user is not registered, the server records the user ID and the content of the initial request in the database.

[1589] The server then analyzes the content of the text message to identify the user's request and emotion. For example, a request such as "Please send me a quote" would be assigned to the "Quote" category. Sentiment analysis also identifies the user's emotional state as "unmotivated."

[1590] The server then selects an appropriate message from its database based on the user's emotions and requests. The selected message is then formatted by the server again and sent back to the user's device. This entire process is automated, and the user waits again until they receive the reply message in the LINE app.

[1591] Specific examples

[1592] As a concrete example, consider the case where a user sends a message saying, "I'm not motivated to study. Please send me some famous quotes." When this message arrives at the server, the server processes it as follows:

[1593] 1. The server receives the message via the LINE Messaging API and extracts the user ID and text content.

[1594] 2. The server accesses the database and registers the user as a new user or checks for an existing user.

[1595] 3. The server analyzes the content of the text message using a natural language processing engine to identify the request and sentiment.

[1596] 4. The server selects a message from the database that best matches the user's emotion.

[1597] 5. The server formats the selected message for transmission to the communication terminal.

[1598] 6. Finally, the user sentiment analysis results and the sent message are stored in the database.

[1599] For example, in response to a prompt message sent by a user such as "I'm not motivated to study. Please send me a quote," the reply message displayed on the user's communication device is "Success comes from overcoming failure." In this way, the system can continue to provide personalized services to users by using the emotion history when selecting the next message.

[1600] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1601] Step 1:

[1602] The server receives text messages sent by users using the API of a communication application (for example, the LINE Messaging API). The input is the user ID and message content, and the output is the received message data. Specifically, the message data is sent to the server by Webhook via an HTTP POST request from the LINE platform.

[1603] Step 2:

[1604] The server accesses the database and verifies or registers the user's information. The input is the user ID and text content received in step 1, and the output is a record of the user information. Specifically, it queries the database (MySQL or PostgreSQL) for existing user information, and if it is a new user, it records the user ID and the content of the initial request.

[1605] Step 3:

[1606] The server analyzes the received text message to identify the user's request. The input is the message content received in step 1, and the output is the classification result of the request. Specifically, a natural language processing library (e.g., NLTK or spaCy) is used to extract keywords from the text and analyze the request.

[1607] Step 4:

[1608] The server analyzes emotions from text messages. The input is the message content received in step 1, and the output is the emotion analysis result. Specifically, it uses a natural language understanding API (e.g., IBM Watson or Google Cloud Natural Language) to identify and evaluate emotions from text.

[1609] Step 5:

[1610] The server selects an appropriate message from the database based on the user request and the results of sentiment analysis. The input is the analysis results from steps 3 and 4, and the output is the selected message. Specifically, it searches the database for messages that match the request and sentiment, and randomly selects one if necessary.

[1611] Step 6:

[1612] The server formats the selected message for transmission to the communication terminal. The input is the message selected in step 5, and the output is the formatted message data. Specifically, the message is converted into an appropriate transmission format such as JSON format.

[1613] Step 7:

[1614] The server sends the formatted message to the user's communication device using the communication application's API (for example, the LINE Messaging API). The input is the message data formatted in step 6, and the output is the transmission result. Specifically, the message is sent using the API's push method.

[1615] Step 8:

[1616] The server stores the user's emotion analysis results and the sent message in a database. The input is the data from steps 1, 4, and 5, and the output is the updated user emotion history. Specifically, the emotion analysis results and the sent message content are recorded in the corresponding tables in the database.

[1617] (Application example 2)

[1618] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1619] In modern society, users' stress, anxiety, and lack of motivation are becoming common problems. This creates a need for timely and encouraging messages. However, current systems have difficulty fully understanding a user's emotional state and recommending personalized content based on that understanding.

[1620] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a text message sent by a user from a communication terminal, means for connecting to a database and confirming or registering user information, means for selecting an appropriate message from a preset category based on a user request, means for formatting the selected message and sending it to the communication terminal, means for analyzing the emotional state of the user from the text message using an emotion analysis engine, and means for recommending content according to the user's emotional state based on the analysis results. This makes it possible to provide timely and personalized messages and content that are in line with the user's emotional state.

[1621] The "means for a user to receive a text message sent from a communication terminal" refers to a function for receiving a text message sent by a user through a communication device such as a mobile terminal or computer.

[1622] The "means for connecting to a database and confirming or registering user information" is a function for accessing a database and confirming existing user information or a function for recording new user information.

