System

Abstract

A system is provided.SOLUTION: A system comprising: interface means for a user to input information; means for transmitting the user input information to a server; natural language processing means for the server to analyze the user input information; means for the server to retrieve relevant information from a database based on the analysis results; means for the server to generate the retrieved information and respond to the user; and means for the user to confirm the generated response and input additional information.SELECTED DRAWING: Figure 1

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] As society ages, many people are beginning to consider end-of-life planning. However, there is a wide variety of information available on end-of-life planning, making it difficult for people to independently find the appropriate procedures for their specific circumstances. In particular, writing a will and taking legal procedures requires specialized knowledge, and there is a risk of acting on incorrect information. Furthermore, properly collecting and managing the necessary information is difficult, requiring time and effort. To solve these problems and enable users to proceed with end-of-life planning with peace of mind, a simple and reliable information and support system is needed. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes an interface for users to input information, a means for transmitting the user-inputted information to a server, a natural language processing means for the server to analyze the user-inputted information, a means for the server to search a database for appropriate information based on the analysis results, a means for the server to generate the searched information and respond to the user, and a means for the user to confirm the generated response and input additional information. This system allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific situation in real time. Furthermore, by using the HTTPS protocol for secure data transmission and reception, it is possible to provide efficient support while maintaining the reliability and security of information.

[0006] "User" means any person or entity that utilizes the System to input information and receive results.

[0007] "Interface means" refers to a screen or input device that allows a user to access the system and input information.

[0008] "Server" means a central processing unit that receives information sent by a user, analyzes and processes it, and generates and returns an appropriate response.

[0009] "Natural language processing means" is a technology that analyzes information entered by a user in text format and interprets its intent and meaning.

[0010] A "database" is a huge collection of data that a system uses to search and store the information it needs.

[0011] "Means for generating information" refers to a mechanism for creating specific information or suggestions to be provided to users based on analysis and search results.

[0012] A "means for confirming a response" is an interface that allows a user to confirm the information received from the system and input the next action.

[0013] The "HTTPS protocol" is a communication method that encrypts data transmission and reception and ensures secure communication. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

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

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

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

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0029] 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.

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

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system mainly consists of a user interface, a server, natural language processing, a database, information generation means, response confirmation means, and secure communication means (HTTPS protocol).

[0036] System configuration and operation

[0037] User Interface Means

[0038] User interface means consist of a screen or input device for users to input information. For example, the application screen of a smartphone or PC falls into this category. Through this screen, users can enter questions or concerns into text boxes.

[0039] server

[0040] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0041] Natural language processing tools

[0042] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content of the user's question and intent. For example, if someone enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write," and search for information showing specific steps.

[0043] Database

[0044] The database is a data repository that allows the system to search and store appropriate information. It stores various information related to the process of creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to the user's request.

[0045] Information generation means

[0046] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0047] Response confirmation means

[0048] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0049] Secure communication method (HTTPS protocol)

[0050] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0051] Specific examples

[0052] For example, suppose a user types the question, "Who can witness a notarized will?"

[0053] 1. The user enters a question on the device and presses the send button.

[0054] 2. The device sends the entered question as a request to the server.

[0055] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0056] 4. The server searches the database to find information regarding witness requirements for notarized wills.

[0057] 5. The server uses the relevant information to generate a specific response such as, "A person who meets the following conditions can be a witness to a notarized will..."

[0058] 6. The server generates a response and sends it to the terminal, where the user confirms it.

[0059] 7. The user asks further questions or clarifies based on the information displayed.

[0060] This allows users to easily access specialized information from the comfort of their own home and proceed with end-of-life planning that is appropriate to their own circumstances.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] Users launch the "End-of-Life Concierge" application on their smartphone or computer and enter their login information to authenticate.

[0064] Step 2:

[0065] The device sends login information to the server, and if authentication is successful, the user is shown a chat screen.

[0066] Step 3:

[0067] Users enter their questions or concerns as text on the chat screen and press the send button.

[0068] Step 4:

[0069] The terminal composes the user's input information as request data and transmits it to the server using the HTTPS protocol.

[0070] Step 5:

[0071] The server receives the request and launches a natural language processing engine.

[0072] Step 6:

[0073] The server uses natural language processing tools to analyze the user's input text and extract key keywords and their intent.

[0074] Step 7:

[0075] Based on the analysis results, the server searches the database and collects related information.

[0076] Step 8:

[0077] The server generates a response message for the user based on the collected information.

[0078] Step 9:

[0079] The server sends the generated response message to the terminal via the HTTPS protocol.

[0080] Step 10:

[0081] The terminal decodes the response message received from the server and displays it on the chat screen.

[0082] Step 11:

[0083] The user reviews the displayed response, enters additional questions or new information as needed, and submits again.

[0084] Step 12:

[0085] The terminal again transmits new request data to the server and repeats the series of processes from step 5 to step 11.

[0086] This allows users to obtain specific and accurate information necessary for their end-of-life planning through continuous interaction.

[0087] Example 1

[0088] 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."

[0089] In modern society, it is extremely important for users to obtain specialized information quickly and accurately. Information regarding end-of-life planning is particularly complex, and while accurate information tailored to individual circumstances is required, it is difficult to find appropriate sources of information. Furthermore, from a security perspective, data protection is necessary when sending and receiving information. A system that addresses these issues is needed.

[0090] 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.

[0091] In this invention, the server includes input means for a user to input information, means for transmitting the information input by the user as data, natural language processing means for the information processing device to analyze the information input by the user, means for the information processing device to search for appropriate information from an information storage device based on the analysis results, information generation means for the information processing device to generate the searched information and respond to the user, input means for the user to check the generated response and input additional information, and secure communication means for securely transmitting and receiving information, thereby enabling users to quickly and safely obtain accurate information tailored to their individual circumstances.

[0092] A "user" is an entity that utilizes a system to input information and obtain a response.

[0093] "Input means" refers to a device or interface through which a user inputs information, and examples include text boxes on smartphones and personal computers.

[0094] "Means for transmitting data" refers to a mechanism for transmitting input information to a server, and includes secure communication methods such as the HTTPS protocol.

[0095] An "information processing device" is a central processing unit that performs multiple processes and analyzes information received from a user.

[0096] "Natural language processing means" refers to technology for analyzing text information entered by a user and understanding its content and intent, and includes generative models.

[0097] "Information storage device" refers to a database or data repository used to retrieve relevant information based on the results of an analysis.

[0098] "Information generation means" refers to a mechanism for generating specific responses or information based on search results.

[0099] "Secure communication means" refers to technology for securely sending and receiving information, including the HTTPS protocol, which uses encrypted communications.

[0100] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. The system configuration is as follows.

[0101] User Interface Means

[0102] User interface means consist of a screen or input device for users to input information. Specifically, this corresponds to the application screen of a smartphone or PC. Through this screen, users can enter their questions or concerns into a text box and press the send button.

[0103] Terminal

[0104] The device is the means by which the information entered by the user is sent to the server, and uses the HTTPS protocol to encrypt and transmit data securely. For example, a smartphone or PC is one such device.

[0105] server

[0106] The server is a central processing unit that receives, analyzes, and processes information sent by users. The server is equipped with the following means:

[0107] Natural language processing tools

[0108] The server uses natural language processing (e.g., a generative AI model) to analyze the text information entered by the user. This allows it to accurately understand the content and intent of the user's question. For example, if the user enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write" and search for information showing specific steps.

[0109] Information Storage Device

[0110] The information storage device is a data repository that allows the system to search for and store appropriate information. For example, it stores various information related to procedures for creating wills, legal procedures, and end-of-life planning. The server uses this information to provide information in response to user requests.

[0111] Information generation means

[0112] The information generation means is a mechanism for creating specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0113] Secure Communication Methods

[0114] The server uses the HTTPS protocol to ensure secure transmission of information, which encrypts communication between the user and the server and prevents information leakage and unauthorized access.

[0115] Specific examples

[0116] For example, suppose a user types the question, "Who can witness a notarized will?"

[0117] The user enters a question into the terminal and presses the send button.

[0118] The terminal sends the entered question as a request to the server.

[0119] The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0120] The server searches the information storage device to find information regarding the requirements for witnesses to notarized wills.

[0121] Based on the relevant information, the server generates a specific response such as "A person who meets the following conditions can be a witness to a notarized will..."

[0122] The server generates a response and sends it to the terminal, where the user confirms it.

[0123] The user can then ask further questions or make further confirmations based on the displayed information, for example, by entering a follow-up question such as, "What are the conditions?"

[0124] An example of a prompt sentence could be a text input such as "Who can be a witness to a notarized will?"

[0125] This allows users to easily access specialized information from the comfort of their own home and proceed with end-of-life planning that is appropriate to their own circumstances.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1: User Enters Information

[0128] The user enters their question or concern into the text box on the application screen of their smartphone or computer and presses the send button. For example, they might type, "Please tell me how to write a will." At this time, the information entered by the user is generated as input data.

[0129] Step 2: The device sends a request to the server

[0130] The terminal receives the text data entered by the user and sends it to the server using the HTTPS protocol. Specifically, it converts the input data into JSON format and sends it to the server as an encrypted request. The input here is the question text entered by the user, and the output is the encrypted data sent to the server.

[0131] Step 3: The server receives and parses the request

[0132] The server receives the request sent from the terminal, decodes it, and extracts the text data. It then analyzes this text data using natural language processing to extract keywords such as "will" and "how to write it." The input is the encrypted request data, and the output is the analyzed keywords.

[0133] Step 4: The server retrieves the information from the database

[0134] The server searches for relevant information from the information storage device based on the keywords obtained through the analysis. Specifically, it uses an SQL query to retrieve information on "how to write a will" from the database. The input is the analyzed keywords, and the output is the information data of the search results.

[0135] Step 5: Server generates response

[0136] The server generates a response to the user based on the search results. Using the information generation means, it formats the acquired information and creates a document containing specific instructions such as "Here's how to write a will...". The input is the information data from the search results, and the output is the generated response document.

[0137] Step 6: Send the server-generated response to the device

[0138] The server converts the generated response document into JSON format and sends it to the terminal using the HTTPS protocol. The input is the generated response document, and the output is the encrypted response data.

[0139] Step 7: User reviews response and provides additional input

[0140] The user checks the response displayed on the terminal, for example, "Here's how to write a will..." If the user has further questions, for example, "What should I pay attention to when writing a will?", they input again and repeat the same process. The input is the displayed response document, and the output is the new question text.

[0141] (Application example 1)

[0142] 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."

[0143] There is a lack of means to quickly provide appropriate information on various issues in daily operations, such as improving work efficiency at distribution centers, inventory management, optimizing picking routes, etc. Employees often lack specific knowledge about how to operate the system and how to improve efficiency, which leads to a decline in productivity.

[0144] 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.

[0145] In this invention, the server includes interface means for a user to input information, means for transmitting the information input by the user to the server, natural language processing means for the server to analyze the information input by the user, means for the server to search a database for appropriate information based on the analysis results, information generation means for the server to generate the searched information and respond to the user, response confirmation means for the user to confirm the generated response and input additional information, means for providing information on improving the efficiency of the logistics center and operating procedures, and communication means for securely transmitting and receiving data. This enables logistics center staff to quickly obtain appropriate information in real time for various problems in their daily work.

[0146] "User interface means" refers to the input device and screen through which the user enters questions or problems.

[0147] "Transmission means" refers to the communication means for transmitting the information entered by the user to the server.

[0148] "Natural language processing means" refers to means for analyzing user input information and accurately understanding the user's intent.

[0149] "Search means" refers to a means for searching for appropriate information from a database based on the analyzed information.

[0150] "Information generation means" refers to a means for generating specific information or suggestions to be provided to the user based on the searched information.

[0151] "Response Verification Means" refers to the means by which a user can verify the answers provided and ask additional questions or clarifications.

[0152] "Measures to improve the efficiency of logistics centers" refers to measures to improve work efficiency at logistics centers and provide information on operating procedures.

[0153] "Communication means" refers to the means for securely sending and receiving data between the server and the user.

[0154] A "picking route" refers to the optimal route for retrieving and collecting products within a logistics center.

[0155] "Inventory management" refers to the means of managing the quantity and condition of goods stored within a logistics center.

[0156] The system for realizing work efficiency at a logistics center according to the present invention mainly comprises a user interface means, a server, natural language processing means, a database, information generation means, response confirmation means, logistics center efficiency improvement means, and communication means.

[0157] Program processing explanation

[0158] The user interface is a smartphone application screen, through which users input questions and problems related to their daily work. The input information is securely transmitted to the server using the HTTPS protocol.

[0159] The server uses a cloud-based server (e.g., an AWS EC2 instance) and, upon receiving information sent by the user, analyzes the input information using a TensorFlow model, a natural language processing tool, to extract the user's intent and important keywords.

[0160] Based on the extracted keywords, the server searches the PostgreSQL database for relevant information, such as information on optimal picking routes and inventory management methods within a logistics center.

[0161] Next, the information generation means generates a specific and easy-to-understand response based on the search results, for example, providing information to the user in the form of "Here's how to create an efficient product pickup route..."

[0162] The response confirmation means provides an interface for the user to confirm the generated information and input further questions or additional information, thereby enabling the user to continuously obtain the required information.

[0163] Specific examples

[0164] For example, if a user types, "How can I optimize inventory management?"

[0165] 1. The user enters a question using a smartphone application and presses the send button.

[0166] 2. The server receives the request and uses a TensorFlow model to extract keywords such as "inventory management" and "optimization methods" and analyze the content.

[0167] 3. The server searches the PostgreSQL database for information on optimizing inventory management.

[0168] 4. The server generates a specific response such as, "To optimize inventory management, please refer to the following points: 1. Periodic inventory counts 2. ABC analysis 3. Order planning based on trend forecasts..."

[0169] 5. The user reviews the displayed information and re-enters any further questions or additional information.

[0170] Prompt Sentence Examples

[0171] "Please tell me how to streamline inventory management at a distribution center."

[0172] "How can I create an efficient pickup route?"

[0173] "What are some best practices for improving packaging efficiency?"

[0174] This allows logistics center staff to obtain the information they need to improve work efficiency in a timely manner, thereby increasing productivity.

[0175] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0176] Step 1:

[0177] The user enters any question or problem on the smartphone application screen. The entered data is sent securely to the server in text format using the HTTPS protocol. The input of this step is the user's text data, and the output is a request to the server.

[0178] Step 2:

[0179] The server uses a TensorFlow model, a natural language processing tool, to analyze the received data. It analyzes the input text data and extracts key keywords and user intent. For example, from the text "Please tell me how to optimize inventory management," the output from this step would be keywords such as "inventory management" and "optimization method."

[0180] Step 3:

[0181] The server searches the PostgreSQL database based on the extracted keywords. The database stores information on improving the efficiency of logistics center operations and specific operational procedures. The input for this step is the extracted keywords, and the output is a set of related information.

[0182] Step 4:

[0183] Based on the search results, the server uses information generation means to create a specific and easy-to-understand response. For example, it generates an answer in the form of "To optimize inventory management, please refer to the following points: 1. Periodic inventory taking 2. ABC analysis 3. Order planning based on trend forecasts..." The input of this step is information obtained from the database, and the output is the generated response message.

[0184] Step 5:

[0185] The server then sends the generated response message to the user's smartphone. The input is the generated response message, and the output is the message sent to the user's device.

[0186] Step 6:

[0187] The user checks the response message and enters further questions or additional information as needed, at which point the process starts again from step 1. The input of this step is the text data entered by the user again, and the output is a new request.

[0188] Through these processing steps, the information necessary to improve work efficiency at the logistics center is provided, enabling users to take appropriate action in real time.

[0189] 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.

[0190] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system consists of a user interface, a server, natural language processing, a database, information generation, response confirmation, an emotion engine, and secure communication (HTTPS protocol).

[0191] System configuration and operation

[0192] User Interface Means

[0193] User interface means consist of a screen or input device for users to input information. For example, the application screen of a smartphone or PC falls into this category. Through this screen, users can enter questions or concerns into text boxes.

[0194] server

[0195] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0196] Natural language processing tools

[0197] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content of the user's question and intent. For example, if someone enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write," and search for information showing specific steps.

[0198] Database

[0199] The database is a data repository that allows the system to search and store appropriate information. It stores various information related to the process of creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to the user's request.

[0200] Information generation means

[0201] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0202] Response confirmation means

[0203] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0204] Emotion Engine

[0205] The emotion engine is a software module that recognizes emotions from user input text. For example, if a user inputs "I'm very anxious about this procedure," the emotion engine will extract the emotion "anxiety." This allows the system to adjust the content and tone of the response according to the recognized emotion and provide more appropriate support to the user.

