system

Abstract

To provide a system that enables a user to quickly obtain necessary information. [Solution] The specific processing unit 290 of the data processing device 12 in the system performs an input process for the user to input specific needs and requirements, a transmission process for sending the input needs and requirements to a server, an analysis process for analyzing the received needs and requirements, a search process for searching for related solution information based on the analysis results, a generation process for generating optimal solution proposals from the search results, and a display process for displaying the generated proposals to the user.

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] Conventional solution proposal systems have made it difficult for users to quickly obtain the information they need, and have faced the problem of requiring a great deal of time and effort to find the appropriate information from vast amounts of documents and databases, particularly in workplaces where increased work efficiency is required. Furthermore, it has been difficult to provide appropriate solutions to meet the diverse needs and requirements of users, resulting in the inability to optimize the entire business process. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means. First, an input means is provided for the user to input specific needs and requirements. This input means allows the user to input detailed information about the solution they are looking for. Next, a transmission means is provided for transmitting the input needs and requirements to a server. Using analysis means for analyzing the needs and requirements received by the server, an AI analyzes the input content and extracts keywords and conditions. A search means searches for related solution information based on the analysis results to find appropriate solution information within the server or from external resources. Next, a generation means is used to generate optimal solution proposals from the search results, and specific proposals for the user are organized. Finally, a display means is provided to display the generated proposals to the user, thereby realizing a system that quickly and accurately provides the solution information required by the user.

[0006] "Input means" is a device, software, or interface that allows a user to input specific needs or requirements into the system.

[0007] "Transmission means" refers to a device, software, or communication interface for transmitting input needs or requirements to a server.

[0008] "Analysis means" refers to a device, software, or algorithm that analyzes the needs and requirements received by the server and extracts keywords and conditions.

[0009] The "search means" is a device, software, or algorithm for searching for relevant solution information based on the keywords and conditions extracted by the analysis means.

[0010] "Generation means" refers to a device, software, or algorithm for generating optimal solution proposals based on search results.

[0011] A "display means" is a device, software, or interface for displaying generated suggestions to a user.

[0012] "Input Form" means an electronic form that allows a user to input specific needs or requirements and that constitutes part of the input means.

[0013] A "database" is a system, software, or collection of structured data that stores each solution information and allows a search means to obtain the required information. [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] System Overview

[0036] This invention relates to a system in which users input their specific needs and requirements, and AI analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, significantly improving work efficiency.

[0037] Specific operation of the system

[0038] This system consists of three main elements: the user, the terminal, and the server. The specific operation of each element is explained below.

[0039] User Operation

[0040] 1. Use of the input form

[0041] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup."

[0042] 2. Confirm your input

[0043] Users can review the input and make corrections or additions as necessary, allowing them to specify the conditions for the desired solution in detail.

[0044] Terminal handling

[0045] 1. Data transmission

[0046] The terminal sends the user's input information to the server, organized as data packets.

[0047] Server Processing

[0048] 1. Data Reception and Analysis

[0049] The server receives the data packets sent from the device and passes them to the AI ​​analysis engine.

[0050] The AI ​​analysis engine analyzes the incoming data and extracts keywords and conditions, such as "cloud-based," "data backup," "low cost," and "easy setup."

[0051] 2. Database Search

[0052] The server searches for relevant solution information from an internal database or external resources based on the keywords and conditions extracted by the analysis means.

[0053] For example, information such as "Amazon S3" and "Google (registered trademark) Drive" is identified as a "low-cost, easily configurable cloud-based data backup solution."

[0054] 3. Proposal Generation

[0055] The server generates optimal solution proposals for the user based on the search results, and the proposals are provided along with detailed information.

[0056] For example, specific recommendations such as "Amazon S3 - a cost-conscious, recommended cloud-based data backup solution" are generated.

[0057] View Suggestions

[0058] 1. Displaying the results

[0059] The device displays the proposed data sent from the server to the user, who can then review the proposal and take next steps to request more information or take specific actions.

[0060] For example, suggestions such as "Google Drive - easy to set up and convenient" are displayed, along with detailed documentation and links.

[0061] Specific Examples

[0062] As a concrete example, consider a user who needs a cloud-based data backup solution and is looking for a low-cost, easy-to-setup solution. The user enters their requirements, and the device sends the information to the server. The server uses an AI analysis engine to search the database for optimal solution information and generate a proposal. Finally, the device displays suggestions such as "Amazon S3" and "Google Drive" to the user, allowing the user to quickly find the optimal solution.

[0063] In this way, by using this system, users can efficiently obtain information and achieve greater work efficiency.

[0064] The processing flow will be explained below.

[0065] Step 1:

[0066] Users enter their needs and requirements using an input form.

[0067] The device presents the user with a form where they can enter details about the solution they are looking for, such as "cloud-based data backup," "low cost," and "easy setup."

[0068] Step 2:

[0069] The user checks the input information and makes corrections or additions as necessary.

[0070] The terminal displays a confirmation screen for the user to confirm the input, and the user can check whether the input needs and requirements are correct and make corrections or additions if necessary. For example, change "low cost" to "minimum cost."

[0071] Step 3:

[0072] The terminal transmits the input information to the server.

[0073] After the user confirms the input, the terminal sends the information organized as a data packet to the server, where the input conditions are included in the data packet.

[0074] Step 4:

[0075] The server receives the data packets and analyzes them using the analysis means.