[1623] "Means for selecting an appropriate message within a predefined category based on a user request" is a function for selecting an optimal message from a predefined message category based on request data received from a user.

[1624] The "means for formatting the selected message and sending it to the communication terminal" is a function for converting the selected message into a format that can be displayed on the user's device and sending the message to the communication terminal.

[1625] "Means for analyzing a user's emotional state from text messages using an emotion analysis engine" refers to a function that uses an emotion analysis engine such as an AI or machine learning algorithm to analyze a user's emotions and feelings from sent text messages.

[1626] "Means for recommending content according to the user's emotional state based on the analysis results" refers to a function that selects and recommends content such as movies, music, and articles that are appropriate to the user's emotions based on the results of emotion analysis.

[1627] The system for realizing this application example analyzes text messages sent by users from their communication terminals and recommends content based on their emotional state. To implement this, the following hardware and software are used:

[1628] Hardware and software used

[1629] Hardware: communication devices (smartphones, tablets, PCs), servers, database servers

[1630] Software: Flask (web framework), SQLite (database management system), TextBlob (sentiment analysis library), LINE Messaging API (communication API)

[1631] System Operation Overview

[1632] 1. Receiving a message:

[1633] The server receives text messages sent by users from their communication devices (smartphones or tablets) via the LINE API. The received messages contain the user ID and message content.

[1634] 2. User information confirmation and registration:

[1635] The server accesses the database to check whether the user is an existing user or a new user. If the user is new, the server registers the user ID and the details of the first request in the database. If the user is an existing user, the server checks the past request history and settings.

[1636] 3. Message analysis:

[1637] The server uses TextBlob to analyze the sentiment of the received text message and determines the user's emotional state (positive or negative) based on the analysis result.

[1638] 4. Message Formatting and Recommendations:

[1639] The server then recommends content based on the user's emotional state based on the results of the emotion analysis. For example, if the user's emotional state is negative, it recommends encouraging and uplifting content. The content is appropriately selected from various categories, such as movies, music, and articles.

[1640] 5. Sending a message:

[1641] The server formats the selected content and sends it to the user's communication device using the LINE API.

[1642] 6. Emotion history storage:

[1643] The results of the user's emotion analysis and the content sent are stored in a database, allowing the system to refer to the user's emotion history and past requests when making recommendations next time.

[1644] Specific examples

[1645] For example, if a user sends a message from a communication terminal saying, "I've been feeling depressed lately," the server processes the message as follows.

[1646] The server receives the message and analyzes the content: "I'm feeling depressed."

[1647] Sentiment analysis detects negative emotional states.

[1648] The server selects appropriate cheer-up content from a database (e.g., "When you're feeling down, listen to 'Hey Jude' by the Beatles!").

[1649] The selected content is formatted in LINE format and sent to the user's communication device.

[1650] Prompt Sentence Examples

[1651] Generate a sample program for your first application that receives text messages from the front end, performs sentiment analysis, and recommends encouraging content if the user is sad.

[1652] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1653] Step 1:

[1654] Receiving messages

[1655] The server receives text messages sent from the user's device via the LINE API. The input is the text message and user ID, and the output is to pass them on to the server for processing. At this stage, the server temporarily stores the received data.

[1656] Step 2:

[1657] User information confirmation and registration

[1658] The server connects to the database and checks the user information based on the received user ID. The input is the user ID, and the output is the user information for an existing user, or the new registration procedure for a new user. The server registers the new user's information in the database, and for existing users, retrieves the past request history.

[1659] Step 3:

[1660] Emotion analysis

[1661] The server uses the TextBlob library to analyze the sentiment of received text messages. The input is the text message, and the output is the sentiment analysis result (positive, negative, neutral, etc.). The server extracts the emotional state of the message and stores the analysis data.

[1662] Step 4:

[1663] Message Selection

[1664] The server selects appropriate content from a database based on the results of sentiment analysis. The input is the sentiment analysis results and the user's request, and the output is recommended content based on the user's emotional state. The server extracts the optimal content from the database based on an algorithm.

[1665] Step 5:

[1666] Formatting and sending messages

[1667] The server formats the selected content into LINE format and sends it to the communication device. The input is the recommended content and the user ID, and the output is the formatted message sent. The server uses the LINE API to return the content message to the user.