[0206] Secure communication method (HTTPS protocol)

[0207] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0208] Specific examples

[0209] For example, suppose a user enters the question, "Who can be a witness to a notarized will? I'm very worried."

[0210] 1. The user enters a question on the device and presses the send button.

[0211] 2. The device sends the entered question as a request to the server.

[0212] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0213] 4. At the same time, the server starts the emotion engine and recognizes the emotion "anxiety" from the input text.

[0214] 5. Based on the analysis results and the recognized emotions, the server searches the database to find information on the requirements for witnesses to notarized wills.

[0215] 6. Based on the relevant information, the server generates a specific response such as, "People who meet the following conditions can be witnesses to a notarized will. Also, because it is common for people to feel anxious about this process, we will provide detailed steps and recommended resources."

[0216] 7. The server generates a response and sends it to the terminal, where the user confirms it.

[0217] 8. The user asks further questions or clarifies based on the information displayed.

[0218] This allows users to quickly and appropriately obtain the information they need while also receiving emotional care.

[0219] The processing flow will be explained below.

[0220] Step 1:

[0221] Users launch the "End-of-Life Concierge" application on their smartphone or computer and enter their login information to authenticate.

[0222] Step 2:

[0223] The device sends login information to the server, and if authentication is successful, the user is shown a chat screen.

[0224] Step 3:

[0225] Users can enter their questions or concerns as text on the chat screen and press the send button. For example, they could type, "Who can be a witness to my notarized will? I'm very worried."

[0226] Step 4:

[0227] The terminal composes the user's input information as request data and transmits it to the server using the HTTPS protocol.

[0228] Step 5:

[0229] The server receives the request and starts the natural language processing engine and the emotion engine simultaneously.

[0230] Step 6:

[0231] The server uses natural language processing tools to analyze the user's input text and extract the main keywords: "notarized will," "witness," and "who can be a witness."

[0232] Step 7:

[0233] The server uses an emotion engine to recognize the emotion "anxiety" from the user's input text.

[0234] Step 8:

[0235] Based on the analysis results and the recognized emotions, the server searches a database to find information on the requirements for witnesses to a notarized will.

[0236] Step 9:

[0237] The server then uses the information to generate a response message that takes into account the sentiment, such as, "People who meet the following criteria can be witnesses to a notarized will. It's common for people to feel anxious about this process. We'll also provide detailed steps and recommended resources."

[0238] Step 10:

[0239] The server sends the generated response message to the terminal via the HTTPS protocol.

[0240] Step 11:

[0241] The terminal decodes the response message received from the server and displays it on the chat screen.

[0242] Step 12:

[0243] The user reviews the displayed response, enters additional questions or new information as needed, and submits again.

[0244] Step 13:

[0245] The terminal again transmits new request data to the server and repeats the series of processes from step 5 to step 12.

[0246] This allows users to efficiently obtain the necessary end-of-life information while receiving careful support that takes their feelings into consideration.

[0247] Example 2

[0248] 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."

[0249] While conventional information provision systems analyze the information entered by users and provide appropriate information, they lack consideration for the user's feelings, resulting in problems such as insufficient system response to sufficiently increase user satisfaction and peace of mind. Furthermore, there is a lack of systems that can provide appropriate analysis and information specialized for specific topics, such as how to write a will. Furthermore, in terms of security, encryption methods to prevent data leaks and unauthorized access are insufficient, potentially putting user information at risk.

[0250] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0251] In this invention, the server includes natural language processing means for analyzing user input information, emotion recognition means for analyzing the user's emotions, and means for generating and responding to the user in a way that takes the user's emotions into consideration. This makes it possible to provide appropriate and specific information while taking the user's emotions into consideration. Furthermore, analysis and information provision specialized for specific themes can be realized, thereby increasing user satisfaction and a sense of security. Furthermore, secure transmission and reception of data using encryption means can reduce security risks.

[0252] "Interface means" refers to means such as a screen or input device for users to input information.

[0253] "Natural language processing means" refers to technical means for analyzing text information entered by a user, extracting keywords, and understanding their intent.

[0254] "Emotion recognition means" refers to technical means for analyzing and extracting emotions from a user's input text.

[0255] A "response generation means" is a mechanism that creates specific information or suggestions to be provided to users based on the analysis and search results.

[0256] A "database" is a data collection that allows an information provision system to search for and store appropriate information, and it stores various information, for example, related to legal procedures and end-of-life planning.

[0257] "Encryption means" refers to technical means that encrypts information to prevent unauthorized access or information leakage in order to ensure secure transmission and reception of data.

[0258] "Secure communications" refers to communications protocols and related technologies that enable secure transmission and reception of data over the Internet.

[0259] "Emotionally sensitive responses" are a method of taking into account the user's emotional state and generating responses whose tone and content match those emotions.

[0260] "Specialized analysis and information provision means" refers to technical means that perform specialized analysis of information on a specific topic and provide more accurate and detailed information in response to user questions.

[0261] This invention relates to an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system consists of a user interface, a server, natural language processing, a database, information generation, response confirmation, emotion recognition, and secure communication (HTTPS protocol).

[0262] User Interface Means

[0263] User interface means consist of a screen or input device for users to input information. Specifically, this would be the application screen of a smartphone or PC. Through this screen, users can enter questions or concerns into text boxes.

[0264] server

[0265] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0266] Natural language processing tools

[0267] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content and intent of the user's question. For example, if the user enters "Please tell me how to write a will," the server extracts keywords such as "will" and "how to write" and searches for information showing specific steps. The natural language processing used here is a generative AI model (e.g., OpenAI GPT-3).

[0268] Database

[0269] A database is a data collection that allows the system to search and store appropriate information. For example, it stores various information related to procedures for creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to user requests. The database used is specifically a MySQL database.

[0270] Information generation means

[0271] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0272] Response confirmation means

[0273] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0274] emotion recognition means

[0275] The emotion recognizer is a software module for recognizing emotions from user input text. For example, if a user inputs "I am very anxious about this procedure," the emotion recognizer will extract the emotion "anxiety." This allows the system to adjust the content and tone of the response according to the recognized emotion and provide more appropriate support to the user.

[0276] Secure communication method (HTTPS protocol)

[0277] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0278] Specific examples

[0279] For example, if a user enters the question, "Who can be a witness to a notarized will? I'm very worried," the following is a specific example:

[0280] 1. The user enters a question on the device and presses the send button.

[0281] 2. The device sends the entered question as a request to the server.

[0282] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0283] 4. At the same time, the server activates the emotion recognition means and recognizes the emotion "anxiety" from the input text.

[0284] 5. Based on the analysis results and the recognized emotions, the server searches the database to find information on the requirements for witnesses to notarized wills.

[0285] 6. Based on the relevant information, the server generates a specific response such as, "People who meet the following conditions can be witnesses to a notarized will. Also, because it is common for people to feel anxious about this process, we will provide detailed steps and recommended resources."

[0286] 7. The server generates a response and sends it to the terminal, where the user confirms it.

[0287] 8. The user asks further questions or clarifies based on the information displayed.

[0288] This allows users to quickly and appropriately obtain the information they need while also receiving emotional care.The system also uses the HTTPS protocol for secure communication, reducing the risk of information leaks and unauthorized access.

[0289] Prompt Sentence Examples

[0290] As a concrete example, we propose a user question: "Who can be a witness to a notarized will? I'm very worried." An example of a prompt sentence to generate an appropriate response to this question is as follows:

[0291] Example prompt:

[0292] A user asks, "Who can witness a notarized will? I'm very worried." Generate an appropriate response to this question and provide emotionally sensitive support.

[0293] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0294] Step 1:

[0295] The user enters a question or concern into the application screen on their smartphone or computer and presses the send button. An example of input is the question, "Who can be a witness to a notarized will? I'm very worried." This input triggers the next processing step. The input data is question information in text format.

[0296] Step 2:

[0297] The terminal receives the question information entered by the user and sends it to the server using the HTTPS protocol. The data is encrypted here to ensure secure communication. The input data is encrypted text information, and the output data is encrypted data sent to the server.

[0298] Step 3:

[0299] The server receives the encrypted data and decrypts it to obtain text information. It then performs natural language processing on the obtained text information using a generative AI model (e.g., OpenAI GPT-3). Specifically, it extracts keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the intent of the question. The input data is the decrypted text information, and the output data is the analyzed keywords and the intent of the question.

[0300] Step 4:

[0301] The server activates the emotion recognition means and analyzes the user's emotion from the input text. For example, it extracts the emotion "anxiety" from the sentence "I'm very anxious." The input data is text information, and the output data is the analyzed emotion information.

[0302] Step 5:

[0303] The server searches a database (e.g., a MySQL database) based on the analysis results and the recognized emotions. It searches for information on "requirements for witnesses to notarized wills" and obtains the necessary data. The input data are the analyzed keywords and emotion information, and the output data is the searched database information.

[0304] Step 6:

[0305] The server uses the information generation means to generate a response based on the acquired database information. The generated response takes into consideration the user's emotions. For example, a specific response such as "A person who meets the following conditions can become a witness to a notarized will. Also, since it is common for people to feel anxious, we will also provide detailed steps and recommended resources." The input data is the information acquired from the database and emotional information, and the output data is the generated response.

[0306] Step 7:

[0307] The server encrypts the generated response and sends it to the terminal. The input data is the generated response information, and the output data is the encrypted response data.

[0308] Step 8:

[0309] The terminal receives the encrypted response data, decrypts it, and displays it to the user. The user reviews the displayed response and, if necessary, asks additional questions or confirmations. Once this process is complete, the terminal returns to the next step. The input data is the encrypted data received from the server, and the output data is the decrypted response information.

[0310] In this way, each step works together, allowing users to obtain accurate and prompt information and receive individualized, specific support in real time.

[0311] (Application example 2)

[0312] 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."

[0313] In recent years, the use of online shopping sites has increased, and users often have trouble gathering information and making decisions when considering a purchase. However, current systems have difficulty providing quick and appropriate advice to address specific questions and concerns users have. Therefore, there is a need for support systems that allow users to make purchasing decisions with peace of mind. In particular, the realization of a system that can respond appropriately to users' emotions is an urgent issue.

[0314] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0315] In this invention, the server includes interface means for the user to input information, means for transmitting the information input by the user to the server, natural language processing means for the server to analyze the information input by the user, means for the server to search a database for appropriate information based on the analysis results, means for the server to generate the searched information and respond to the user, means for the user to check the generated response and input additional information, emotion engine means for adjusting the response content based on emotion analysis, interface means for the user to input questions and concerns about products, and generative AI model means for the server to provide information related to the user's purchasing behavior in real time. This allows the user to receive appropriate support when they have concerns or worries about a purchase, allowing them to make decisions with peace of mind.

[0316] "Interface means for users to input information" refers to a screen or input device used by users to input questions or concerns.

[0317] "Means for transmitting information entered by the user to the server" refers to the mechanism by which information entered by the user from the terminal is transmitted to the server.

[0318] "Natural language processing means for the server to analyze the user's input information" refers to technology that allows the server to understand the user's input text and analyze its intent and content.

[0319] "Means for the server to search for appropriate information from a database based on the analysis results" refers to a mechanism by which the server searches for relevant information from a database based on the analysis results.

[0320] "Means for the server to generate the searched information and respond to the user" refers to the mechanism by which the server generates an appropriate response based on the information retrieved from the database and returns it to the user.

[0321] "Means for the user to review the generated response and enter additional information" means a mechanism that allows the user to view the response from the server and enter further questions or additional information.

[0322] "Emotion engine means for adjusting response content based on emotion analysis" refers to technology for analyzing emotions from user input and adjusting the content and tone of the response.

[0323] "Interface means for users to input product-related questions and concerns" refers to a screen or input device designed to make it easy for users to input product-related inquiries.

[0324] "Generative AI model means by which a server provides information related to a user's purchasing behavior in real time" refers to an artificial intelligence model that generates related information based on a user's purchasing behavior and presents it in real time.

[0325] The present invention relates to a system that quickly provides appropriate information and emotional support to users in response to questions or concerns they may have when considering a purchase on an online shopping site. The system includes a user interface, a server, a natural language processing system, a database, an information generation system, an emotion engine, and a generative AI model system.

[0326] Specifically, user interface means include smartphone applications and web interfaces through which users can input questions or concerns about products.

[0327] The server receives the information entered by the user and analyzes the text information using natural language processing means. This analysis process utilizes machine learning libraries such as TensorFlow. Based on the analysis results, the server searches for appropriate information from a database. The searched information is then generated in a form appropriate for the user by information generation means.

[0328] The emotion engine uses an emotion analysis tool such as IBM Watson's Tone Analyzer to extract emotions from user input. For example, if a user inputs, "I'm thinking about whether to purchase this product. I'm worried about the reviews," the emotion engine will recognize the emotion as "anxiety." Based on this recognition, the server will adjust the content and tone of the response and provide appropriate advice to the user.

[0329] The generative AI modeling method provides real-time information related to a user's purchasing behavior, including techniques to provide the most relevant information to the user based on their past purchase history and responses to similar questions.

[0330] For example, if a user inputs a question such as, "I'm thinking about whether to purchase this product. I'm worried about the reviews," the system generates a response using the following steps. First, the natural language processing means extracts the keywords "product," "purchase," "concern," and "review," and then the emotion engine recognizes the emotion "anxiety." Next, related product review information and advice for considering the purchase are retrieved from the database. Finally, the generative AI model means references the user's past purchase history and the behavior of other users to generate the optimal response in real time and present it to the user.

[0331] In this way, users can eliminate any concerns about purchasing products and make decisions with peace of mind.

[0332] Examples and prompts

[0333] As a concrete example, when a user enters the question, "I'm wondering whether to purchase this product. I'm worried about the reviews," the system generates the following response:

[0334] Example prompt sentence:

[0335] If a user types in a question like, "I'm not sure whether to buy this product or not. I'm worried about the reviews," how would an assistant app based on this invention respond?

[0336] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0337] Step 1:

[0338] The user enters information.

[0339] Users input questions or concerns about products through smartphone applications or web interfaces, often entering text such as "I'm thinking about whether to purchase this product. I'm worried about the reviews." The input information is sent to a server via the device.

[0340] Step 2:

[0341] The server receives the user's input and performs natural language processing.

[0342] The server receives the user's input information sent from the device. It then uses machine learning libraries such as TensorFlow to analyze the input text. Specifically, the server extracts keywords such as "product," "purchase," "problem," and "review" to understand the user's intent. The results of this analysis are passed to the next step.

[0343] Step 3:

[0344] The server performs sentiment analysis.

[0345] The server uses IBM Watson's Tone Analyzer to extract emotions from the user's input text. For example, it recognizes the emotion "anxiety" from the input text "I'm thinking about whether to buy this product. I'm worried about the reviews." The results of the emotion analysis are passed to the next step.

[0346] Step 4:

[0347] The server searches the database based on the analysis results.

[0348] The server uses the results of natural language processing and sentiment analysis to search for relevant information from a database, such as product reviews or purchasing advice, to find information that best suits the user's question. The search results are then passed on to the next step.

[0349] Step 5:

[0350] The server generates the appropriate information and responds to the user.

[0351] The server uses a generative AI model to generate an appropriate response based on the search results retrieved from the database. It also takes into account the user's past purchase history and other users' responses to similar questions. For example, it generates a response such as, "Here are some reviews from other users of this product. We also recommend that you double-check the return policy if you have any concerns."

[0352] Step 6:

[0353] The server sends the response to the user's device.

[0354] The generated response is encrypted and sent using the HTTPS protocol to the user's device, where the user can view the response, and then provide further questions or confirmations.

[0355] Step 7:

[0356] The user reviews the generated response and enters additional information.

[0357] The user can review the server's response and re-enter any questions or additional information they have. This continuous interaction allows the user to gain more information and make a more confident purchasing decision.

[0358] Examples:

[0359] For example, if a user types in the question "I'm not sure whether to buy this product or not, and I'm worried about the reviews," the steps above will be followed to generate the following specific response:

[0360] Example prompt sentence:

[0361] If a user types in a question like, "I'm not sure whether to buy this product or not. I'm worried about the reviews," how would an assistant app based on this invention respond?

[0362] 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.

[0363] 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.

[0364] 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.

[0365] [Second embodiment]

[0366] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0367] 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.

[0368] 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).

[0369] 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.

[0370] 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.

[0371] 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).

[0372] 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.

[0373] 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.

[0374] 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.

[0375] 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.

[0376] 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.

[0377] 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."