[0076] The server receives data packets sent from the device and passes them to the AI ​​analysis engine. The AI ​​analysis engine analyzes the received data and extracts related keywords and conditions. For example, "cloud-based," "data backup," "low cost," and "easy setup" are extracted.

[0077] Step 5:

[0078] The server searches the database based on the analysis results.

[0079] The server searches for relevant solution information from internal databases or external resources based on the keywords and conditions extracted by the analysis means. For example, it finds information such as "Amazon S3," "Google Drive," and "MICROSOFT (registered trademark) ONEDRIVE (registered trademark)" as "low-cost, easy-to-configure cloud-based data backup solutions."

[0080] Step 6:

[0081] The server generates an optimal solution proposal.

[0082] The server generates optimal solution proposals for the user based on the information obtained by the search means. The generation means organizes and lists the detailed proposals for each solution. For example, it generates specific proposals such as "Amazon S3 - cost-conscious, easy to set up" and "Google Drive - convenient and easy to use."

[0083] Step 7:

[0084] The server transmits the generated proposal data to the terminal.

[0085] The server transmits the generated proposal data to the terminal so that the user can confirm it. The transmitting means transmits a data packet including the proposal content to the terminal.

[0086] Step 8:

[0087] The device displays the suggestions to the user.

[0088] The device receives the proposed data from the server and displays it to the user. The user can then review the proposed solution and view detailed information on the device screen. For example, the proposed solution might say, "Amazon S3 - A cost-effective, recommended cloud-based data backup solution."

[0089] In this way, each step ensures a smooth process from user input to the proposal of the optimal solution.

[0090] Example 1

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

[0092] In traditional systems, even when users input their specific needs and requirements, the process for connecting that information to the optimal solution is often inefficient. It also requires a lot of manual work and takes a long time to find the correct solution. This can lead to reduced operational efficiency and user dissatisfaction.

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

[0094] In this invention, the server includes input means for a user to input specific needs and requirements, transmission means for transmitting the input needs and requirements to the information processing device, analysis means for analyzing the received needs and requirements, search means for searching for related solution information based on the analysis results, generation means for generating optimal solution proposals from the search results, and display means for displaying the generated proposals to the user, thereby making it possible to quickly and accurately propose solutions based on the user's input.

[0095] "Input means" is a device or interface through which a user inputs their specific needs or requirements.

[0096] The "transmission means" is a device or protocol for transmitting input needs and requirements to an information processing device.

[0097] "Analysis means" is a device or software for analyzing received needs or requirements.

[0098] The "search means" is a device or software for searching for related solution information based on the analysis results.

[0099] The "generation means" is a device or software for generating optimal solution proposals from search results.

[0100] A "display means" is a device or interface for displaying generated suggestions to a user.

[0101] "Solution information" is information about solutions that address user needs and requirements.

[0102] A "storage device" is a data storage device for storing solution information.

[0103] System Overview

[0104] The present invention relates to a system that allows users to input specific needs and requirements, and an information processing device analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, significantly improving work efficiency.

[0105] Specific system configuration

[0106] This system consists of three main elements: users, terminals, and servers. The specific configuration and functions of each element are explained below.

[0107] User operations and devices

[0108] The user enters their needs and requirements using an input form on the device. The information is organized in JSON format and sent to the server via HTTPS. The device uses a form written in React that runs on a web browser.

[0109] Examples:

[0110] The user enters their requirements for "cloud-based data backup," "low cost," and "easy setup." Once they've completed the input, they press the "Submit" button.

[0111] Server Processing

[0112] The server receives the JSON data sent from the device. The received data is passed to an AI analysis engine, which converts the data into text format and begins analysis. The generative AI model used is, for example, GPT-3 (registered trademark) from OpenAI (registered trademark).

[0113] Examples:

[0114] An example of a prompt is as follows:

[0115] Please suggest the best solution for the following requirements:

[0116] Cloud-based data backup

[0117] Low cost

[0118] Easy to set up

[0119] The server searches for the best solution information from a database based on the analyzed keywords. In addition to the internal database, it utilizes external resources (e.g., APIs of cloud service providers).

[0120] The search results are generated as optimal solution recommendations. The recommendations are presented in a user-friendly format. An example recommendation might be, "Amazon S3 - A cost-conscious, recommended cloud-based data backup solution."

[0121] View Suggestions

[0122] The device receives the proposed data sent from the server and displays it to the user, providing detailed information and links so the user can easily take the next action.

[0123] Examples:

[0124] The content displayed on the terminal will be as follows:

[0125] Recommended solutions:

[0126] 1. Amazon S3 - A cost-effective and recommended cloud-based data backup solution.

[0127] [More details here]

[0128] 2. Google Drive - A convenient cloud-based data backup solution that's easy to set up.

[0129] [More details here]

[0130] In this way, the process from user input to server analysis and display on the terminal allows users to efficiently obtain information and improve work efficiency.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] System program processing flow

[0133] Step 1:

[0134] Users enter their needs and requirements into an input form on their device. For example, they might enter "cloud-based data backup," "low cost," and "easy setup." This input form is written in React and runs on a web browser, with the input data organized in JSON format.

[0135] Input: User needs and requirements (e.g., "cloud-based data backup," "low cost," "easy to set up")

[0136] Output: Cleaned JSON data

[0137] Step 2:

[0138] The device sends the entered JSON data to the server via HTTPS, and this communication is encrypted to ensure security.