[1668] Step 6:

[1669] Emotion history storage

[1670] The server stores the user's sentiment analysis results and submitted content in a database. The input is the sentiment analysis results and recommended content, and the output is an updated user sentiment history. The server records this data in the database so that it can be used for the next recommendation.

[1671] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1672] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1673] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1674] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1675] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1676] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1677] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1678] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1679] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1680] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1681] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1682] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1683] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1684] 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.

[1685] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1686] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1687] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1688] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1689] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1690] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1691] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1692] The following is further disclosed regarding the above embodiment.

[1693] (Claim 1)

[1694] means for a user to receive a text message sent from a communication terminal;

[1695] A means for connecting to the database and verifying or registering user information;

[1696] means for selecting an appropriate message within a predefined category based on a user request;

[1697] means for formatting and transmitting the selected message to the communication terminal;

[1698] A system including:

[1699] (Claim 2)

[1700] 10. The system of claim 1, further comprising: means for analyzing a text message sent by a user and extracting a request content.

[1701] (Claim 3)

[1702] 10. The system of claim 1, further comprising means for randomly selecting an appropriate message.

[1703] "Example 1"

[1704] (Claim 1)

[1705] means for a user to receive a text message sent from a communication terminal;

[1706] A means for connecting to the database and verifying or registering user information;

[1707] means for selecting an appropriate message within a predefined category based on a user request;

[1708] means for formatting and transmitting the selected message to the communication terminal;

[1709] means for adding identification information for identifying user information;

[1710] a means including an algorithm for randomly or specifically selecting appropriate messages from a specified category;

[1711] A system including:

[1712] (Claim 2)

[1713] 10. The system of claim 1, further comprising: means for analyzing a text message sent by a user and extracting a request content.

[1714] (Claim 3)

[1715] 10. The system of claim 1, further comprising means for randomly selecting an appropriate message.

[1716] "Application Example 1"

[1717] (Claim 1)

[1718] means for a user to receive a text message sent from a communication terminal;

[1719] A means for connecting to the database and verifying or registering user information;

[1720] means for selecting an appropriate message within a predefined category based on a user request;

[1721] means for formatting and transmitting the selected message to the communication terminal;

[1722] a means for providing a motivational message to a user when ordering food delivery;

[1723] A means for automatically translating multilingual messages and displaying them in a user interface;

[1724] A system including:

[1725] (Claim 2)

[1726] 10. The system of claim 1, further comprising: means for analyzing a text message sent by a user and extracting a request content.

[1727] (Claim 3)

[1728] 10. The system of claim 1, further comprising means for randomly selecting an appropriate message.

[1729] "Example 2: Combining Emotion Engines"

[1730] (Claim 1)

[1731] means for a user to receive a text message sent from a communication terminal;

[1732] A means for connecting to the database and verifying or registering user information;

[1733] means for selecting an appropriate message within a predefined category based on a user request;

[1734] means for formatting and transmitting the selected message to the communication terminal;

[1735] means for analyzing sentiment from a user's text message;

[1736] a means for storing the sentiment analysis results in a database;

[1737] A system including:

[1738] (Claim 2)

[1739] 10. The system of claim 1, further comprising: means for analyzing a text message sent by a user and extracting a request content.

[1740] (Claim 3)

[1741] 10. The system of claim 1, further comprising means for randomly selecting an appropriate message.

[1742] "Application example 2 when combining emotion engines"

[1743] (Claim 1)

[1744] means for a user to receive a text message sent from a communication terminal;

[1745] A means for connecting to the database and verifying or registering user information;

[1746] means for selecting an appropriate message within a predefined category based on a user request;

[1747] means for formatting and transmitting the selected message to the communication terminal;

[1748] means for analyzing an emotional state from a user's text message using an emotion analysis engine;

[1749] A means for recommending content according to the emotional state of the user based on the analysis results;

[1750] A system including:

[1751] (Claim 2)

[1752] 10. The system of claim 1, further comprising: means for analyzing a text message sent by a user and extracting a request content.

[1753] (Claim 3)

[1754] 10. The system of claim 1, further comprising means for randomly selecting an appropriate message. [Explanation of symbols]

[1755] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for a user to receive a text message sent from a communication terminal; A means for connecting to the database and verifying or registering user information; means for selecting an appropriate message within a predefined category based on a user request; means for formatting and transmitting the selected message to the communication terminal; A system including:

2. 2. The system according to claim 1, further comprising means for analyzing a text message sent by a user and extracting the request content.

3. 10. The system of claim 1, further comprising means for randomly selecting an appropriate message.

Images