[0378] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system mainly consists of a user interface, a server, natural language processing, a database, information generation means, response confirmation means, and secure communication means (HTTPS protocol).

[0379] System configuration and operation

[0380] User Interface Means

[0381] User interface means consist of a screen or input device for users to input information. For example, the application screen of a smartphone or PC falls into this category. Through this screen, users can enter questions or concerns into text boxes.

[0382] server

[0383] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0384] Natural language processing tools

[0385] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content of the user's question and intent. For example, if someone enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write," and search for information showing specific steps.

[0386] Database

[0387] The database is a data repository that allows the system to search and store appropriate information. It stores various information related to the process of creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to the user's request.

[0388] Information generation means

[0389] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0390] Response confirmation means

[0391] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0392] Secure communication method (HTTPS protocol)

[0393] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0394] Specific examples

[0395] For example, suppose a user types the question, "Who can witness a notarized will?"

[0396] 1. The user enters a question on the device and presses the send button.

[0397] 2. The device sends the entered question as a request to the server.

[0398] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0399] 4. The server searches the database to find information regarding witness requirements for notarized wills.

[0400] 5. The server uses the relevant information to generate a specific response such as, "A person who meets the following conditions can be a witness to a notarized will..."

[0401] 6. The server generates a response and sends it to the terminal, where the user confirms it.

[0402] 7. The user asks further questions or clarifies based on the information displayed.

[0403] This allows users to easily access specialized information from the comfort of their own home and proceed with end-of-life planning that is appropriate to their own circumstances.

[0404] The processing flow will be explained below.

[0405] Step 1:

[0406] Users launch the "End-of-Life Concierge" application on their smartphone or computer and enter their login information to authenticate.

[0407] Step 2:

[0408] The device sends login information to the server, and if authentication is successful, the user is shown a chat screen.

[0409] Step 3:

[0410] Users enter their questions or concerns as text on the chat screen and press the send button.

[0411] Step 4:

[0412] The terminal composes the user's input information as request data and transmits it to the server using the HTTPS protocol.

[0413] Step 5:

[0414] The server receives the request and launches a natural language processing engine.

[0415] Step 6:

[0416] The server uses natural language processing tools to analyze the user's input text and extract key keywords and their intent.

[0417] Step 7:

[0418] Based on the analysis results, the server searches the database and collects related information.

[0419] Step 8:

[0420] The server generates a response message for the user based on the collected information.

[0421] Step 9:

[0422] The server sends the generated response message to the terminal via the HTTPS protocol.

[0423] Step 10:

[0424] The terminal decodes the response message received from the server and displays it on the chat screen.

[0425] Step 11:

[0426] The user reviews the displayed response, enters additional questions or new information as needed, and submits again.

[0427] Step 12:

[0428] The terminal again transmits new request data to the server and repeats the series of processes from step 5 to step 11.

[0429] This allows users to obtain specific and accurate information necessary for their end-of-life planning through continuous interaction.

[0430] Example 1

[0431] 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."

[0432] In modern society, it is extremely important for users to obtain specialized information quickly and accurately. Information regarding end-of-life planning is particularly complex, and while accurate information tailored to individual circumstances is required, it is difficult to find appropriate sources of information. Furthermore, from a security perspective, data protection is necessary when sending and receiving information. A system that addresses these issues is needed.

[0433] 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.

[0434] In this invention, the server includes input means for a user to input information, means for transmitting the information input by the user as data, natural language processing means for the information processing device to analyze the information input by the user, means for the information processing device to search for appropriate information from an information storage device based on the analysis results, information generation means for the information processing device to generate the searched information and respond to the user, input means for the user to check the generated response and input additional information, and secure communication means for securely transmitting and receiving information, thereby enabling users to quickly and safely obtain accurate information tailored to their individual circumstances.

[0435] A "user" is an entity that utilizes a system to input information and obtain a response.

[0436] "Input means" refers to a device or interface through which a user inputs information, and examples include text boxes on smartphones and personal computers.

[0437] "Means for transmitting data" refers to a mechanism for transmitting input information to a server, and includes secure communication methods such as the HTTPS protocol.

[0438] An "information processing device" is a central processing unit that performs multiple processes and analyzes information received from a user.

[0439] "Natural language processing means" refers to technology for analyzing text information entered by a user and understanding its content and intent, and includes generative models.

[0440] "Information storage device" refers to a database or data repository used to retrieve relevant information based on the results of an analysis.

[0441] "Information generation means" refers to a mechanism for generating specific responses or information based on search results.

[0442] "Secure communication means" refers to technology for securely sending and receiving information, including the HTTPS protocol, which uses encrypted communications.

[0443] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. The system configuration is as follows.

[0444] User Interface Means

[0445] User interface means consist of a screen or input device for users to input information. Specifically, this corresponds to the application screen of a smartphone or PC. Through this screen, users can enter their questions or concerns into a text box and press the send button.

[0446] Terminal

[0447] The device is the means by which the information entered by the user is sent to the server, and uses the HTTPS protocol to encrypt and transmit data securely. For example, a smartphone or PC is one such device.

[0448] server

[0449] The server is a central processing unit that receives, analyzes, and processes information sent by users. The server is equipped with the following means:

[0450] Natural language processing tools

[0451] The server uses natural language processing (e.g., a generative AI model) to analyze the text information entered by the user. This allows it to accurately understand the content and intent of the user's question. For example, if the user enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write" and search for information showing specific steps.

[0452] Information Storage Device

[0453] The information storage device is a data repository that allows the system to search for and store appropriate information. For example, it stores various information related to procedures for creating wills, legal procedures, and end-of-life planning. The server uses this information to provide information in response to user requests.

[0454] Information generation means

[0455] The information generation means is a mechanism for creating specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0456] Secure Communication Methods

[0457] The server uses the HTTPS protocol to ensure secure transmission of information, which encrypts communication between the user and the server and prevents information leakage and unauthorized access.

[0458] Specific examples

[0459] For example, suppose a user types the question, "Who can witness a notarized will?"

[0460] The user enters a question into the terminal and presses the send button.

[0461] The terminal sends the entered question as a request to the server.

[0462] The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0463] The server searches the information storage device to find information regarding the requirements for witnesses to notarized wills.

[0464] Based on the relevant information, the server generates a specific response such as "A person who meets the following conditions can be a witness to a notarized will..."

[0465] The server generates a response and sends it to the terminal, where the user confirms it.

[0466] The user can then ask further questions or make further confirmations based on the displayed information, for example, by entering a follow-up question such as, "What are the conditions?"

[0467] An example of a prompt sentence could be a text input such as "Who can be a witness to a notarized will?"

[0468] This allows users to easily access specialized information from the comfort of their own home and proceed with end-of-life planning that is appropriate to their own circumstances.

[0469] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0470] Step 1: User Enters Information

[0471] The user enters their question or concern into the text box on the application screen of their smartphone or computer and presses the send button. For example, they might type, "Please tell me how to write a will." At this time, the information entered by the user is generated as input data.

[0472] Step 2: The device sends a request to the server

[0473] The terminal receives the text data entered by the user and sends it to the server using the HTTPS protocol. Specifically, it converts the input data into JSON format and sends it to the server as an encrypted request. The input here is the question text entered by the user, and the output is the encrypted data sent to the server.

[0474] Step 3: The server receives and parses the request

[0475] The server receives the request sent from the terminal, decodes it, and extracts the text data. It then analyzes this text data using natural language processing to extract keywords such as "will" and "how to write it." The input is the encrypted request data, and the output is the analyzed keywords.

[0476] Step 4: The server retrieves the information from the database

[0477] The server searches for relevant information from the information storage device based on the keywords obtained through the analysis. Specifically, it uses an SQL query to retrieve information on "how to write a will" from the database. The input is the analyzed keywords, and the output is the information data of the search results.

[0478] Step 5: Server generates response

[0479] The server generates a response to the user based on the search results. Using the information generation means, it formats the acquired information and creates a document containing specific instructions such as "Here's how to write a will...". The input is the information data from the search results, and the output is the generated response document.

[0480] Step 6: Send the server-generated response to the device

[0481] The server converts the generated response document into JSON format and sends it to the terminal using the HTTPS protocol. The input is the generated response document, and the output is the encrypted response data.

[0482] Step 7: User reviews response and provides additional input

[0483] The user checks the response displayed on the terminal, for example, "Here's how to write a will..." If the user has further questions, for example, "What should I pay attention to when writing a will?", they input again and repeat the same process. The input is the displayed response document, and the output is the new question text.

[0484] (Application example 1)

[0485] 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."

[0486] There is a lack of means to quickly provide appropriate information on various issues in daily operations, such as improving work efficiency at distribution centers, inventory management, optimizing picking routes, etc. Employees often lack specific knowledge about how to operate the system and how to improve efficiency, which leads to a decline in productivity.

[0487] 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.

[0488] In this invention, the server includes interface means for a user to input information, means for transmitting the information input by the user to the server, natural language processing means for the server to analyze the information input by the user, means for the server to search a database for appropriate information based on the analysis results, information generation means for the server to generate the searched information and respond to the user, response confirmation means for the user to confirm the generated response and input additional information, means for providing information on improving the efficiency of the logistics center and operating procedures, and communication means for securely transmitting and receiving data. This enables logistics center staff to quickly obtain appropriate information in real time for various problems in their daily work.

[0489] "User interface means" refers to the input device and screen through which the user enters questions or problems.

[0490] "Transmission means" refers to the communication means for transmitting the information entered by the user to the server.

[0491] "Natural language processing means" refers to means for analyzing user input information and accurately understanding the user's intent.

[0492] "Search means" refers to a means for searching for appropriate information from a database based on the analyzed information.

[0493] "Information generation means" refers to a means for generating specific information or suggestions to be provided to the user based on the searched information.

[0494] "Response Verification Means" refers to the means by which a user can verify the answers provided and ask additional questions or clarifications.

[0495] "Measures to improve the efficiency of logistics centers" refers to measures to improve work efficiency at logistics centers and provide information on operating procedures.

[0496] "Communication means" refers to the means for securely sending and receiving data between the server and the user.

[0497] A "picking route" refers to the optimal route for retrieving and collecting products within a logistics center.

[0498] "Inventory management" refers to the means of managing the quantity and condition of goods stored within a logistics center.

[0499] The system for realizing work efficiency at a logistics center according to the present invention mainly comprises a user interface means, a server, natural language processing means, a database, information generation means, response confirmation means, logistics center efficiency improvement means, and communication means.

[0500] Program processing explanation

[0501] The user interface is a smartphone application screen, through which users input questions and problems related to their daily work. The input information is securely transmitted to the server using the HTTPS protocol.

[0502] The server uses a cloud-based server (e.g., an AWS EC2 instance) and, upon receiving information sent by the user, analyzes the input information using a TensorFlow model, a natural language processing tool, to extract the user's intent and important keywords.

[0503] Based on the extracted keywords, the server searches the PostgreSQL database for relevant information, such as information on optimal picking routes and inventory management methods within a logistics center.

[0504] Next, the information generation means generates a specific and easy-to-understand response based on the search results, for example, providing information to the user in the form of "Here's how to create an efficient product pickup route..."

[0505] The response confirmation means provides an interface for the user to confirm the generated information and input further questions or additional information, thereby enabling the user to continuously obtain the required information.

[0506] Specific examples

[0507] For example, if a user types, "How can I optimize inventory management?"

[0508] 1. The user enters a question using a smartphone application and presses the send button.

[0509] 2. The server receives the request and uses a TensorFlow model to extract keywords such as "inventory management" and "optimization methods" and analyze the content.

[0510] 3. The server searches the PostgreSQL database for information on optimizing inventory management.

[0511] 4. The server generates a specific response such as, "To optimize inventory management, please refer to the following points: 1. Periodic inventory counts 2. ABC analysis 3. Order planning based on trend forecasts..."

[0512] 5. The user reviews the displayed information and re-enters any further questions or additional information.

[0513] Prompt Sentence Examples

[0514] "Please tell me how to streamline inventory management at a distribution center."

[0515] "How can I create an efficient pickup route?"

[0516] "What are some best practices for improving packaging efficiency?"

[0517] This allows logistics center staff to obtain the information they need to improve work efficiency in a timely manner, thereby increasing productivity.

[0518] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0519] Step 1:

[0520] The user enters any question or problem on the smartphone application screen. The entered data is sent securely to the server in text format using the HTTPS protocol. The input of this step is the user's text data, and the output is a request to the server.

[0521] Step 2:

[0522] The server uses a TensorFlow model, a natural language processing tool, to analyze the received data. It analyzes the input text data and extracts key keywords and user intent. For example, from the text "Please tell me how to optimize inventory management," the output from this step would be keywords such as "inventory management" and "optimization method."

[0523] Step 3:

[0524] The server searches the PostgreSQL database based on the extracted keywords. The database stores information on improving the efficiency of logistics center operations and specific operational procedures. The input for this step is the extracted keywords, and the output is a set of related information.

[0525] Step 4:

[0526] Based on the search results, the server uses information generation means to create a specific and easy-to-understand response. For example, it generates an answer in the form of "To optimize inventory management, please refer to the following points: 1. Periodic inventory taking 2. ABC analysis 3. Order planning based on trend forecasts..." The input of this step is information obtained from the database, and the output is the generated response message.

[0527] Step 5:

[0528] The server then sends the generated response message to the user's smartphone. The input is the generated response message, and the output is the message sent to the user's device.

[0529] Step 6:

[0530] The user checks the response message and enters further questions or additional information as needed, at which point the process starts again from step 1. The input of this step is the text data entered by the user again, and the output is a new request.

[0531] Through these processing steps, the information necessary to improve work efficiency at the logistics center is provided, enabling users to take appropriate action in real time.

[0532] 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.

[0533] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system consists of a user interface, a server, natural language processing, a database, information generation, response confirmation, an emotion engine, and secure communication (HTTPS protocol).

[0534] System configuration and operation

[0535] User Interface Means

[0536] User interface means consist of a screen or input device for users to input information. For example, the application screen of a smartphone or PC falls into this category. Through this screen, users can enter questions or concerns into text boxes.

[0537] server

[0538] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0539] Natural language processing tools

[0540] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content of the user's question and intent. For example, if someone enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write," and search for information showing specific steps.

[0541] Database

[0542] The database is a data repository that allows the system to search and store appropriate information. It stores various information related to the process of creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to the user's request.

[0543] Information generation means

[0544] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0545] Response confirmation means

[0546] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0547] Emotion Engine

[0548] The emotion engine is a software module that recognizes emotions from user input text. For example, if a user inputs "I'm very anxious about this procedure," the emotion engine will extract the emotion "anxiety." This allows the system to adjust the content and tone of the response according to the recognized emotion and provide more appropriate support to the user.

[0549] Secure communication method (HTTPS protocol)

[0550] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0551] Specific examples

[0552] For example, suppose a user enters the question, "Who can be a witness to a notarized will? I'm very worried."

[0553] 1. The user enters a question on the device and presses the send button.

[0554] 2. The device sends the entered question as a request to the server.

[0555] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0556] 4. At the same time, the server starts the emotion engine and recognizes the emotion "anxiety" from the input text.

[0557] 5. Based on the analysis results and the recognized emotions, the server searches the database to find information on the requirements for witnesses to notarized wills.

[0558] 6. Based on the relevant information, the server generates a specific response such as, "People who meet the following conditions can be witnesses to a notarized will. Also, because it is common for people to feel anxious about this process, we will provide detailed steps and recommended resources."

[0559] 7. The server generates a response and sends it to the terminal, where the user confirms it.

[0560] 8. The user asks further questions or clarifies based on the information displayed.

[0561] This allows users to quickly and appropriately obtain the information they need while also receiving emotional care.

[0562] The processing flow will be explained below.

[0563] Step 1:

[0564] Users launch the "End-of-Life Concierge" application on their smartphone or computer and enter their login information to authenticate.

[0565] Step 2:

[0566] The device sends login information to the server, and if authentication is successful, the user is shown a chat screen.

[0567] Step 3:

[0568] Users can enter their questions or concerns as text on the chat screen and press the send button. For example, they could type, "Who can be a witness to my notarized will? I'm very worried."

[0569] Step 4:

[0570] The terminal composes the user's input information as request data and transmits it to the server using the HTTPS protocol.

[0571] Step 5:

[0572] The server receives the request and starts the natural language processing engine and the emotion engine simultaneously.

[0573] Step 6:

[0574] The server uses natural language processing tools to analyze the user's input text and extract the main keywords: "notarized will," "witness," and "who can be a witness."

[0575] Step 7:

[0576] The server uses an emotion engine to recognize the emotion "anxiety" from the user's input text.