[0139] Input: Organized JSON data

[0140] Output: JSON data sent to the server

[0141] Step 3:

[0142] The server receives the JSON data sent from the device. The received data is passed to an AI analysis engine and converted into text format. The generative AI model used here is, for example, OpenAI's GPT-3.

[0143] Input: JSON data received from the terminal

[0144] Output: Data converted to text format

[0145] Step 4:

[0146] The server inputs the converted data into text format into an AI analysis engine, which then analyzes the received text data and extracts important keywords and conditions.

[0147] Input: Data converted to text format (e.g., "Cloud-based data backup," "Low cost," "Easy to set up")

[0148] Output: Extracted keywords and conditions

[0149] Step 5:

[0150] The server searches for the best solution information from an internal database or external resources based on the extracted keywords and conditions, for example, by using a cloud service provider's API to find the relevant solution. This search includes filtering and ranking.

[0151] Input: Extracted keywords or conditions (e.g., "cloud-based," "low-cost," "easy to set up")

[0152] Output: Search results (list of optimal solution information)

[0153] Step 6:

[0154] The server generates optimal solution proposals based on the search results, including specific product or service names and features.

[0155] Input: Search results (list of best solution information)

[0156] Output: Generated recommendations (e.g., "Amazon S3 - Cost-sensitive and recommended cloud-based data backup solutions")

[0157] Step 7:

[0158] The device receives the proposed data sent from the server and displays it to the user, showing detailed information about the proposed solution and related links.

[0159] Input: Proposal data sent from the server

[0160] Output: The recommendation that will be displayed to the user (e.g., "Amazon S3 - A cost-sensitive and recommended cloud-based data backup solution")

[0161] This series of processing steps allows the user to obtain the optimal solution efficiently and quickly.

[0162] (Application example 1)

[0163] 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."

[0164] Conventional food delivery systems have the problem that users must individually search for the type of food they want, their budget, delivery time, etc., which is time-consuming. It is also difficult to quickly and accurately obtain information on the restaurant and menu that best matches the user's criteria. This situation often makes it difficult for users to easily find the food they want, resulting in inconvenience.

[0165] 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.

[0166] In this invention, the server includes input means for a user to input specific needs and requirements, transmission means for transmitting the input needs and requirements to the server, analysis means for analyzing the received needs and requirements, search means for searching for related solution information based on the analysis results, generation means for generating optimal solution proposals from the search results, display means for displaying the generated proposals to the user, and means for inputting conditions such as the user's food preferences, budget, and delivery time and suggesting optimal restaurants and dishes based on these conditions, thereby enabling users to quickly and accurately find dishes and restaurants that meet their desired conditions.

[0167] "User" means any individual or entity that uses the Service or System.

[0168] "Needs" are the demands and desires that users have for specific services or products.

[0169] "Requirements" are the conditions or criteria that a user must meet to meet a particular need.

[0170] "Input means" refers to a device or interface that allows a user to input their needs and requirements into the system.

[0171] "Transmission means" refers to the communication functions and protocols used to send data entered by the user to the server.

[0172] "Analysis means" refers to algorithms or programs for analyzing received needs and requirements and extracting relevant information.

[0173] "Search means" refers to the function of searching for related solutions and data from a database based on the information obtained by the analysis means.

[0174] "Generation means" refers to a function or program for creating optimal proposals based on the information obtained by the search means.

[0175] "Display means" refers to a display or interface for showing the generated suggestions to the user.

[0176] "Cooking preferences" refers to the user's preferences for specific ingredients, cooking methods, etc.

[0177] A "budget" refers to the funds or expenses that a user plans to allocate for purchases or uses.

[0178] "Delivery time" refers to the time it takes from placing an order to completing delivery.

[0179] A "restaurant" is a commercial establishment that serves food and beverages.

[0180] A "prompt" is text that provides instructions or information to a generative AI model.

[0181] MODE FOR CARRYING OUT THE INVENTION

[0182] This invention relates to a system in which a user inputs specific needs and requirements, and an AI analyzes the input content to generate optimal solution proposals. Specific embodiments for implementing this invention are described below.

[0183] System configuration

[0184] User

[0185] Users use a device such as a smartphone to input conditions such as specific food preferences, budget, and delivery time. For example, they can input detailed needs and requirements such as "I want spicy pizza," "under 2,000 yen," and "delivery within 45 minutes."

[0186] Terminal

[0187] The user's input information is sent to the server by the terminal (smartphone or tablet) via a transmission means. The terminal has the function of formatting the data into an appropriate format and sending it to the server as a data packet.

[0188] server

[0189] The server uses a generative AI model to analyze the received user needs and requirements. Specifically, it uses an AI analysis engine (e.g., OpenAI GPT-4 (registered trademark)) to extract search criteria. The analysis means searches a database for relevant restaurant and cuisine information based on the analyzed keywords and criteria. The server generates appropriate restaurant and menu suggestions based on the analysis results.

[0190] Database

[0191] The database stores data such as menu information, prices, delivery times, etc. The search function allows users to quickly extract information that matches their requirements.

[0192] Generate and view suggestions

[0193] The proposal generated on the server is sent to the user's terminal along with detailed information. The generating means generates an optimal solution (e.g., "Spicy pizza at a nearby pizza place - 1,800 yen"). The display means on the terminal allows the user to quickly and accurately check the proposal.