[0577] Step 8:

[0578] Based on the analysis results and the recognized emotions, the server searches a database to find information on the requirements for witnesses to a notarized will.

[0579] Step 9:

[0580] The server then uses the information to generate a response message that takes into account the sentiment, such as, "People who meet the following criteria can be witnesses to a notarized will. It's common for people to feel anxious about this process. We'll also provide detailed steps and recommended resources."

[0581] Step 10:

[0582] The server sends the generated response message to the terminal via the HTTPS protocol.

[0583] Step 11:

[0584] The terminal decodes the response message received from the server and displays it on the chat screen.

[0585] Step 12:

[0586] The user reviews the displayed response, enters additional questions or new information as needed, and submits again.

[0587] Step 13:

[0588] The terminal again transmits new request data to the server and repeats the series of processes from step 5 to step 12.

[0589] This allows users to efficiently obtain the necessary end-of-life information while receiving careful support that takes their feelings into consideration.

[0590] Example 2

[0591] 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."

[0592] While conventional information provision systems analyze the information entered by users and provide appropriate information, they lack consideration for the user's feelings, resulting in problems such as insufficient system response to sufficiently increase user satisfaction and peace of mind. Furthermore, there is a lack of systems that can provide appropriate analysis and information specialized for specific topics, such as how to write a will. Furthermore, in terms of security, encryption methods to prevent data leaks and unauthorized access are insufficient, potentially putting user information at risk.

[0593] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0594] In this invention, the server includes natural language processing means for analyzing user input information, emotion recognition means for analyzing the user's emotions, and means for generating and responding to the user in a way that takes the user's emotions into consideration. This makes it possible to provide appropriate and specific information while taking the user's emotions into consideration. Furthermore, analysis and information provision specialized for specific themes can be realized, thereby increasing user satisfaction and a sense of security. Furthermore, secure transmission and reception of data using encryption means can reduce security risks.

[0595] "Interface means" refers to means such as a screen or input device for users to input information.

[0596] "Natural language processing means" refers to technical means for analyzing text information entered by a user, extracting keywords, and understanding their intent.

[0597] "Emotion recognition means" refers to technical means for analyzing and extracting emotions from a user's input text.

[0598] A "response generation means" is a mechanism that creates specific information or suggestions to be provided to users based on the analysis and search results.

[0599] A "database" is a data collection that allows an information provision system to search for and store appropriate information, and it stores various information, for example, related to legal procedures and end-of-life planning.

[0600] "Encryption means" refers to technical means that encrypts information to prevent unauthorized access or information leakage in order to ensure secure transmission and reception of data.

[0601] "Secure communications" refers to communications protocols and related technologies that enable secure transmission and reception of data over the Internet.

[0602] "Emotionally sensitive responses" are a method of taking into account the user's emotional state and generating responses whose tone and content match those emotions.

[0603] "Specialized analysis and information provision means" refers to technical means that perform specialized analysis of information on a specific topic and provide more accurate and detailed information in response to user questions.

[0604] This invention relates to an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system consists of a user interface, a server, natural language processing, a database, information generation, response confirmation, emotion recognition, and secure communication (HTTPS protocol).

[0605] User Interface Means

[0606] User interface means consist of a screen or input device for users to input information. Specifically, this would be the application screen of a smartphone or PC. Through this screen, users can enter questions or concerns into text boxes.

[0607] server

[0608] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0609] Natural language processing tools

[0610] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content and intent of the user's question. For example, if the user enters "Please tell me how to write a will," the server extracts keywords such as "will" and "how to write" and searches for information showing specific steps. The natural language processing used here is a generative AI model (e.g., OpenAI GPT-3).

[0611] Database

[0612] A database is a data collection that allows the system to search and store appropriate information. For example, it stores various information related to procedures for creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to user requests. The database used is specifically a MySQL database.

[0613] Information generation means

[0614] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0615] Response confirmation means

[0616] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0617] emotion recognition means

[0618] The emotion recognizer is a software module for recognizing emotions from user input text. For example, if a user inputs "I am very anxious about this procedure," the emotion recognizer will extract the emotion "anxiety." This allows the system to adjust the content and tone of the response according to the recognized emotion and provide more appropriate support to the user.

[0619] Secure communication method (HTTPS protocol)

[0620] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0621] Specific examples

[0622] For example, if a user enters the question, "Who can be a witness to a notarized will? I'm very worried," the following is a specific example:

[0623] 1. The user enters a question on the device and presses the send button.

[0624] 2. The device sends the entered question as a request to the server.

[0625] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0626] 4. At the same time, the server activates the emotion recognition means and recognizes the emotion "anxiety" from the input text.

[0627] 5. Based on the analysis results and the recognized emotions, the server searches the database to find information on the requirements for witnesses to notarized wills.

[0628] 6. Based on the relevant information, the server generates a specific response such as, "People who meet the following conditions can be witnesses to a notarized will. Also, because it is common for people to feel anxious about this process, we will provide detailed steps and recommended resources."

[0629] 7. The server generates a response and sends it to the terminal, where the user confirms it.

[0630] 8. The user asks further questions or clarifies based on the information displayed.

[0631] This allows users to quickly and appropriately obtain the information they need while also receiving emotional care.The system also uses the HTTPS protocol for secure communication, reducing the risk of information leaks and unauthorized access.

[0632] Prompt Sentence Examples

[0633] As a concrete example, we propose a user question: "Who can be a witness to a notarized will? I'm very worried." An example of a prompt sentence to generate an appropriate response to this question is as follows:

[0634] Example prompt:

[0635] A user asks, "Who can witness a notarized will? I'm very worried." Generate an appropriate response to this question and provide emotionally sensitive support.

[0636] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0637] Step 1:

[0638] The user enters a question or concern into the application screen on their smartphone or computer and presses the send button. An example of input is the question, "Who can be a witness to a notarized will? I'm very worried." This input triggers the next processing step. The input data is question information in text format.

[0639] Step 2:

[0640] The terminal receives the question information entered by the user and sends it to the server using the HTTPS protocol. The data is encrypted here to ensure secure communication. The input data is encrypted text information, and the output data is encrypted data sent to the server.

[0641] Step 3:

[0642] The server receives the encrypted data and decrypts it to obtain text information. It then performs natural language processing on the obtained text information using a generative AI model (e.g., OpenAI GPT-3). Specifically, it extracts keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the intent of the question. The input data is the decrypted text information, and the output data is the analyzed keywords and the intent of the question.

[0643] Step 4:

[0644] The server activates the emotion recognition means and analyzes the user's emotion from the input text. For example, it extracts the emotion "anxiety" from the sentence "I'm very anxious." The input data is text information, and the output data is the analyzed emotion information.

[0645] Step 5:

[0646] The server searches a database (e.g., a MySQL database) based on the analysis results and the recognized emotions. It searches for information on "requirements for witnesses to notarized wills" and obtains the necessary data. The input data are the analyzed keywords and emotion information, and the output data is the searched database information.

[0647] Step 6:

[0648] The server uses the information generation means to generate a response based on the acquired database information. The generated response takes into consideration the user's emotions. For example, a specific response such as "A person who meets the following conditions can become a witness to a notarized will. Also, since it is common for people to feel anxious, we will also provide detailed steps and recommended resources." The input data is the information acquired from the database and emotional information, and the output data is the generated response.

[0649] Step 7:

[0650] The server encrypts the generated response and sends it to the terminal. The input data is the generated response information, and the output data is the encrypted response data.

[0651] Step 8:

[0652] The terminal receives the encrypted response data, decrypts it, and displays it to the user. The user reviews the displayed response and, if necessary, asks additional questions or confirmations. Once this process is complete, the terminal returns to the next step. The input data is the encrypted data received from the server, and the output data is the decrypted response information.

[0653] In this way, each step works together, allowing users to obtain accurate and prompt information and receive individualized, specific support in real time.

[0654] (Application example 2)

[0655] 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."

[0656] In recent years, the use of online shopping sites has increased, and users often have trouble gathering information and making decisions when considering a purchase. However, current systems have difficulty providing quick and appropriate advice to address specific questions and concerns users have. Therefore, there is a need for support systems that allow users to make purchasing decisions with peace of mind. In particular, the realization of a system that can respond appropriately to users' emotions is an urgent issue.

[0657] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0658] In this invention, the server includes interface means for the user to input information, means for transmitting the information input by the user to the server, natural language processing means for the server to analyze the information input by the user, means for the server to search a database for appropriate information based on the analysis results, means for the server to generate the searched information and respond to the user, means for the user to check the generated response and input additional information, emotion engine means for adjusting the response content based on emotion analysis, interface means for the user to input questions and concerns about products, and generative AI model means for the server to provide information related to the user's purchasing behavior in real time. This allows the user to receive appropriate support when they have concerns or worries about a purchase, allowing them to make decisions with peace of mind.

[0659] "Interface means for users to input information" refers to a screen or input device used by users to input questions or concerns.

[0660] "Means for transmitting information entered by the user to the server" refers to the mechanism by which information entered by the user from the terminal is transmitted to the server.

[0661] "Natural language processing means for the server to analyze the user's input information" refers to technology that allows the server to understand the user's input text and analyze its intent and content.

[0662] "Means for the server to search for appropriate information from a database based on the analysis results" refers to a mechanism by which the server searches for relevant information from a database based on the analysis results.

[0663] "Means for the server to generate the searched information and respond to the user" refers to the mechanism by which the server generates an appropriate response based on the information retrieved from the database and returns it to the user.

[0664] "Means for the user to review the generated response and enter additional information" means a mechanism that allows the user to view the response from the server and enter further questions or additional information.

[0665] "Emotion engine means for adjusting response content based on emotion analysis" refers to technology for analyzing emotions from user input and adjusting the content and tone of the response.

[0666] "Interface means for users to input product-related questions and concerns" refers to a screen or input device designed to make it easy for users to input product-related inquiries.

[0667] "Generative AI model means by which a server provides information related to a user's purchasing behavior in real time" refers to an artificial intelligence model that generates related information based on a user's purchasing behavior and presents it in real time.

[0668] The present invention relates to a system that quickly provides appropriate information and emotional support to users in response to questions or concerns they may have when considering a purchase on an online shopping site. The system includes a user interface, a server, a natural language processing system, a database, an information generation system, an emotion engine, and a generative AI model system.

[0669] Specifically, user interface means include smartphone applications and web interfaces through which users can input questions or concerns about products.

[0670] The server receives the information entered by the user and analyzes the text information using natural language processing means. This analysis process utilizes machine learning libraries such as TensorFlow. Based on the analysis results, the server searches for appropriate information from a database. The searched information is then generated in a form appropriate for the user by information generation means.

[0671] The emotion engine uses an emotion analysis tool such as IBM Watson's Tone Analyzer to extract emotions from user input. For example, if a user inputs, "I'm thinking about whether to purchase this product. I'm worried about the reviews," the emotion engine will recognize the emotion as "anxiety." Based on this recognition, the server will adjust the content and tone of the response and provide appropriate advice to the user.

[0672] The generative AI modeling method provides real-time information related to a user's purchasing behavior, including techniques to provide the most relevant information to the user based on their past purchase history and responses to similar questions.

[0673] For example, if a user inputs a question such as, "I'm thinking about whether to purchase this product. I'm worried about the reviews," the system generates a response using the following steps. First, the natural language processing means extracts the keywords "product," "purchase," "concern," and "review," and then the emotion engine recognizes the emotion "anxiety." Next, related product review information and advice for considering the purchase are retrieved from the database. Finally, the generative AI model means references the user's past purchase history and the behavior of other users to generate the optimal response in real time and present it to the user.

[0674] In this way, users can eliminate any concerns about purchasing products and make decisions with peace of mind.

[0675] Examples and prompts

[0676] As a concrete example, when a user enters the question, "I'm wondering whether to purchase this product. I'm worried about the reviews," the system generates the following response:

[0677] Example prompt sentence:

[0678] If a user types in a question like, "I'm not sure whether to buy this product or not. I'm worried about the reviews," how would an assistant app based on this invention respond?

[0679] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0680] Step 1:

[0681] The user enters information.

[0682] Users input questions or concerns about products through smartphone applications or web interfaces, often entering text such as "I'm thinking about whether to purchase this product. I'm worried about the reviews." The input information is sent to a server via the device.

[0683] Step 2:

[0684] The server receives the user's input and performs natural language processing.

[0685] The server receives the user's input information sent from the device. It then uses machine learning libraries such as TensorFlow to analyze the input text. Specifically, the server extracts keywords such as "product," "purchase," "problem," and "review" to understand the user's intent. The results of this analysis are passed to the next step.

[0686] Step 3:

[0687] The server performs sentiment analysis.

[0688] The server uses IBM Watson's Tone Analyzer to extract emotions from the user's input text. For example, it recognizes the emotion "anxiety" from the input text "I'm thinking about whether to buy this product. I'm worried about the reviews." The results of the emotion analysis are passed to the next step.

[0689] Step 4:

[0690] The server searches the database based on the analysis results.

[0691] The server uses the results of natural language processing and sentiment analysis to search for relevant information from a database, such as product reviews or purchasing advice, to find information that best suits the user's question. The search results are then passed on to the next step.

[0692] Step 5:

[0693] The server generates the appropriate information and responds to the user.

[0694] The server uses a generative AI model to generate an appropriate response based on the search results retrieved from the database. It also takes into account the user's past purchase history and other users' responses to similar questions. For example, it generates a response such as, "Here are some reviews from other users of this product. We also recommend that you double-check the return policy if you have any concerns."

[0695] Step 6:

[0696] The server sends the response to the user's device.

[0697] The generated response is encrypted and sent using the HTTPS protocol to the user's device, where the user can view the response, and then provide further questions or confirmations.

[0698] Step 7:

[0699] The user reviews the generated response and enters additional information.

[0700] The user can review the server's response and re-enter any questions or additional information they have. This continuous interaction allows the user to gain more information and make a more confident purchasing decision.

[0701] Examples:

[0702] For example, if a user types in the question "I'm not sure whether to buy this product or not, and I'm worried about the reviews," the steps above will be followed to generate the following specific response:

[0703] Example prompt sentence:

[0704] If a user types in a question like, "I'm not sure whether to buy this product or not. I'm worried about the reviews," how would an assistant app based on this invention respond?

[0705] 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.

[0706] 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.

[0707] 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.

[0708] [Third embodiment]

[0709] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0710] 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.

[0711] 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).

[0712] 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.

[0713] 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.

[0714] 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).

[0715] 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.

[0716] 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.

[0717] 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.

[0718] 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.

[0719] 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.

[0720] 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."

[0721] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system mainly consists of a user interface, a server, natural language processing, a database, information generation means, response confirmation means, and secure communication means (HTTPS protocol).

[0722] System configuration and operation

[0723] User Interface Means

[0724] User interface means consist of a screen or input device for users to input information. For example, the application screen of a smartphone or PC falls into this category. Through this screen, users can enter questions or concerns into text boxes.

[0725] server

[0726] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0727] Natural language processing tools

[0728] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content of the user's question and intent. For example, if someone enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write," and search for information showing specific steps.

[0729] Database

[0730] The database is a data repository that allows the system to search and store appropriate information. It stores various information related to the process of creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to the user's request.

[0731] Information generation means

[0732] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0733] Response confirmation means

[0734] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0735] Secure communication method (HTTPS protocol)

[0736] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0737] Specific examples

[0738] For example, suppose a user types the question, "Who can witness a notarized will?"

[0739] 1. The user enters a question on the device and presses the send button.

[0740] 2. The device sends the entered question as a request to the server.

[0741] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0742] 4. The server searches the database to find information regarding witness requirements for notarized wills.

[0743] 5. The server uses the relevant information to generate a specific response such as, "A person who meets the following conditions can be a witness to a notarized will..."

[0744] 6. The server generates a response and sends it to the terminal, where the user confirms it.

[0745] 7. The user asks further questions or clarifies based on the information displayed.

[0746] This allows users to easily access specialized information from the comfort of their own home and proceed with end-of-life planning that is appropriate to their own circumstances.

[0747] The processing flow will be explained below.

[0748] Step 1:

[0749] Users launch the "End-of-Life Concierge" application on their smartphone or computer and enter their login information to authenticate.

[0750] Step 2:

[0751] The device sends login information to the server, and if authentication is successful, the user is shown a chat screen.

[0752] Step 3:

[0753] Users enter their questions or concerns as text on the chat screen and press the send button.

[0754] Step 4:

[0755] The terminal composes the user's input information as request data and transmits it to the server using the HTTPS protocol.

[0756] Step 5:

[0757] The server receives the request and launches a natural language processing engine.

[0758] Step 6:

[0759] The server uses natural language processing tools to analyze the user's input text and extract key keywords and their intent.

[0760] Step 7:

[0761] Based on the analysis results, the server searches the database and collects related information.

[0762] Step 8:

[0763] The server generates a response message for the user based on the collected information.

[0764] Step 9:

[0765] The server sends the generated response message to the terminal via the HTTPS protocol.

[0766] Step 10:

[0767] The terminal decodes the response message received from the server and displays it on the chat screen.

[0768] Step 11:

[0769] The user reviews the displayed response, enters additional questions or new information as needed, and submits again.

[0770] Step 12:

[0771] The terminal again transmits new request data to the server and repeats the series of processes from step 5 to step 11.

[0772] This allows users to obtain specific and accurate information necessary for their end-of-life planning through continuous interaction.

[0773] Example 1

[0774] 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."

[0775] In modern society, it is extremely important for users to obtain specialized information quickly and accurately. Information regarding end-of-life planning is particularly complex, and while accurate information tailored to individual circumstances is required, it is difficult to find appropriate sources of information. Furthermore, from a security perspective, data protection is necessary when sending and receiving information. A system that addresses these issues is needed.

[0776] 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.

[0777] In this invention, the server includes input means for a user to input information, means for transmitting the information input by the user as data, natural language processing means for the information processing device to analyze the information input by the user, means for the information processing device to search for appropriate information from an information storage device based on the analysis results, information generation means for the information processing device to generate the searched information and respond to the user, input means for the user to check the generated response and input additional information, and secure communication means for securely transmitting and receiving information, thereby enabling users to quickly and safely obtain accurate information tailored to their individual circumstances.

[0778] A "user" is an entity that utilizes a system to input information and obtain a response.

[0779] "Input means" refers to a device or interface through which a user inputs information, and examples include text boxes on smartphones and personal computers.

[0780] "Means for transmitting data" refers to a mechanism for transmitting input information to a server, and includes secure communication methods such as the HTTPS protocol.

[0781] An "information processing device" is a central processing unit that performs multiple processes and analyzes information received from a user.

[0782] "Natural language processing means" refers to technology for analyzing text information entered by a user and understanding its content and intent, and includes generative models.

[0783] "Information storage device" refers to a database or data repository used to retrieve relevant information based on the results of an analysis.

[0784] "Information generation means" refers to a mechanism for generating specific responses or information based on search results.

[0785] "Secure communication means" refers to technology for securely sending and receiving information, including the HTTPS protocol, which uses encrypted communications.

[0786] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. The system configuration is as follows.

[0787] User Interface Means

[0788] User interface means consist of a screen or input device for users to input information. Specifically, this corresponds to the application screen of a smartphone or PC. Through this screen, users can enter their questions or concerns into a text box and press the send button.

[0789] Terminal

[0790] The device is the means by which the information entered by the user is sent to the server, and uses the HTTPS protocol to encrypt and transmit data securely. For example, a smartphone or PC is one such device.

[0791] server

[0792] The server is a central processing unit that receives, analyzes, and processes information sent by users. The server is equipped with the following means:

[0793] Natural language processing tools

[0794] The server uses natural language processing (e.g., a generative AI model) to analyze the text information entered by the user. This allows it to accurately understand the content and intent of the user's question. For example, if the user enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write" and search for information showing specific steps.

[0795] Information Storage Device

[0796] The information storage device is a data repository that allows the system to search for and store appropriate information. For example, it stores various information related to procedures for creating wills, legal procedures, and end-of-life planning. The server uses this information to provide information in response to user requests.

[0797] Information generation means

[0798] The information generation means is a mechanism for creating specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0799] Secure Communication Methods

[0800] The server uses the HTTPS protocol to ensure secure transmission of information, which encrypts communication between the user and the server and prevents information leakage and unauthorized access.

[0801] Specific examples

[0802] For example, suppose a user types the question, "Who can witness a notarized will?"

[0803] The user enters a question into the terminal and presses the send button.

[0804] The terminal sends the entered question as a request to the server.

[0805] The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0806] The server searches the information storage device to find information regarding the requirements for witnesses to notarized wills.

[0807] Based on the relevant information, the server generates a specific response such as "A person who meets the following conditions can be a witness to a notarized will..."

[0808] The server generates a response and sends it to the terminal, where the user confirms it.

[0809] The user can then ask further questions or make further confirmations based on the displayed information, for example, by entering a follow-up question such as, "What are the conditions?"

[0810] An example of a prompt sentence could be a text input such as "Who can be a witness to a notarized will?"

[0811] This allows users to easily access specialized information from the comfort of their own home and proceed with end-of-life planning that is appropriate to their own circumstances.

[0812] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0813] Step 1: User Enters Information

[0814] The user enters their question or concern into the text box on the application screen of their smartphone or computer and presses the send button. For example, they might type, "Please tell me how to write a will." At this time, the information entered by the user is generated as input data.

[0815] Step 2: The device sends a request to the server

[0816] The terminal receives the text data entered by the user and sends it to the server using the HTTPS protocol. Specifically, it converts the input data into JSON format and sends it to the server as an encrypted request. The input here is the question text entered by the user, and the output is the encrypted data sent to the server.

[0817] Step 3: The server receives and parses the request

[0818] The server receives the request sent from the terminal, decodes it, and extracts the text data. It then analyzes this text data using natural language processing to extract keywords such as "will" and "how to write it." The input is the encrypted request data, and the output is the analyzed keywords.

[0819] Step 4: The server retrieves the information from the database

[0820] The server searches for relevant information from the information storage device based on the keywords obtained through the analysis. Specifically, it uses an SQL query to retrieve information on "how to write a will" from the database. The input is the analyzed keywords, and the output is the information data of the search results.

[0821] Step 5: Server generates response

[0822] The server generates a response to the user based on the search results. Using the information generation means, it formats the acquired information and creates a document containing specific instructions such as "Here's how to write a will...". The input is the information data from the search results, and the output is the generated response document.

[0823] Step 6: Send the server-generated response to the device

[0824] The server converts the generated response document into JSON format and sends it to the terminal using the HTTPS protocol. The input is the generated response document, and the output is the encrypted response data.

[0825] Step 7: User reviews response and provides additional input

[0826] The user checks the response displayed on the terminal, for example, "Here's how to write a will..." If the user has further questions, for example, "What should I pay attention to when writing a will?", they input again and repeat the same process. The input is the displayed response document, and the output is the new question text.

[0827] (Application example 1)

[0828] 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."

[0829] There is a lack of means to quickly provide appropriate information on various issues in daily operations, such as improving work efficiency at distribution centers, inventory management, optimizing picking routes, etc. Employees often lack specific knowledge about how to operate the system and how to improve efficiency, which leads to a decline in productivity.

[0830] 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.

[0831] In this invention, the server includes interface means for a user to input information, means for transmitting the information input by the user to the server, natural language processing means for the server to analyze the information input by the user, means for the server to search a database for appropriate information based on the analysis results, information generation means for the server to generate the searched information and respond to the user, response confirmation means for the user to confirm the generated response and input additional information, means for providing information on improving the efficiency of the logistics center and operating procedures, and communication means for securely transmitting and receiving data. This enables logistics center staff to quickly obtain appropriate information in real time for various problems in their daily work.

[0832] "User interface means" refers to the input device and screen through which the user enters questions or problems.

[0833] "Transmission means" refers to the communication means for transmitting the information entered by the user to the server.

[0834] "Natural language processing means" refers to means for analyzing user input information and accurately understanding the user's intent.

[0835] "Search means" refers to a means for searching for appropriate information from a database based on the analyzed information.

[0836] "Information generation means" refers to a means for generating specific information or suggestions to be provided to the user based on the searched information.

[0837] "Response Verification Means" refers to the means by which a user can verify the answers provided and ask additional questions or clarifications.

[0838] "Measures to improve the efficiency of logistics centers" refers to measures to improve work efficiency at logistics centers and provide information on operating procedures.

[0839] "Communication means" refers to the means for securely sending and receiving data between the server and the user.

[0840] A "picking route" refers to the optimal route for retrieving and collecting products within a logistics center.

[0841] "Inventory management" refers to the means of managing the quantity and condition of goods stored within a logistics center.

[0842] The system for realizing work efficiency at a logistics center according to the present invention mainly comprises a user interface means, a server, natural language processing means, a database, information generation means, response confirmation means, logistics center efficiency improvement means, and communication means.

[0843] Program processing explanation

[0844] The user interface is a smartphone application screen, through which users input questions and problems related to their daily work. The input information is securely transmitted to the server using the HTTPS protocol.

[0845] The server uses a cloud-based server (e.g., an AWS EC2 instance) and, upon receiving information sent by the user, analyzes the input information using a TensorFlow model, a natural language processing tool, to extract the user's intent and important keywords.

[0846] Based on the extracted keywords, the server searches the PostgreSQL database for relevant information, such as information on optimal picking routes and inventory management methods within a logistics center.

[0847] Next, the information generation means generates a specific and easy-to-understand response based on the search results, for example, providing information to the user in the form of "Here's how to create an efficient product pickup route..."

[0848] The response confirmation means provides an interface for the user to confirm the generated information and input further questions or additional information, thereby enabling the user to continuously obtain the required information.

[0849] Specific examples

[0850] For example, if a user types, "How can I optimize inventory management?"

[0851] 1. The user enters a question using a smartphone application and presses the send button.

[0852] 2. The server receives the request and uses a TensorFlow model to extract keywords such as "inventory management" and "optimization methods" and analyze the content.

[0853] 3. The server searches the PostgreSQL database for information on optimizing inventory management.

[0854] 4. The server generates a specific response such as, "To optimize inventory management, please refer to the following points: 1. Periodic inventory counts 2. ABC analysis 3. Order planning based on trend forecasts..."

[0855] 5. The user reviews the displayed information and re-enters any further questions or additional information.

[0856] Prompt Sentence Examples

[0857] "Please tell me how to streamline inventory management at a distribution center."

[0858] "How can I create an efficient pickup route?"

[0859] "What are some best practices for improving packaging efficiency?"

[0860] This allows logistics center staff to obtain the information they need to improve work efficiency in a timely manner, thereby increasing productivity.

[0861] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0862] Step 1:

[0863] The user enters any question or problem on the smartphone application screen. The entered data is sent securely to the server in text format using the HTTPS protocol. The input of this step is the user's text data, and the output is a request to the server.

[0864] Step 2:

[0865] The server uses a TensorFlow model, a natural language processing tool, to analyze the received data. It analyzes the input text data and extracts key keywords and user intent. For example, from the text "Please tell me how to optimize inventory management," the output from this step would be keywords such as "inventory management" and "optimization method."

[0866] Step 3:

[0867] The server searches the PostgreSQL database based on the extracted keywords. The database stores information on improving the efficiency of logistics center operations and specific operational procedures. The input for this step is the extracted keywords, and the output is a set of related information.

[0868] Step 4:

[0869] Based on the search results, the server uses information generation means to create a specific and easy-to-understand response. For example, it generates an answer in the form of "To optimize inventory management, please refer to the following points: 1. Periodic inventory taking 2. ABC analysis 3. Order planning based on trend forecasts..." The input of this step is information obtained from the database, and the output is the generated response message.

[0870] Step 5:

[0871] The server then sends the generated response message to the user's smartphone. The input is the generated response message, and the output is the message sent to the user's device.

[0872] Step 6:

[0873] The user checks the response message and enters further questions or additional information as needed, at which point the process starts again from step 1. The input of this step is the text data entered by the user again, and the output is a new request.

[0874] Through these processing steps, the information necessary to improve work efficiency at the logistics center is provided, enabling users to take appropriate action in real time.

[0875] 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.

[0876] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system consists of a user interface, a server, natural language processing, a database, information generation, response confirmation, an emotion engine, and secure communication (HTTPS protocol).

[0877] System configuration and operation

[0878] User Interface Means

[0879] User interface means consist of a screen or input device for users to input information. For example, the application screen of a smartphone or PC falls into this category. Through this screen, users can enter questions or concerns into text boxes.

[0880] server

[0881] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0882] Natural language processing tools

[0883] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content of the user's question and intent. For example, if someone enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write," and search for information showing specific steps.

[0884] Database

[0885] The database is a data repository that allows the system to search and store appropriate information. It stores various information related to the process of creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to the user's request.

[0886] Information generation means

[0887] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0888] Response confirmation means

[0889] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0890] Emotion Engine

[0891] The emotion engine is a software module that recognizes emotions from user input text. For example, if a user inputs "I'm very anxious about this procedure," the emotion engine will extract the emotion "anxiety." This allows the system to adjust the content and tone of the response according to the recognized emotion and provide more appropriate support to the user.

[0892] Secure communication method (HTTPS protocol)

[0893] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0894] Specific examples

[0895] For example, suppose a user enters the question, "Who can be a witness to a notarized will? I'm very worried."

[0896] 1. The user enters a question on the device and presses the send button.

[0897] 2. The device sends the entered question as a request to the server.

[0898] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0899] 4. At the same time, the server starts the emotion engine and recognizes the emotion "anxiety" from the input text.

[0900] 5. Based on the analysis results and the recognized emotions, the server searches the database to find information on the requirements for witnesses to notarized wills.

[0901] 6. Based on the relevant information, the server generates a specific response such as, "People who meet the following conditions can be witnesses to a notarized will. Also, because it is common for people to feel anxious about this process, we will provide detailed steps and recommended resources."

[0902] 7. The server generates a response and sends it to the terminal, where the user confirms it.

[0903] 8. The user asks further questions or clarifies based on the information displayed.

[0904] This allows users to quickly and appropriately obtain the information they need while also receiving emotional care.

[0905] The processing flow will be explained below.

[0906] Step 1:

[0907] Users launch the "End-of-Life Concierge" application on their smartphone or computer and enter their login information to authenticate.

[0908] Step 2:

[0909] The device sends login information to the server, and if authentication is successful, the user is shown a chat screen.

[0910] Step 3:

[0911] Users can enter their questions or concerns as text on the chat screen and press the send button. For example, they could type, "Who can be a witness to my notarized will? I'm very worried."

[0912] Step 4:

[0913] The terminal composes the user's input information as request data and transmits it to the server using the HTTPS protocol.

[0914] Step 5:

[0915] The server receives the request and starts the natural language processing engine and the emotion engine simultaneously.

[0916] Step 6:

[0917] The server uses natural language processing tools to analyze the user's input text and extract the main keywords: "notarized will," "witness," and "who can be a witness."

[0918] Step 7:

[0919] The server uses an emotion engine to recognize the emotion "anxiety" from the user's input text.

[0920] Step 8:

[0921] Based on the analysis results and the recognized emotions, the server searches a database to find information on the requirements for witnesses to a notarized will.

[0922] Step 9:

[0923] The server then uses the information to generate a response message that takes into account the sentiment, such as, "People who meet the following criteria can be witnesses to a notarized will. It's common for people to feel anxious about this process. We'll also provide detailed steps and recommended resources."

[0924] Step 10:

[0925] The server sends the generated response message to the terminal via the HTTPS protocol.

[0926] Step 11:

[0927] The terminal decodes the response message received from the server and displays it on the chat screen.

[0928] Step 12:

[0929] The user reviews the displayed response, enters additional questions or new information as needed, and submits again.

[0930] Step 13:

[0931] The terminal again transmits new request data to the server and repeats the series of processes from step 5 to step 12.

[0932] This allows users to efficiently obtain the necessary end-of-life information while receiving careful support that takes their feelings into consideration.

[0933] Example 2

[0934] 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."

[0935] While conventional information provision systems analyze the information entered by users and provide appropriate information, they lack consideration for the user's feelings, resulting in problems such as insufficient system response to sufficiently increase user satisfaction and peace of mind. Furthermore, there is a lack of systems that can provide appropriate analysis and information specialized for specific topics, such as how to write a will. Furthermore, in terms of security, encryption methods to prevent data leaks and unauthorized access are insufficient, potentially putting user information at risk.

[0936] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0937] In this invention, the server includes natural language processing means for analyzing user input information, emotion recognition means for analyzing the user's emotions, and means for generating and responding to the user in a way that takes the user's emotions into consideration. This makes it possible to provide appropriate and specific information while taking the user's emotions into consideration. Furthermore, analysis and information provision specialized for specific themes can be realized, thereby increasing user satisfaction and a sense of security. Furthermore, secure transmission and reception of data using encryption means can reduce security risks.

[0938] "Interface means" refers to means such as a screen or input device for users to input information.