[0194] Natural language processing explanation

[0195] Specific names of hardware and software

[0196] Hardware: Smartphone, server (e.g., Amazon AWS (registered trademark))

[0197] Software: Generative AI models (e.g., OpenAI GPT-4), database systems

[0198] Data processing and calculation

[0199] 1. Data reception and analysis: The user enters their food preferences, budget, and delivery time into an input form on their smartphone and sends the information to the server.

[0200] 2. Data transmission: The terminal transmits data to the server by the transmission means.

[0201] 3. Data analysis: The AI ​​analysis engine on the server analyzes the data and searches the database for restaurant information that meets the criteria.

[0202] 4. Proposal generation: Using the generation method, the AI ​​generates optimal restaurant and menu suggestions and provides feedback to the user.

[0203] Adding specific examples

[0204] Specific examples

[0205] When a user types, "I want a spicy pizza that costs under 2,000 yen and can be delivered within 45 minutes," the AI ​​searches for nearby restaurants that meet the criteria and generates suggestions such as "Spicy pizza from Pizza Shop X - 1,800 yen."

[0206] Prompt Sentence Examples

[0207] The user entered the following criteria:

[0208] Cuisine: Pizza

[0209] Budget: Under 2000 yen

[0210] Delivery time: within 45 minutes

[0211] Specific requirements: Spicy

[0212] Based on this, please suggest the best restaurant and menu.

[0213] By implementing the present invention based on the above aspects, a user can quickly and accurately find food and restaurants that meet his or her desired conditions.

[0214] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0215] Step 1:

[0216] Users input criteria such as specific food preferences, budget, and delivery time into a form on their smartphone. For example, they enter detailed requirements such as "pizza," "under 2000 yen," "within 45 minutes," and "spicy." This input data is organized as a data packet in JSON format.

[0217] input:

[0218] Types of cuisine

[0219] budget

[0220] Delivery time

[0221] Specific requirements

[0222] output:

[0223] Organized data packets (e.g., JSON format)

[0224] Operation:

[0225] The user operates the input form on the smartphone and enters the required conditions.

[0226] Step 2:

[0227] The terminal sends the input data packet to the server using a communication protocol such as an HTTP POST request. At this time, the data entered in the input form is sent to the server appropriately.

[0228] input:

[0229] Reordered data packets (output of step 1)

[0230] output:

[0231] Data packets sent to the server

[0232] Operation:

[0233] The device formats the data appropriately and sends it to the server.

[0234] Step 3:

[0235] The server passes the received data packets to an analysis engine (e.g., a generative AI model). The analysis engine extracts important keywords and conditions based on the input data. For example, it might extract keywords such as "pizza," "under 2,000 yen," "within 45 minutes," and "spicy."

[0236] input:

[0237] Received data packets (output of step 2)

[0238] output:

[0239] Extracted keywords and conditions

[0240] Operation:

[0241] The server uses a generative AI model to analyze the input data and obtain important keywords and conditions.

[0242] Step 4:

[0243] The server searches the database for relevant restaurant and food information based on the keywords and conditions extracted by the analysis engine. For example, it searches for restaurants that meet the conditions "pizza," "under 2,000 yen," "within 45 minutes," and "spicy."

[0244] input:

[0245] Extracted keywords and conditions (output of Step 3)

[0246] output:

[0247] Restaurant and food information extracted from the database

[0248] Operation:

[0249] The server performs a database search and extracts information that matches the criteria.

[0250] Step 5:

[0251] The server generates optimal suggestions based on the search results. The generation means creates suggestions suitable for the user, such as "Spicy pizza from pizza shop Y - 1800 yen."

[0252] input:

[0253] Restaurant and dish information extracted from the database (output of step 4)

[0254] output:

[0255] Optimal proposal content

[0256] Operation:

[0257] The server puts together the best suggestions and generates the information to show to the user.

[0258] Step 6:

[0259] The generated suggestions are sent to the terminal and are fed back to the user via the display means. The user can check the suggestions and use them as a reference for deciding what to order.

[0260] input:

[0261] Optimal proposal (output of step 5)

[0262] output:

[0263] Displaying suggestions to users

[0264] Operation:

[0265] The server sends the generated proposals to the terminal, which displays them to the user.

[0266] As a result, users can quickly and accurately obtain suggestions for dishes and restaurants that meet their desired conditions.

[0267] 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.

[0268] System Overview

[0269] This invention combines an emotion engine with a system in which users input their specific needs and requirements, and AI analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, and by making proposals that take the user's emotions into consideration, it is possible to provide more appropriate and satisfying solutions.

[0270] Specific operation of the system

[0271] This system is composed of three main elements: the user, the device, and the server. By incorporating an emotion engine, it is possible to realize suggestions based on the user's emotional state. The specific operation of each element is explained below.

[0272] User Operation

[0273] 1. Use of the input form

[0274] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup."

[0275] 2. Confirm your input

[0276] Users can review the input and make corrections or additions as necessary, allowing them to specify the conditions for the desired solution in detail.

[0277] Terminal handling

[0278] 1. Data transmission

[0279] The terminal sends the user's input information to the server, organized as data packets.

[0280] 2. Emotional Engine Activation

[0281] The device sends the user's facial expression and voice data to the emotion engine, which analyzes the user's emotions. For example, it uses a camera and microphone to detect the user's smile, tone of voice, stress level, etc.