[0939] "Natural language processing means" refers to technical means for analyzing text information entered by a user, extracting keywords, and understanding their intent.

[0940] "Emotion recognition means" refers to technical means for analyzing and extracting emotions from a user's input text.

[0941] A "response generation means" is a mechanism that creates specific information or suggestions to be provided to users based on the analysis and search results.

[0942] A "database" is a data collection that allows an information provision system to search for and store appropriate information, and it stores various information, for example, related to legal procedures and end-of-life planning.

[0943] "Encryption means" refers to technical means that encrypts information to prevent unauthorized access or information leakage in order to ensure secure transmission and reception of data.

[0944] "Secure communications" refers to communications protocols and related technologies that enable secure transmission and reception of data over the Internet.

[0945] "Emotionally sensitive responses" are a method of taking into account the user's emotional state and generating responses whose tone and content match those emotions.

[0946] "Specialized analysis and information provision means" refers to technical means that perform specialized analysis of information on a specific topic and provide more accurate and detailed information in response to user questions.

[0947] This invention relates to an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system consists of a user interface, a server, natural language processing, a database, information generation, response confirmation, emotion recognition, and secure communication (HTTPS protocol).

[0948] User Interface Means

[0949] User interface means consist of a screen or input device for users to input information. Specifically, this would be the application screen of a smartphone or PC. Through this screen, users can enter questions or concerns into text boxes.

[0950] server

[0951] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[0952] Natural language processing tools

[0953] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content and intent of the user's question. For example, if the user enters "Please tell me how to write a will," the server extracts keywords such as "will" and "how to write" and searches for information showing specific steps. The natural language processing used here is a generative AI model (e.g., OpenAI GPT-3).

[0954] Database

[0955] A database is a data collection that allows the system to search and store appropriate information. For example, it stores various information related to procedures for creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to user requests. The database used is specifically a MySQL database.

[0956] Information generation means

[0957] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[0958] Response confirmation means

[0959] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[0960] emotion recognition means

[0961] The emotion recognizer is a software module for recognizing emotions from user input text. For example, if a user inputs "I am very anxious about this procedure," the emotion recognizer will extract the emotion "anxiety." This allows the system to adjust the content and tone of the response according to the recognized emotion and provide more appropriate support to the user.

[0962] Secure communication method (HTTPS protocol)

[0963] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[0964] Specific examples

[0965] For example, if a user enters the question, "Who can be a witness to a notarized will? I'm very worried," the following is a specific example:

[0966] 1. The user enters a question on the device and presses the send button.

[0967] 2. The device sends the entered question as a request to the server.

[0968] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[0969] 4. At the same time, the server activates the emotion recognition means and recognizes the emotion "anxiety" from the input text.

[0970] 5. Based on the analysis results and the recognized emotions, the server searches the database to find information on the requirements for witnesses to notarized wills.

[0971] 6. Based on the relevant information, the server generates a specific response such as, "People who meet the following conditions can be witnesses to a notarized will. Also, because it is common for people to feel anxious about this process, we will provide detailed steps and recommended resources."

[0972] 7. The server generates a response and sends it to the terminal, where the user confirms it.

[0973] 8. The user asks further questions or clarifies based on the information displayed.

[0974] This allows users to quickly and appropriately obtain the information they need while also receiving emotional care.The system also uses the HTTPS protocol for secure communication, reducing the risk of information leaks and unauthorized access.

[0975] Prompt Sentence Examples

[0976] As a concrete example, we propose a user question: "Who can be a witness to a notarized will? I'm very worried." An example of a prompt sentence to generate an appropriate response to this question is as follows:

[0977] Example prompt:

[0978] A user asks, "Who can witness a notarized will? I'm very worried." Generate an appropriate response to this question and provide emotionally sensitive support.

[0979] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0980] Step 1:

[0981] The user enters a question or concern into the application screen on their smartphone or computer and presses the send button. An example of input is the question, "Who can be a witness to a notarized will? I'm very worried." This input triggers the next processing step. The input data is question information in text format.

[0982] Step 2:

[0983] The terminal receives the question information entered by the user and sends it to the server using the HTTPS protocol. The data is encrypted here to ensure secure communication. The input data is encrypted text information, and the output data is encrypted data sent to the server.

[0984] Step 3:

[0985] The server receives the encrypted data and decrypts it to obtain text information. It then performs natural language processing on the obtained text information using a generative AI model (e.g., OpenAI GPT-3). Specifically, it extracts keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the intent of the question. The input data is the decrypted text information, and the output data is the analyzed keywords and the intent of the question.

[0986] Step 4:

[0987] The server activates the emotion recognition means and analyzes the user's emotion from the input text. For example, it extracts the emotion "anxiety" from the sentence "I'm very anxious." The input data is text information, and the output data is the analyzed emotion information.

[0988] Step 5:

[0989] The server searches a database (e.g., a MySQL database) based on the analysis results and the recognized emotions. It searches for information on "requirements for witnesses to notarized wills" and obtains the necessary data. The input data are the analyzed keywords and emotion information, and the output data is the searched database information.

[0990] Step 6:

[0991] The server uses the information generation means to generate a response based on the acquired database information. The generated response takes into consideration the user's emotions. For example, a specific response such as "A person who meets the following conditions can become a witness to a notarized will. Also, since it is common for people to feel anxious, we will also provide detailed steps and recommended resources." The input data is the information acquired from the database and emotional information, and the output data is the generated response.

[0992] Step 7:

[0993] The server encrypts the generated response and sends it to the terminal. The input data is the generated response information, and the output data is the encrypted response data.

[0994] Step 8:

[0995] The terminal receives the encrypted response data, decrypts it, and displays it to the user. The user reviews the displayed response and, if necessary, asks additional questions or confirmations. Once this process is complete, the terminal returns to the next step. The input data is the encrypted data received from the server, and the output data is the decrypted response information.

[0996] In this way, each step works together, allowing users to obtain accurate and prompt information and receive individualized, specific support in real time.

[0997] (Application example 2)

[0998] 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."

[0999] In recent years, the use of online shopping sites has increased, and users often have trouble gathering information and making decisions when considering a purchase. However, current systems have difficulty providing quick and appropriate advice to address specific questions and concerns users have. Therefore, there is a need for support systems that allow users to make purchasing decisions with peace of mind. In particular, the realization of a system that can respond appropriately to users' emotions is an urgent issue.

[1000] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1001] In this invention, the server includes interface means for the user to input information, means for transmitting the information input by the user to the server, natural language processing means for the server to analyze the information input by the user, means for the server to search a database for appropriate information based on the analysis results, means for the server to generate the searched information and respond to the user, means for the user to check the generated response and input additional information, emotion engine means for adjusting the response content based on emotion analysis, interface means for the user to input questions and concerns about products, and generative AI model means for the server to provide information related to the user's purchasing behavior in real time. This allows the user to receive appropriate support when they have concerns or worries about a purchase, allowing them to make decisions with peace of mind.

[1002] "Interface means for users to input information" refers to a screen or input device used by users to input questions or concerns.

[1003] "Means for transmitting information entered by the user to the server" refers to the mechanism by which information entered by the user from the terminal is transmitted to the server.

[1004] "Natural language processing means for the server to analyze the user's input information" refers to technology that allows the server to understand the user's input text and analyze its intent and content.

[1005] "Means for the server to search for appropriate information from a database based on the analysis results" refers to a mechanism by which the server searches for relevant information from a database based on the analysis results.

[1006] "Means for the server to generate the searched information and respond to the user" refers to the mechanism by which the server generates an appropriate response based on the information retrieved from the database and returns it to the user.

[1007] "Means for the user to review the generated response and enter additional information" means a mechanism that allows the user to view the response from the server and enter further questions or additional information.

[1008] "Emotion engine means for adjusting response content based on emotion analysis" refers to technology for analyzing emotions from user input and adjusting the content and tone of the response.

[1009] "Interface means for users to input product-related questions and concerns" refers to a screen or input device designed to make it easy for users to input product-related inquiries.

[1010] "Generative AI model means by which a server provides information related to a user's purchasing behavior in real time" refers to an artificial intelligence model that generates related information based on a user's purchasing behavior and presents it in real time.

[1011] The present invention relates to a system that quickly provides appropriate information and emotional support to users in response to questions or concerns they may have when considering a purchase on an online shopping site. The system includes a user interface, a server, a natural language processing system, a database, an information generation system, an emotion engine, and a generative AI model system.

[1012] Specifically, user interface means include smartphone applications and web interfaces through which users can input questions or concerns about products.

[1013] The server receives the information entered by the user and analyzes the text information using natural language processing means. This analysis process utilizes machine learning libraries such as TensorFlow. Based on the analysis results, the server searches for appropriate information from a database. The searched information is then generated in a form appropriate for the user by information generation means.

[1014] The emotion engine uses an emotion analysis tool such as IBM Watson's Tone Analyzer to extract emotions from user input. For example, if a user inputs, "I'm thinking about whether to purchase this product. I'm worried about the reviews," the emotion engine will recognize the emotion as "anxiety." Based on this recognition, the server will adjust the content and tone of the response and provide appropriate advice to the user.

[1015] The generative AI modeling method provides real-time information related to a user's purchasing behavior, including techniques to provide the most relevant information to the user based on their past purchase history and responses to similar questions.

[1016] For example, if a user inputs a question such as, "I'm thinking about whether to purchase this product. I'm worried about the reviews," the system generates a response using the following steps. First, the natural language processing means extracts the keywords "product," "purchase," "concern," and "review," and then the emotion engine recognizes the emotion "anxiety." Next, related product review information and advice for considering the purchase are retrieved from the database. Finally, the generative AI model means references the user's past purchase history and the behavior of other users to generate the optimal response in real time and present it to the user.

[1017] In this way, users can eliminate any concerns about purchasing products and make decisions with peace of mind.

[1018] Examples and prompts

[1019] As a concrete example, when a user enters the question, "I'm wondering whether to purchase this product. I'm worried about the reviews," the system generates the following response:

[1020] Example prompt sentence:

[1021] If a user types in a question like, "I'm not sure whether to buy this product or not. I'm worried about the reviews," how would an assistant app based on this invention respond?

[1022] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1023] Step 1:

[1024] The user enters information.

[1025] Users input questions or concerns about products through smartphone applications or web interfaces, often entering text such as "I'm thinking about whether to purchase this product. I'm worried about the reviews." The input information is sent to a server via the device.

[1026] Step 2:

[1027] The server receives the user's input and performs natural language processing.

[1028] The server receives the user's input information sent from the device. It then uses machine learning libraries such as TensorFlow to analyze the input text. Specifically, the server extracts keywords such as "product," "purchase," "problem," and "review" to understand the user's intent. The results of this analysis are passed to the next step.

[1029] Step 3:

[1030] The server performs sentiment analysis.

[1031] The server uses IBM Watson's Tone Analyzer to extract emotions from the user's input text. For example, it recognizes the emotion "anxiety" from the input text "I'm thinking about whether to buy this product. I'm worried about the reviews." The results of the emotion analysis are passed to the next step.

[1032] Step 4:

[1033] The server searches the database based on the analysis results.

[1034] The server uses the results of natural language processing and sentiment analysis to search for relevant information from a database, such as product reviews or purchasing advice, to find information that best suits the user's question. The search results are then passed on to the next step.

[1035] Step 5:

[1036] The server generates the appropriate information and responds to the user.

[1037] The server uses a generative AI model to generate an appropriate response based on the search results retrieved from the database. It also takes into account the user's past purchase history and other users' responses to similar questions. For example, it generates a response such as, "Here are some reviews from other users of this product. We also recommend that you double-check the return policy if you have any concerns."

[1038] Step 6:

[1039] The server sends the response to the user's device.

[1040] The generated response is encrypted and sent using the HTTPS protocol to the user's device, where the user can view the response, and then provide further questions or confirmations.

[1041] Step 7:

[1042] The user reviews the generated response and enters additional information.

[1043] The user can review the server's response and re-enter any questions or additional information they have. This continuous interaction allows the user to gain more information and make a more confident purchasing decision.

[1044] Examples:

[1045] For example, if a user types in the question "I'm not sure whether to buy this product or not, and I'm worried about the reviews," the steps above will be followed to generate the following specific response:

[1046] Example prompt sentence:

[1047] If a user types in a question like, "I'm not sure whether to buy this product or not. I'm worried about the reviews," how would an assistant app based on this invention respond?

[1048] 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.

[1049] 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.

[1050] 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.

[1051] [Fourth embodiment]

[1052] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1053] 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.

[1054] 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).

[1055] 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.

[1056] 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.

[1057] 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).

[1058] 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.

[1059] 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.

[1060] 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.

[1061] 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.

[1062] 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.

[1063] 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.

[1064] 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."

[1065] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system mainly consists of a user interface, a server, natural language processing, a database, information generation means, response confirmation means, and secure communication means (HTTPS protocol).

[1066] System configuration and operation

[1067] User Interface Means

[1068] User interface means consist of a screen or input device for users to input information. For example, the application screen of a smartphone or PC falls into this category. Through this screen, users can enter questions or concerns into text boxes.

[1069] server

[1070] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[1071] Natural language processing tools

[1072] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content of the user's question and intent. For example, if someone enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write," and search for information showing specific steps.

[1073] Database

[1074] The database is a data repository that allows the system to search and store appropriate information. It stores various information related to the process of creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to the user's request.

[1075] Information generation means

[1076] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[1077] Response confirmation means

[1078] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[1079] Secure communication method (HTTPS protocol)

[1080] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[1081] Specific examples

[1082] For example, suppose a user types the question, "Who can witness a notarized will?"

[1083] 1. The user enters a question on the device and presses the send button.

[1084] 2. The device sends the entered question as a request to the server.

[1085] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[1086] 4. The server searches the database to find information regarding witness requirements for notarized wills.

[1087] 5. The server uses the relevant information to generate a specific response such as, "A person who meets the following conditions can be a witness to a notarized will..."

[1088] 6. The server generates a response and sends it to the terminal, where the user confirms it.

[1089] 7. The user asks further questions or clarifies based on the information displayed.

[1090] This allows users to easily access specialized information from the comfort of their own home and proceed with end-of-life planning that is appropriate to their own circumstances.

[1091] The processing flow will be explained below.

[1092] Step 1:

[1093] Users launch the "End-of-Life Concierge" application on their smartphone or computer and enter their login information to authenticate.

[1094] Step 2:

[1095] The device sends login information to the server, and if authentication is successful, the user is shown a chat screen.

[1096] Step 3:

[1097] Users enter their questions or concerns as text on the chat screen and press the send button.

[1098] Step 4:

[1099] The terminal composes the user's input information as request data and transmits it to the server using the HTTPS protocol.

[1100] Step 5:

[1101] The server receives the request and launches a natural language processing engine.

[1102] Step 6:

[1103] The server uses natural language processing tools to analyze the user's input text and extract key keywords and their intent.

[1104] Step 7:

[1105] Based on the analysis results, the server searches the database and collects related information.

[1106] Step 8:

[1107] The server generates a response message for the user based on the collected information.

[1108] Step 9:

[1109] The server sends the generated response message to the terminal via the HTTPS protocol.

[1110] Step 10:

[1111] The terminal decodes the response message received from the server and displays it on the chat screen.

[1112] Step 11:

[1113] The user reviews the displayed response, enters additional questions or new information as needed, and submits again.

[1114] Step 12:

[1115] The terminal again transmits new request data to the server and repeats the series of processes from step 5 to step 11.

[1116] This allows users to obtain specific and accurate information necessary for their end-of-life planning through continuous interaction.

[1117] Example 1

[1118] 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."

[1119] In modern society, it is extremely important for users to obtain specialized information quickly and accurately. Information regarding end-of-life planning is particularly complex, and while accurate information tailored to individual circumstances is required, it is difficult to find appropriate sources of information. Furthermore, from a security perspective, data protection is necessary when sending and receiving information. A system that addresses these issues is needed.

[1120] 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.

[1121] In this invention, the server includes input means for a user to input information, means for transmitting the information input by the user as data, natural language processing means for the information processing device to analyze the information input by the user, means for the information processing device to search for appropriate information from an information storage device based on the analysis results, information generation means for the information processing device to generate the searched information and respond to the user, input means for the user to check the generated response and input additional information, and secure communication means for securely transmitting and receiving information, thereby enabling users to quickly and safely obtain accurate information tailored to their individual circumstances.

[1122] A "user" is an entity that utilizes a system to input information and obtain a response.

[1123] "Input means" refers to a device or interface through which a user inputs information, and examples include text boxes on smartphones and personal computers.

[1124] "Means for transmitting data" refers to a mechanism for transmitting input information to a server, and includes secure communication methods such as the HTTPS protocol.

[1125] An "information processing device" is a central processing unit that performs multiple processes and analyzes information received from a user.

[1126] "Natural language processing means" refers to technology for analyzing text information entered by a user and understanding its content and intent, and includes generative models.

[1127] "Information storage device" refers to a database or data repository used to retrieve relevant information based on the results of an analysis.

[1128] "Information generation means" refers to a mechanism for generating specific responses or information based on search results.

[1129] "Secure communication means" refers to technology for securely sending and receiving information, including the HTTPS protocol, which uses encrypted communications.

[1130] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. The system configuration is as follows.

[1131] User Interface Means

[1132] User interface means consist of a screen or input device for users to input information. Specifically, this corresponds to the application screen of a smartphone or PC. Through this screen, users can enter their questions or concerns into a text box and press the send button.

[1133] Terminal

[1134] The device is the means by which the information entered by the user is sent to the server, and uses the HTTPS protocol to encrypt and transmit data securely. For example, a smartphone or PC is one such device.

[1135] server

[1136] The server is a central processing unit that receives, analyzes, and processes information sent by users. The server is equipped with the following means:

[1137] Natural language processing tools

[1138] The server uses natural language processing (e.g., a generative AI model) to analyze the text information entered by the user. This allows it to accurately understand the content and intent of the user's question. For example, if the user enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write" and search for information showing specific steps.

[1139] Information Storage Device

[1140] The information storage device is a data repository that allows the system to search for and store appropriate information. For example, it stores various information related to procedures for creating wills, legal procedures, and end-of-life planning. The server uses this information to provide information in response to user requests.

[1141] Information generation means

[1142] The information generation means is a mechanism for creating specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[1143] Secure Communication Methods

[1144] The server uses the HTTPS protocol to ensure secure transmission of information, which encrypts communication between the user and the server and prevents information leakage and unauthorized access.

[1145] Specific examples

[1146] For example, suppose a user types the question, "Who can witness a notarized will?"

[1147] The user enters a question into the terminal and presses the send button.

[1148] The terminal sends the entered question as a request to the server.

[1149] The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[1150] The server searches the information storage device to find information regarding the requirements for witnesses to notarized wills.

[1151] Based on the relevant information, the server generates a specific response such as "A person who meets the following conditions can be a witness to a notarized will..."

[1152] The server generates a response and sends it to the terminal, where the user confirms it.

[1153] The user can then ask further questions or make further confirmations based on the displayed information, for example, by entering a follow-up question such as, "What are the conditions?"

[1154] An example of a prompt sentence could be a text input such as "Who can be a witness to a notarized will?"

[1155] This allows users to easily access specialized information from the comfort of their own home and proceed with end-of-life planning that is appropriate to their own circumstances.

[1156] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1157] Step 1: User Enters Information

[1158] The user enters their question or concern into the text box on the application screen of their smartphone or computer and presses the send button. For example, they might type, "Please tell me how to write a will." At this time, the information entered by the user is generated as input data.

[1159] Step 2: The device sends a request to the server

[1160] The terminal receives the text data entered by the user and sends it to the server using the HTTPS protocol. Specifically, it converts the input data into JSON format and sends it to the server as an encrypted request. The input here is the question text entered by the user, and the output is the encrypted data sent to the server.

[1161] Step 3: The server receives and parses the request

[1162] The server receives the request sent from the terminal, decodes it, and extracts the text data. It then analyzes this text data using natural language processing to extract keywords such as "will" and "how to write it." The input is the encrypted request data, and the output is the analyzed keywords.

[1163] Step 4: The server retrieves the information from the database

[1164] The server searches for relevant information from the information storage device based on the keywords obtained through the analysis. Specifically, it uses an SQL query to retrieve information on "how to write a will" from the database. The input is the analyzed keywords, and the output is the information data of the search results.

[1165] Step 5: Server generates response

[1166] The server generates a response to the user based on the search results. Using the information generation means, it formats the acquired information and creates a document containing specific instructions such as "Here's how to write a will...". The input is the information data from the search results, and the output is the generated response document.

[1167] Step 6: Send the server-generated response to the device

[1168] The server converts the generated response document into JSON format and sends it to the terminal using the HTTPS protocol. The input is the generated response document, and the output is the encrypted response data.

[1169] Step 7: User reviews response and provides additional input

[1170] The user checks the response displayed on the terminal, for example, "Here's how to write a will..." If the user has further questions, for example, "What should I pay attention to when writing a will?", they input again and repeat the same process. The input is the displayed response document, and the output is the new question text.

[1171] (Application example 1)

[1172] 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."

[1173] There is a lack of means to quickly provide appropriate information on various issues in daily operations, such as improving work efficiency at distribution centers, inventory management, optimizing picking routes, etc. Employees often lack specific knowledge about how to operate the system and how to improve efficiency, which leads to a decline in productivity.

[1174] 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.

[1175] In this invention, the server includes interface means for a user to input information, means for transmitting the information input by the user to the server, natural language processing means for the server to analyze the information input by the user, means for the server to search a database for appropriate information based on the analysis results, information generation means for the server to generate the searched information and respond to the user, response confirmation means for the user to confirm the generated response and input additional information, means for providing information on improving the efficiency of the logistics center and operating procedures, and communication means for securely transmitting and receiving data. This enables logistics center staff to quickly obtain appropriate information in real time for various problems in their daily work.

[1176] "User interface means" refers to the input device and screen through which the user enters questions or problems.

[1177] "Transmission means" refers to the communication means for transmitting the information entered by the user to the server.

[1178] "Natural language processing means" refers to means for analyzing user input information and accurately understanding the user's intent.

[1179] "Search means" refers to a means for searching for appropriate information from a database based on the analyzed information.

[1180] "Information generation means" refers to a means for generating specific information or suggestions to be provided to the user based on the searched information.

[1181] "Response Verification Means" refers to the means by which a user can verify the answers provided and ask additional questions or clarifications.

[1182] "Measures to improve the efficiency of logistics centers" refers to measures to improve work efficiency at logistics centers and provide information on operating procedures.

[1183] "Communication means" refers to the means for securely sending and receiving data between the server and the user.

[1184] A "picking route" refers to the optimal route for retrieving and collecting products within a logistics center.

[1185] "Inventory management" refers to the means of managing the quantity and condition of goods stored within a logistics center.

[1186] The system for realizing work efficiency at a logistics center according to the present invention mainly comprises a user interface means, a server, natural language processing means, a database, information generation means, response confirmation means, logistics center efficiency improvement means, and communication means.

[1187] Program processing explanation

[1188] The user interface is a smartphone application screen, through which users input questions and problems related to their daily work. The input information is securely transmitted to the server using the HTTPS protocol.

[1189] The server uses a cloud-based server (e.g., an AWS EC2 instance) and, upon receiving information sent by the user, analyzes the input information using a TensorFlow model, a natural language processing tool, to extract the user's intent and important keywords.

[1190] Based on the extracted keywords, the server searches the PostgreSQL database for relevant information, such as information on optimal picking routes and inventory management methods within a logistics center.

[1191] Next, the information generation means generates a specific and easy-to-understand response based on the search results, for example, providing information to the user in the form of "Here's how to create an efficient product pickup route..."

[1192] The response confirmation means provides an interface for the user to confirm the generated information and input further questions or additional information, thereby enabling the user to continuously obtain the required information.

[1193] Specific examples

[1194] For example, if a user types, "How can I optimize inventory management?"

[1195] 1. The user enters a question using a smartphone application and presses the send button.

[1196] 2. The server receives the request and uses a TensorFlow model to extract keywords such as "inventory management" and "optimization methods" and analyze the content.

[1197] 3. The server searches the PostgreSQL database for information on optimizing inventory management.

[1198] 4. The server generates a specific response such as, "To optimize inventory management, please refer to the following points: 1. Periodic inventory counts 2. ABC analysis 3. Order planning based on trend forecasts..."

[1199] 5. The user reviews the displayed information and re-enters any further questions or additional information.

[1200] Prompt Sentence Examples

[1201] "Please tell me how to streamline inventory management at a distribution center."

[1202] "How can I create an efficient pickup route?"

[1203] "What are some best practices for improving packaging efficiency?"

[1204] This allows logistics center staff to obtain the information they need to improve work efficiency in a timely manner, thereby increasing productivity.

[1205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1206] Step 1:

[1207] The user enters any question or problem on the smartphone application screen. The entered data is sent securely to the server in text format using the HTTPS protocol. The input of this step is the user's text data, and the output is a request to the server.

[1208] Step 2:

[1209] The server uses a TensorFlow model, a natural language processing tool, to analyze the received data. It analyzes the input text data and extracts key keywords and user intent. For example, from the text "Please tell me how to optimize inventory management," the output from this step would be keywords such as "inventory management" and "optimization method."

[1210] Step 3:

[1211] The server searches the PostgreSQL database based on the extracted keywords. The database stores information on improving the efficiency of logistics center operations and specific operational procedures. The input for this step is the extracted keywords, and the output is a set of related information.

[1212] Step 4:

[1213] Based on the search results, the server uses information generation means to create a specific and easy-to-understand response. For example, it generates an answer in the form of "To optimize inventory management, please refer to the following points: 1. Periodic inventory taking 2. ABC analysis 3. Order planning based on trend forecasts..." The input of this step is information obtained from the database, and the output is the generated response message.

[1214] Step 5:

[1215] The server then sends the generated response message to the user's smartphone. The input is the generated response message, and the output is the message sent to the user's device.

[1216] Step 6:

[1217] The user checks the response message and enters further questions or additional information as needed, at which point the process starts again from step 1. The input of this step is the text data entered by the user again, and the output is a new request.

[1218] Through these processing steps, the information necessary to improve work efficiency at the logistics center is provided, enabling users to take appropriate action in real time.

[1219] 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.

[1220] This invention is an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system consists of a user interface, a server, natural language processing, a database, information generation, response confirmation, an emotion engine, and secure communication (HTTPS protocol).

[1221] System configuration and operation

[1222] User Interface Means

[1223] User interface means consist of a screen or input device for users to input information. For example, the application screen of a smartphone or PC falls into this category. Through this screen, users can enter questions or concerns into text boxes.

[1224] server

[1225] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[1226] Natural language processing tools

[1227] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content of the user's question and intent. For example, if someone enters, "Please tell me how to write a will," the server will extract keywords such as "will" and "how to write," and search for information showing specific steps.

[1228] Database

[1229] The database is a data repository that allows the system to search and store appropriate information. It stores various information related to the process of creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to the user's request.

[1230] Information generation means

[1231] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[1232] Response confirmation means

[1233] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[1234] Emotion Engine

[1235] The emotion engine is a software module that recognizes emotions from user input text. For example, if a user inputs "I'm very anxious about this procedure," the emotion engine will extract the emotion "anxiety." This allows the system to adjust the content and tone of the response according to the recognized emotion and provide more appropriate support to the user.

[1236] Secure communication method (HTTPS protocol)

[1237] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[1238] Specific examples

[1239] For example, suppose a user enters the question, "Who can be a witness to a notarized will? I'm very worried."

[1240] 1. The user enters a question on the device and presses the send button.

[1241] 2. The device sends the entered question as a request to the server.

[1242] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[1243] 4. At the same time, the server starts the emotion engine and recognizes the emotion "anxiety" from the input text.

[1244] 5. Based on the analysis results and the recognized emotions, the server searches the database to find information on the requirements for witnesses to notarized wills.

[1245] 6. Based on the relevant information, the server generates a specific response such as, "People who meet the following conditions can be witnesses to a notarized will. Also, because it is common for people to feel anxious about this process, we will provide detailed steps and recommended resources."

[1246] 7. The server generates a response and sends it to the terminal, where the user confirms it.

[1247] 8. The user asks further questions or clarifies based on the information displayed.

[1248] This allows users to quickly and appropriately obtain the information they need while also receiving emotional care.

[1249] The processing flow will be explained below.

[1250] Step 1:

[1251] Users launch the "End-of-Life Concierge" application on their smartphone or computer and enter their login information to authenticate.

[1252] Step 2:

[1253] The device sends login information to the server, and if authentication is successful, the user is shown a chat screen.

[1254] Step 3:

[1255] Users can enter their questions or concerns as text on the chat screen and press the send button. For example, they could type, "Who can be a witness to my notarized will? I'm very worried."

[1256] Step 4:

[1257] The terminal composes the user's input information as request data and transmits it to the server using the HTTPS protocol.

[1258] Step 5:

[1259] The server receives the request and starts the natural language processing engine and the emotion engine simultaneously.

[1260] Step 6:

[1261] The server uses natural language processing tools to analyze the user's input text and extract the main keywords: "notarized will," "witness," and "who can be a witness."

[1262] Step 7:

[1263] The server uses an emotion engine to recognize the emotion "anxiety" from the user's input text.

[1264] Step 8:

[1265] Based on the analysis results and the recognized emotions, the server searches a database to find information on the requirements for witnesses to a notarized will.

[1266] Step 9:

[1267] The server then uses the information to generate a response message that takes into account the sentiment, such as, "People who meet the following criteria can be witnesses to a notarized will. It's common for people to feel anxious about this process. We'll also provide detailed steps and recommended resources."

[1268] Step 10:

[1269] The server sends the generated response message to the terminal via the HTTPS protocol.

[1270] Step 11:

[1271] The terminal decodes the response message received from the server and displays it on the chat screen.

[1272] Step 12:

[1273] The user reviews the displayed response, enters additional questions or new information as needed, and submits again.

[1274] Step 13:

[1275] The terminal again transmits new request data to the server and repeats the series of processes from step 5 to step 12.

[1276] This allows users to efficiently obtain the necessary end-of-life information while receiving careful support that takes their feelings into consideration.

[1277] Example 2

[1278] 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."

[1279] While conventional information provision systems analyze the information entered by users and provide appropriate information, they lack consideration for the user's feelings, resulting in problems such as insufficient system response to sufficiently increase user satisfaction and peace of mind. Furthermore, there is a lack of systems that can provide appropriate analysis and information specialized for specific topics, such as how to write a will. Furthermore, in terms of security, encryption methods to prevent data leaks and unauthorized access are insufficient, potentially putting user information at risk.

[1280] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1281] In this invention, the server includes natural language processing means for analyzing user input information, emotion recognition means for analyzing the user's emotions, and means for generating and responding to the user in a way that takes the user's emotions into consideration. This makes it possible to provide appropriate and specific information while taking the user's emotions into consideration. Furthermore, analysis and information provision specialized for specific themes can be realized, thereby increasing user satisfaction and a sense of security. Furthermore, secure transmission and reception of data using encryption means can reduce security risks.

[1282] "Interface means" refers to means such as a screen or input device for users to input information.

[1283] "Natural language processing means" refers to technical means for analyzing text information entered by a user, extracting keywords, and understanding their intent.

[1284] "Emotion recognition means" refers to technical means for analyzing and extracting emotions from a user's input text.

[1285] A "response generation means" is a mechanism that creates specific information or suggestions to be provided to users based on the analysis and search results.

[1286] A "database" is a data collection that allows an information provision system to search for and store appropriate information, and it stores various information, for example, related to legal procedures and end-of-life planning.

[1287] "Encryption means" refers to technical means that encrypts information to prevent unauthorized access or information leakage in order to ensure secure transmission and reception of data.

[1288] "Secure communications" refers to communications protocols and related technologies that enable secure transmission and reception of data over the Internet.

[1289] "Emotionally sensitive responses" are a method of taking into account the user's emotional state and generating responses whose tone and content match those emotions.

[1290] "Specialized analysis and information provision means" refers to technical means that perform specialized analysis of information on a specific topic and provide more accurate and detailed information in response to user questions.

[1291] This invention relates to an information provision system that allows users to easily input questions and concerns about end-of-life planning and receive accurate information tailored to their specific circumstances in real time. This system consists of a user interface, a server, natural language processing, a database, information generation, response confirmation, emotion recognition, and secure communication (HTTPS protocol).

[1292] User Interface Means

[1293] User interface means consist of a screen or input device for users to input information. Specifically, this would be the application screen of a smartphone or PC. Through this screen, users can enter questions or concerns into text boxes.

[1294] server

[1295] The server is a central processing unit that receives information sent by users, analyzes and processes it, and generates and sends an appropriate response. When the server receives a user request, it analyzes the content, searches for appropriate information in a database, and generates a response based on the analysis results and sends it back to the user.

[1296] Natural language processing tools

[1297] The server uses natural language processing to analyze the text information entered by the user. This allows it to accurately understand the content and intent of the user's question. For example, if the user enters "Please tell me how to write a will," the server extracts keywords such as "will" and "how to write" and searches for information showing specific steps. The natural language processing used here is a generative AI model (e.g., OpenAI GPT-3).