[0282] Server Processing

[0283] 1. Data Reception and Analysis

[0284] The server receives the data packets sent from the device and the emotion data from the emotion engine, and passes them to the AI ​​analysis engine.

[0285] An AI analytics engine analyzes the received data and extracts relevant keywords, conditions, and emotional states, such as "cloud-based," "data backup," "low cost," "easy to set up," and "high stress."

[0286] 2. Database Search

[0287] The server searches for relevant solution information from an internal database or external resources based on the keywords, conditions, and emotional data extracted by the analysis means.

[0288] For example, it detects information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-setup cloud-based data backup solutions."

[0289] 3. Proposal Generation

[0290] The server uses the generation means to generate optimal solution proposals for the user based on the search results and emotion data. For example, if the user is in a high stress state, the server will prioritize proposing easier and less time-consuming solutions.

[0291] It generates detailed proposals such as "Amazon S3 - cost-conscious, easy to set up" and "Google Drive - convenient and easy to use."

[0292] View Suggestions

[0293] 1. Displaying the results

[0294] The device displays the proposed data sent from the server to the user, who can then review the proposal and take next steps to request more information or take specific actions.

[0295] For example, suggestions like "Amazon S3 - A cost-effective, recommended cloud-based data backup solution" are displayed, along with detailed documentation and links.

[0296] Specific Examples

[0297] As a concrete example, consider a user who needs a "cloud-based data backup solution" and is looking for a solution that is low-cost and easy to set up. The user enters their requirements, and the device sends the information to the server. Then, an emotion engine recognizes the user's high stress level from their facial expressions and voice. The server uses an analysis engine to search a database for optimal solution information and generates suggestions that take the user's emotional state into account. Finally, the device displays suggestions such as "Amazon S3" and "Google Drive" to the user, allowing the user to quickly find the optimal solution.

[0298] In this way, by using this system, users can not only obtain information efficiently and achieve work efficiency, but also improve satisfaction through suggestions that take their emotional state into consideration.

[0299] The processing flow will be explained below.

[0300] Step 1:

[0301] Users enter their needs and requirements using an input form.

[0302] The device displays a form for users to enter details about the solution they are looking for, such as "cloud-based data backup," "low cost," and "easy setup."

[0303] Step 2:

[0304] The user checks the input information and makes corrections or additions as necessary.

[0305] The terminal displays a confirmation screen for the user to confirm the input, and the user can check whether the input needs and requirements are correct and make corrections or additions if necessary. For example, change "low cost" to "minimum cost."

[0306] Step 3:

[0307] The terminal transmits the input information to the server.

[0308] After the user confirms the input, the terminal sends the information organized as a data packet to the server, where the input conditions are included in the data packet.

[0309] Step 4:

[0310] The device sends the user's facial expressions and voice data to an emotion engine to recognize the user's emotions.

[0311] The device sends the user's facial expressions and voice via a camera and microphone to the emotion engine, which then analyzes the user's emotional state. For example, it examines smiles, tone of voice, and stress levels, and recognizes them as "high stress."

[0312] Step 5:

[0313] The server receives the data packets and analyzes them using the analysis means.

[0314] The server receives the data packets and emotion data sent from the device and passes them to the AI ​​analysis engine. The AI ​​analysis engine analyzes the received data and extracts related keywords and conditions, such as "cloud-based," "data backup," "low cost," "easy to set up," and "high stress."

[0315] Step 6:

[0316] Based on the analysis results, the server searches for solution information from resources inside and outside the database.

[0317] The server searches for relevant solution information from an internal database or external resources based on the keywords, conditions, and sentiment data extracted by the analysis method. For example, it searches for information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-configure cloud-based data backup solutions."

[0318] Step 7:

[0319] The server generates an optimal solution proposal.

[0320] The server generates optimal solution suggestions for the user based on the acquired information and emotional data. For example, if the user is in a high-stress state, it will prioritize solutions that are easier and less time-consuming. It generates detailed suggestions such as "Amazon S3 - cost-conscious, easy to set up" or "Google Drive - convenient and easy to use."

[0321] Step 8:

[0322] The server transmits the generated proposal data to the terminal.

[0323] The server transmits the generated proposal data to the terminal so that the user can confirm it. The transmitting means transmits a data packet including the proposal content to the terminal.

[0324] Step 9:

[0325] The device displays the suggestions to the user.

[0326] The device receives the proposed data from the server and displays it to the user. The user can then review the proposed solution and view detailed information on the device screen. For example, the device may display a suggestion such as "Amazon S3 - A cost-effective, recommended cloud-based data backup solution," along with detailed documentation and links.

[0327] In this way, each step ensures a smooth process from user input to the proposal of the optimal solution. In addition, by combining it with an emotion engine, it is possible to make more appropriate proposals that take into account the user's emotional state.

[0328] Example 2

[0329] 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."

[0330] In conventional systems, users can input their specific needs and requirements and then propose optimal solutions based on the results. However, proposals are often made without taking into account the user's emotional state. This can leave users feeling stressed or dissatisfied, and there are issues with the quality of proposals and satisfaction not being sufficiently improved.

[0331] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes an input means for the user to input specific needs and requirements, a transmission means for transmitting the input needs and requirements to the server, an emotion analysis means for analyzing the emotional state of the user on the terminal, an analysis means for analyzing the received needs, requirements, and emotional state, a search means for searching for related solution information based on the analysis results, a generation means for generating an optimal solution proposal taking into account the search results and the user's emotional state, and a display means for displaying the generated proposal to the user. This makes it possible to propose an appropriate solution according to the user's emotional state, thereby improving user satisfaction.

[0332] "Input means" is an interface through which a user inputs their specific needs and requirements.

[0333] "Transmission means" is a function for transmitting input needs and requirements to a server.

[0334] The "emotion analysis means" is a function for analyzing the user's emotional state from facial expressions, voice, etc.

[0335] "Analysis means" is a device or software for analyzing received needs, requirements and emotional states.

[0336] The "search means" is a function for searching for related solution information based on the analysis results.

[0337] The "generation means" is a function for generating optimal solution proposals taking into account the search results and the emotional state of the user.

[0338] The "display means" is an interface for displaying the generated solution proposal to the user.

[0339] A "server" is a computer device that receives user needs, requirements, and emotional data, analyzes, searches, and generates suggestions.

[0340] A "terminal" is a device that a user uses to input their needs and requirements and analyze emotional data.

[0341] This invention combines an emotion engine with a system in which a user inputs specific needs and requirements, and a server analyzes those needs and requirements to generate optimal solution proposals. Specifically, it consists of three main elements: the user, the terminal, and the server.

[0342] User Operation

[0343] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup." They can then review their input and make corrections or additions if necessary. The more accurate and detailed this information is, the more likely it is that the optimal solution will be suggested.

[0344] Terminal handling

[0345] The device organizes the user's input information into data packets and sends them to the server. Communication protocols such as HTTP POST requests are used for data transmission. Furthermore, the device uses an emotion engine to collect the user's facial expressions and voice data and analyze their emotional state. Specifically, the device collects data using the built-in camera and microphone, and analyzes it using an emotion recognition API (e.g., a general emotion recognition platform).

[0346] Server Processing

[0347] The server receives the data packets and sentiment analysis data sent from the device and passes them to the analysis engine. The analysis engine uses an NLP library (e.g., a general natural language processing library) to extract relevant keywords, conditions, and emotional states from the received data. Next, a search function runs to search for relevant solution information based on the analysis results. SQL queries and API calls are used for database searches.

[0348] The server then generates optimal solution proposals based on the search results and the user's emotional state. A template engine (e.g., a general template engine) is used to generate the proposals, forming specific proposal content. If the user is in a high-stress state, easier and less time-consuming solutions are prioritized.

[0349] View Suggestions

[0350] The device receives the recommendations sent from the server and displays them to the user, either as a web browser widget or a dedicated application. The user can review the recommendations and select next steps for more information or specific actions. For example, a recommendation might be "Amazon S3 - a cost-conscious, recommended cloud-based data backup solution," with corresponding detailed documentation and links provided.

[0351] Examples and prompts

[0352] As a concrete example, consider a situation where a user in need of a "cloud-based data backup solution" is looking for a solution that is low-cost and easy to set up. The user enters their requirements, and the device sends that information to the server. An emotion engine then recognizes the user's high stress level from their facial expressions and voice. The server uses an analysis engine to search a database for optimal solution information and generates suggestions that take the user's emotional state into account. Finally, the device displays suggestions such as "general cloud storage services" to the user, allowing the user to quickly find the optimal solution.

[0353] Example prompt sentence:

[0354] Generate a proposal for a high-stress user looking for a cloud-based data backup solution that is low-cost and easy to set up.

[0355] By using this system, users can not only obtain information efficiently and achieve work efficiency, but also improve satisfaction through suggestions that take their emotional state into account.

[0356] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0357] Step 1:

[0358] The user enters their needs and requirements using an input form displayed on the device. The input information includes "cloud-based data backup," "low cost," and "easy setup." This clearly defines the user's requirements. For example, if a user enters "low cost, easy setup cloud storage," the requirement is recorded as data.

[0359] Step 2:

[0360] The user checks the input and makes corrections or additions as necessary. The input in this step is a review and correction of the information entered in the previous step. For example, by changing "low cost" to "annual cost less than $100," more specific requirements are determined. This checked and corrected data is passed to the next step as the final output.

[0361] Step 3:

[0362] The device sends the organized user input information to the server, formatted as a data packet in JSON or XML format. For example, a requirement for "low-cost cloud-based data backup" is sent to the server using an HTTP POST request. The input in this step is the user's requirement information, and the output is a data packet sent to the server.

[0363] Step 4:

[0364] At the same time, the device starts an emotion engine, collecting and analyzing the user's facial expressions and voice data. The data is captured using a camera and microphone, and analyzed using an emotion recognition API (e.g., a general emotion recognition platform). The analysis result is an emotional state such as "high stress" or "moderate." This analyzed emotion data is also sent to the server. The input is the original emotional state data, and the output is the analyzed emotion data.

[0365] Step 5:

[0366] The server receives data packets and emotional data sent from the device and passes them to the AI ​​analysis engine. The received data is in JSON or XML format and is fed to the analysis engine. For example, an NLP library (e.g., a general natural language processing library) is used to extract keywords and conditions such as "cloud-based," "low cost," and "easily configurable," as well as the emotional state ("high stress"). The input of this step is the user's requirements and emotional data, and the output is the extracted keywords and emotional state.