[1298] Database

[1299] A database is a data collection that allows the system to search and store appropriate information. For example, it stores various information related to procedures for creating a will, legal procedures, and end-of-life planning, and the server uses this information to provide information according to user requests. The database used is specifically a MySQL database.

[1300] Information generation means

[1301] The information generation method is a mechanism that creates specific information and suggestions to be provided to users based on the analysis and search results. For example, it generates a document containing specific instructions on how to write a will and important points to note, and sends it to the user.

[1302] Response confirmation means

[1303] The user can review the displayed response and re-enter any new questions or additional information they may have. To do this, an interface is provided that accepts re-entry. This continuous interaction allows the user to obtain successively more detailed information.

[1304] emotion recognition means

[1305] The emotion recognizer is a software module for recognizing emotions from user input text. For example, if a user inputs "I am very anxious about this procedure," the emotion recognizer will extract the emotion "anxiety." This allows the system to adjust the content and tone of the response according to the recognized emotion and provide more appropriate support to the user.

[1306] Secure communication method (HTTPS protocol)

[1307] The system uses the HTTPS protocol to ensure secure data transmission, encrypting communications between users and the server to prevent information leaks and unauthorized access.

[1308] Specific examples

[1309] For example, if a user enters the question, "Who can be a witness to a notarized will? I'm very worried," the following is a specific example:

[1310] 1. The user enters a question on the device and presses the send button.

[1311] 2. The device sends the entered question as a request to the server.

[1312] 3. The server receives the request and uses natural language processing to extract keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the content.

[1313] 4. At the same time, the server activates the emotion recognition means and recognizes the emotion "anxiety" from the input text.

[1314] 5. Based on the analysis results and the recognized emotions, the server searches the database to find information on the requirements for witnesses to notarized wills.

[1315] 6. Based on the relevant information, the server generates a specific response such as, "People who meet the following conditions can be witnesses to a notarized will. Also, because it is common for people to feel anxious about this process, we will provide detailed steps and recommended resources."

[1316] 7. The server generates a response and sends it to the terminal, where the user confirms it.

[1317] 8. The user asks further questions or clarifies based on the information displayed.

[1318] This allows users to quickly and appropriately obtain the information they need while also receiving emotional care.The system also uses the HTTPS protocol for secure communication, reducing the risk of information leaks and unauthorized access.

[1319] Prompt Sentence Examples

[1320] As a concrete example, we propose a user question: "Who can be a witness to a notarized will? I'm very worried." An example of a prompt sentence to generate an appropriate response to this question is as follows:

[1321] Example prompt:

[1322] A user asks, "Who can witness a notarized will? I'm very worried." Generate an appropriate response to this question and provide emotionally sensitive support.

[1323] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1324] Step 1:

[1325] The user enters a question or concern into the application screen on their smartphone or computer and presses the send button. An example of input is the question, "Who can be a witness to a notarized will? I'm very worried." This input triggers the next processing step. The input data is question information in text format.

[1326] Step 2:

[1327] The terminal receives the question information entered by the user and sends it to the server using the HTTPS protocol. The data is encrypted here to ensure secure communication. The input data is encrypted text information, and the output data is encrypted data sent to the server.

[1328] Step 3:

[1329] The server receives the encrypted data and decrypts it to obtain text information. It then performs natural language processing on the obtained text information using a generative AI model (e.g., OpenAI GPT-3). Specifically, it extracts keywords such as "notarized will," "witness," and "who can be a witness," and analyzes the intent of the question. The input data is the decrypted text information, and the output data is the analyzed keywords and the intent of the question.

[1330] Step 4:

[1331] The server activates the emotion recognition means and analyzes the user's emotion from the input text. For example, it extracts the emotion "anxiety" from the sentence "I'm very anxious." The input data is text information, and the output data is the analyzed emotion information.

[1332] Step 5:

[1333] The server searches a database (e.g., a MySQL database) based on the analysis results and the recognized emotions. It searches for information on "requirements for witnesses to notarized wills" and obtains the necessary data. The input data are the analyzed keywords and emotion information, and the output data is the searched database information.

[1334] Step 6:

[1335] The server uses the information generation means to generate a response based on the acquired database information. The generated response takes into consideration the user's emotions. For example, a specific response such as "A person who meets the following conditions can become a witness to a notarized will. Also, since it is common for people to feel anxious, we will also provide detailed steps and recommended resources." The input data is the information acquired from the database and emotional information, and the output data is the generated response.

[1336] Step 7:

[1337] The server encrypts the generated response and sends it to the terminal. The input data is the generated response information, and the output data is the encrypted response data.

[1338] Step 8:

[1339] The terminal receives the encrypted response data, decrypts it, and displays it to the user. The user reviews the displayed response and, if necessary, asks additional questions or confirmations. Once this process is complete, the terminal returns to the next step. The input data is the encrypted data received from the server, and the output data is the decrypted response information.

[1340] In this way, each step works together, allowing users to obtain accurate and prompt information and receive individualized, specific support in real time.

[1341] (Application example 2)

[1342] 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."

[1343] In recent years, the use of online shopping sites has increased, and users often have trouble gathering information and making decisions when considering a purchase. However, current systems have difficulty providing quick and appropriate advice to address specific questions and concerns users have. Therefore, there is a need for support systems that allow users to make purchasing decisions with peace of mind. In particular, the realization of a system that can respond appropriately to users' emotions is an urgent issue.

[1344] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1345] In this invention, the server includes interface means for the user to input information, means for transmitting the information input by the user to the server, natural language processing means for the server to analyze the information input by the user, means for the server to search a database for appropriate information based on the analysis results, means for the server to generate the searched information and respond to the user, means for the user to check the generated response and input additional information, emotion engine means for adjusting the response content based on emotion analysis, interface means for the user to input questions and concerns about products, and generative AI model means for the server to provide information related to the user's purchasing behavior in real time. This allows the user to receive appropriate support when they have concerns or worries about a purchase, allowing them to make decisions with peace of mind.

[1346] "Interface means for users to input information" refers to a screen or input device used by users to input questions or concerns.

[1347] "Means for transmitting information entered by the user to the server" refers to the mechanism by which information entered by the user from the terminal is transmitted to the server.

[1348] "Natural language processing means for the server to analyze the user's input information" refers to technology that allows the server to understand the user's input text and analyze its intent and content.

[1349] "Means for the server to search for appropriate information from a database based on the analysis results" refers to a mechanism by which the server searches for relevant information from a database based on the analysis results.

[1350] "Means for the server to generate the searched information and respond to the user" refers to the mechanism by which the server generates an appropriate response based on the information retrieved from the database and returns it to the user.

[1351] "Means for the user to review the generated response and enter additional information" means a mechanism that allows the user to view the response from the server and enter further questions or additional information.

[1352] "Emotion engine means for adjusting response content based on emotion analysis" refers to technology for analyzing emotions from user input and adjusting the content and tone of the response.

[1353] "Interface means for users to input product-related questions and concerns" refers to a screen or input device designed to make it easy for users to input product-related inquiries.

[1354] "Generative AI model means by which a server provides information related to a user's purchasing behavior in real time" refers to an artificial intelligence model that generates related information based on a user's purchasing behavior and presents it in real time.

[1355] The present invention relates to a system that quickly provides appropriate information and emotional support to users in response to questions or concerns they may have when considering a purchase on an online shopping site. The system includes a user interface, a server, a natural language processing system, a database, an information generation system, an emotion engine, and a generative AI model system.

[1356] Specifically, user interface means include smartphone applications and web interfaces through which users can input questions or concerns about products.

[1357] The server receives the information entered by the user and analyzes the text information using natural language processing means. This analysis process utilizes machine learning libraries such as TensorFlow. Based on the analysis results, the server searches for appropriate information from a database. The searched information is then generated in a form appropriate for the user by information generation means.

[1358] The emotion engine uses an emotion analysis tool such as IBM Watson's Tone Analyzer to extract emotions from user input. For example, if a user inputs, "I'm thinking about whether to purchase this product. I'm worried about the reviews," the emotion engine will recognize the emotion as "anxiety." Based on this recognition, the server will adjust the content and tone of the response and provide appropriate advice to the user.

[1359] The generative AI modeling method provides real-time information related to a user's purchasing behavior, including techniques to provide the most relevant information to the user based on their past purchase history and responses to similar questions.

[1360] For example, if a user inputs a question such as, "I'm thinking about whether to purchase this product. I'm worried about the reviews," the system generates a response using the following steps. First, the natural language processing means extracts the keywords "product," "purchase," "concern," and "review," and then the emotion engine recognizes the emotion "anxiety." Next, related product review information and advice for considering the purchase are retrieved from the database. Finally, the generative AI model means references the user's past purchase history and the behavior of other users to generate the optimal response in real time and present it to the user.

[1361] In this way, users can eliminate any concerns about purchasing products and make decisions with peace of mind.

[1362] Examples and prompts

[1363] As a concrete example, when a user enters the question, "I'm wondering whether to purchase this product. I'm worried about the reviews," the system generates the following response:

[1364] Example prompt sentence:

[1365] If a user types in a question like, "I'm not sure whether to buy this product or not. I'm worried about the reviews," how would an assistant app based on this invention respond?

[1366] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1367] Step 1:

[1368] The user enters information.

[1369] Users input questions or concerns about products through smartphone applications or web interfaces, often entering text such as "I'm thinking about whether to purchase this product. I'm worried about the reviews." The input information is sent to a server via the device.

[1370] Step 2:

[1371] The server receives the user's input and performs natural language processing.

[1372] The server receives the user's input information sent from the device. It then uses machine learning libraries such as TensorFlow to analyze the input text. Specifically, the server extracts keywords such as "product," "purchase," "problem," and "review" to understand the user's intent. The results of this analysis are passed to the next step.

[1373] Step 3:

[1374] The server performs sentiment analysis.

[1375] The server uses IBM Watson's Tone Analyzer to extract emotions from the user's input text. For example, it recognizes the emotion "anxiety" from the input text "I'm thinking about whether to buy this product. I'm worried about the reviews." The results of the emotion analysis are passed to the next step.

[1376] Step 4:

[1377] The server searches the database based on the analysis results.

[1378] The server uses the results of natural language processing and sentiment analysis to search for relevant information from a database, such as product reviews or purchasing advice, to find information that best suits the user's question. The search results are then passed on to the next step.

[1379] Step 5:

[1380] The server generates the appropriate information and responds to the user.

[1381] The server uses a generative AI model to generate an appropriate response based on the search results retrieved from the database. It also takes into account the user's past purchase history and other users' responses to similar questions. For example, it generates a response such as, "Here are some reviews from other users of this product. We also recommend that you double-check the return policy if you have any concerns."

[1382] Step 6:

[1383] The server sends the response to the user's device.

[1384] The generated response is encrypted and sent using the HTTPS protocol to the user's device, where the user can view the response, and then provide further questions or confirmations.

[1385] Step 7:

[1386] The user reviews the generated response and enters additional information.

[1387] The user can review the server's response and re-enter any questions or additional information they have. This continuous interaction allows the user to gain more information and make a more confident purchasing decision.

[1388] Examples:

[1389] For example, if a user types in the question "I'm not sure whether to buy this product or not, and I'm worried about the reviews," the steps above will be followed to generate the following specific response:

[1390] Example prompt sentence:

[1391] If a user types in a question like, "I'm not sure whether to buy this product or not. I'm worried about the reviews," how would an assistant app based on this invention respond?

[1392] 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.

[1393] 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.

[1394] 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.

[1395] 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.

[1396] 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.

[1397] 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.

[1398] 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).

[1399] 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.

[1400] 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."

[1401] 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.

[1402] 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).

[1403] 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.

[1404] 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.

[1405] 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.

[1406] 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.

[1407] 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.

[1408] 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.

[1409] 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.

[1410] 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.

[1411] 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.

[1412] 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.

[1413] The following is further disclosed regarding the above embodiment.

[1414] (Claim 1)

[1415] an interface means for a user to input information;

[1416] means for transmitting information entered by the user to a server;

[1417] a natural language processing means for the server to analyze the user's input information;

[1418] A means for the server to search for appropriate information from a database based on the analysis results;

[1419] means for the server to generate the retrieved information and respond to the user;

[1420] The system includes a means for the user to review the generated response and enter additional information.

[1421] (Claim 2)

[1422] 2. The system according to claim 1, further comprising means for analyzing and providing information specifically when the user's input information relates to a method for creating a will.

[1423] (Claim 3)

[1424] 10. The system of claim 1, further comprising means for securely transmitting and receiving data using the HTTPS protocol.

[1425] "Example 1"

[1426] (Claim 1)

[1427] an input means for a user to input information;

[1428] A means for data transmission of information entered by a user;

[1429] natural language processing means for the information processing device to analyze information input by a user;

[1430] A means for the information processing device to search for appropriate information from an information storage device based on the analysis result;

[1431] an information generating means for generating information searched by the information processing device and responding to the user;

[1432] input means for a user to review the generated response and enter additional information;

[1433] Secure communication means for securely sending and receiving information

[1434] A system including:

[1435] (Claim 2)

[1436] The system according to claim 1, further comprising means for analyzing and providing information specifically when the information input by the user is related to end-of-life planning.

[1437] (Claim 3)

[1438] 10. The system of claim 1, further comprising means for using the generative model as a natural language processing means.

[1439] "Application Example 1"

[1440] (Claim 1)

[1441] an interface means for a user to input information;

[1442] means for transmitting information entered by a user to a server;

[1443] a natural language processing means for the server to analyze the user's input information;

[1444] A means for the server to search for appropriate information from a database based on the analysis results;

[1445] an information generating means for generating the information searched by the server and responding to the user;

[1446] a response validation means for allowing a user to validate the generated response and enter additional information;

[1447] a means to provide information on logistics center efficiency and operating procedures;

[1448] A system that includes a communication means for securely transmitting and receiving data.

[1449] (Claim 2)

[1450] 2. The system according to claim 1, further comprising means for analyzing and providing information specifically when the information input by the user relates to work efficiency, inventory management, and picking routes within the logistics center.

[1451] (Claim 3)

[1452] 10. The system of claim 1, further comprising means for securely transmitting and receiving data using the HTTPS protocol.

[1453] "Example 2: Combining Emotion Engines"

[1454] (Claim 1)

[1455] an interface means for a user to input information;

[1456] means for transmitting information entered by the user to a server;

[1457] a natural language processing means for the server to analyze the user's input information;

[1458] A means for the server to search for appropriate information from a database based on the analysis results;

[1459] An emotion recognition means for the server to analyze the emotion of the user;

[1460] means for the server to generate an emotion-sensitive response and respond to the user;

[1461] The system includes a means for the user to review the generated response and enter additional information.

[1462] (Claim 2)

[1463] 2. The system according to claim 1, further comprising means for analyzing and providing information specifically when the user's input information relates to a method for creating a will.

[1464] (Claim 3)

[1465] 10. The system of claim 1, further comprising means for encrypting the secure transmission and reception of data.

[1466] "Application example 2 when combining emotion engines"

[1467] (Claim 1)

[1468] an interface means for a user to input information;

[1469] means for transmitting information entered by the user to a server;

[1470] a natural language processing means for the server to analyze the user's input information;

[1471] A means for the server to search for appropriate information from a database based on the analysis results;

[1472] means for the server to generate the retrieved information and respond to the user;

[1473] a means for the user to review the generated response and enter additional information;

[1474] an emotion engine means for adjusting response content based on emotion analysis;

[1475] An interface means for users to input questions or concerns about the product;

[1476] The system includes a generative AI model means whereby a server provides information related to user purchasing behavior in real time.

[1477] (Claim 2)

[1478] 2. The system according to claim 1, further comprising means for analyzing and providing information specifically when the information input by the user is related to a product purchase.

[1479] (Claim 3)

[1480] 10. The system of claim 1, further comprising means for securely transmitting and receiving data using the HTTPS protocol. [Explanation of symbols]

[1481] 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. an interface means for a user to input information; means for transmitting information entered by the user to a server; a natural language processing means for the server to analyze the user's input information; A means for the server to search for appropriate information from a database based on the analysis results; means for the server to generate the retrieved information and respond to the user; The system includes a means for the user to review the generated response and enter additional information.

2. 2. The system according to claim 1, further comprising means for analyzing and providing information specifically when the information input by the user relates to a method for creating a will.

3. 10. The system of claim 1, further comprising means for securely transmitting and receiving data using the HTTPS protocol.

Images