[0367] Step 6:

[0368] The server searches for relevant solution information from databases and external resources based on the analyzed keywords, conditions, and sentiment data. It uses SQL queries and API calls to retrieve entries containing, for example, "low-cost, easy-to-configure cloud backup solutions." The input is the analysis results, and the output is the searched solution information.

[0369] Step 7:

[0370] The server uses a template engine (e.g., a general template engine) to generate optimal solution proposals based on the search results and sentiment data. For example, it generates proposals such as "Amazon S3 - cost-effective and easy to set up" and "Google Drive - convenient and easy to use." Since the user is in a high-stress state at this time, it prioritizes simpler solutions. The generated proposals are formatted in a format appropriate for the user. The inputs are search results and sentiment data, and the output is the generated proposal text.

[0371] Step 8:

[0372] The terminal receives the generated recommendation data from the server and displays it to the user. The display format can be a web browser widget or a dedicated application. For example, the recommendation content may be "Amazon S3 - A cost-conscious, recommended cloud-based data backup solution" and provide a link to more information. The input is the generated recommendation text, and the output is a visual display to the user.

[0373] Through these processing steps, users are efficiently offered solutions that meet their requirements and can achieve higher satisfaction because the suggestions take into account the user's emotional state.

[0374] (Application example 2)

[0375] 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."

[0376] Conventional solution proposal systems were able to make optimal proposals based on the user's needs and requirements, but they were unable to take the user's emotional state into consideration. As a result, they were unable to make proposals that were optimized for the user's psychological state, such as high stress or relaxed state, which led to a problem of reduced user satisfaction.

[0377] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion analysis means for analyzing the user's emotions, means for adjusting the solution proposal based on the emotion analysis results, and analysis means for analyzing the received needs and requirements. This makes it possible to propose an optimal solution based on the user's emotional state.

[0378] "Input means" refers to the means by which a user inputs their specific needs and requirements.

[0379] The "transmission means" is a means for transmitting the input needs and requirements to the server.

[0380] "Analysis means" is a means for analyzing received needs and requirements.

[0381] The "search means" is a means for searching for related solution information based on the analysis results.

[0382] The "generation means" is a means for generating an optimal solution proposal from the search results.

[0383] The "display means" is a means for displaying the generated proposal to the user.

[0384] The "emotion analysis means" is a means for analyzing the user's emotions.

[0385] "Adjustment means" refers to a means for adjusting a solution proposal based on the results of sentiment analysis.

[0386] A "database" is a data storage device for storing information on each solution.

[0387] The present invention is a system that proposes optimal solutions taking into account the emotional state of the user. The system consists of the following main components:

[0388] 1. System Configuration

[0389] User Operation

[0390] The user uses the input means to input their specific needs and requirements. For example, they can input the genres and conditions they want to watch on the "content distribution service." Furthermore, a camera and microphone are used to collect facial expressions and voice data, and an emotion analysis means is used to analyze the user's emotions.

[0391] Terminal handling

[0392] The input means is used to collect needs and requirements from the user, which are then transmitted to the server by the transmission means. The collected facial expression and voice data is analyzed by the emotion analysis means and transmitted to the server as emotion data.

[0393] Server Processing

[0394] The server analyzes the needs and requirements data and emotion analysis data received by the transmission means using the analysis means. Based on the analysis results, related solution information is searched for using the search means. The searched information is generated as an optimal solution proposal by the generation means. An adjustment means adjusts the proposal content based on the emotion analysis data to generate a proposal that is optimal for the user's emotional state. In addition, each piece of solution information is stored in a database.

[0395] View Suggestions

[0396] The final solution proposal is displayed to the user using a display means, and the user can check the proposal, obtain more detailed information, or take specific actions.

[0397] 2. Working Example

[0398] For example, suppose a user wants to watch an "action movie" on a streaming service. The user inputs this request using the input means, and the input data is sent to the server. At the same time, an emotion analysis means using a camera and microphone analyzes the user's emotional state and determines, for example, that the user is in a "high stress state." Based on this, the server analyzes the received data using the analysis means and searches for information on related action movies using the search means.

[0399] Based on these search results, the generation means generates a suggestion of an action movie that will help the user relax. For example, instead of "action movies that get you excited," the generation means may adjust the suggestion to "action movies that are relaxing." The display means then displays the most suitable suggestion to the user. The user can then decide whether to watch the suggested movie.

[0400] In this way, using emotion analysis makes it possible to make suggestions that are tailored to the user's psychological state, thereby improving user satisfaction.

[0401] 3. Example prompts

[0402] For example, the following could be entered as a specific example of a prompt sentence for a generative AI model:

[0403] "If the user says they want to watch an action movie, and their current emotion is analyzed as high stress, generate recommendations for relaxing action movies based on this data."

[0404] The above is a specific embodiment of the present invention. This system makes it possible to propose optimal solutions according to the emotional state of the user.

[0405] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0406] Step 1:

[0407] The user uses an input means to input their specific needs or requirements. For example, the user may input a need such as "I want to watch an action movie," and the input data is captured by the terminal. The input acts as text data, which is used for further processing.

[0408] Step 2:

[0409] The terminal sends the input data of needs and requirements to the server. Using the transmission means, text data is sent to the server, and the server receives this data. The input data is packetized in JSON format and sent.

[0410] Step 3:

[0411] The device collects the user's facial expressions and voice data and analyzes their emotional state using emotion analysis means. Using a camera and microphone, the emotion engine analyzes the user's emotions based on the collected data. The analysis results in emotional states such as "high stress" and "relaxed."

[0412] Step 4:

[0413] The server uses an analysis means to analyze the needs and requirements data and emotion analysis data received from the terminal. The received text data and emotion data are passed to the analysis means, which extracts keywords from the input content and analyzes the emotional state.

[0414] Step 5:

[0415] Based on the keywords and emotion data extracted by the analysis means, the search means searches the database for related solution information. For example, a search is performed using the keywords "action movie" and "relaxation" to collect related information.

[0416] Step 6:

[0417] The server uses the generation means to generate optimal solution proposals based on the information collected by the search means. The generation means selects optimal solutions and constructs proposals based on the collected information and emotion data. For example, a list of "relaxing action movies" is generated.

[0418] Step 7:

[0419] The generated solution proposals are adapted to the sentiment analysis results using a tuning mechanism that further refines the proposals and restructures them to best suit the user's current emotional state.

[0420] Step 8:

[0421] The final proposal is sent from the server to the terminal and displayed to the user using the display means, allowing the user to visually confirm the proposal and decide on an action based on it.

[0422] These are the specific processing steps of the system that proposes optimal solutions based on the user's needs and emotional state.

[0423] 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.

[0424] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0425] 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.

[0426] [Second embodiment]

[0427] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] In the smart glasses 214, 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.

[0438] 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."

[0439] System Overview

[0440] This invention relates to a system in which users input their specific needs and requirements, and AI analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, significantly improving work efficiency.

[0441] Specific operation of the system

[0442] This system consists of three main elements: the user, the terminal, and the server. The specific operation of each element is explained below.

[0443] User Operation

[0444] 1. Use of the input form

[0445] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup."

[0446] 2. Confirm your input

[0447] Users can review the input and make corrections or additions as necessary, allowing them to specify the conditions for the desired solution in detail.

[0448] Terminal handling

[0449] 1. Data transmission

[0450] The terminal sends the user's input information to the server, organized as data packets.

[0451] Server Processing

[0452] 1. Data Reception and Analysis

[0453] The server receives the data packets sent from the device and passes them to the AI ​​analysis engine.

[0454] The AI ​​analysis engine analyzes the incoming data and extracts keywords and conditions, such as "cloud-based," "data backup," "low cost," and "easy setup."

[0455] 2. Database Search

[0456] The server searches for relevant solution information from an internal database or external resources based on the keywords and conditions extracted by the analysis means.

[0457] For example, information such as "Amazon S3" and "Google Drive" is identified as a "low-cost, easy-to-setup cloud-based data backup solution."

[0458] 3. Proposal Generation

[0459] The server generates optimal solution proposals for the user based on the search results, and the proposals are provided along with detailed information.

[0460] For example, specific recommendations such as "Amazon S3 - a cost-conscious, recommended cloud-based data backup solution" are generated.

[0461] View Suggestions

[0462] 1. Displaying the results

[0463] The device displays the proposed data sent from the server to the user, who can then review the proposal and take next steps to request more information or take specific actions.

[0464] For example, suggestions such as "Google Drive - easy to set up and convenient" are displayed, along with detailed documentation and links.

[0465] Specific Examples

[0466] As a concrete example, consider a user who needs a cloud-based data backup solution and is looking for a low-cost, easy-to-setup solution. The user enters their requirements, and the device sends the information to the server. The server uses an AI analysis engine to search the database for optimal solution information and generate a proposal. Finally, the device displays suggestions such as "Amazon S3" and "Google Drive" to the user, allowing the user to quickly find the optimal solution.

[0467] In this way, by using this system, users can efficiently obtain information and achieve greater work efficiency.

[0468] The processing flow will be explained below.

[0469] Step 1:

[0470] Users enter their needs and requirements using an input form.

[0471] The device presents the user with a form where they can enter details about the solution they are looking for, such as "cloud-based data backup," "low cost," and "easy setup."

[0472] Step 2:

[0473] The user checks the input information and makes corrections or additions as necessary.

[0474] The terminal displays a confirmation screen for the user to confirm the input, and the user can check whether the input needs and requirements are correct and make corrections or additions if necessary. For example, change "low cost" to "minimum cost."

[0475] Step 3:

[0476] The terminal transmits the input information to the server.

[0477] After the user confirms the input, the terminal sends the information organized as a data packet to the server, where the input conditions are included in the data packet.

[0478] Step 4:

[0479] The server receives the data packets and analyzes them using the analysis means.

[0480] The server receives data packets sent from the device and passes them to the AI ​​analysis engine. The AI ​​analysis engine analyzes the received data and extracts related keywords and conditions. For example, "cloud-based," "data backup," "low cost," and "easy setup" are extracted.

[0481] Step 5:

[0482] The server searches the database based on the analysis results.

[0483] The server searches for relevant solution information from internal databases or external resources based on keywords and conditions extracted by the analysis method. For example, it finds information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-configure cloud-based data backup solutions."

[0484] Step 6:

[0485] The server generates an optimal solution proposal.

[0486] The server generates optimal solution proposals for the user based on the information obtained by the search means. The generation means organizes and lists the detailed proposals for each solution. For example, it generates specific proposals such as "Amazon S3 - cost-conscious, easy to set up" and "Google Drive - convenient and easy to use."

[0487] Step 7:

[0488] The server transmits the generated proposal data to the terminal.

[0489] The server transmits the generated proposal data to the terminal so that the user can confirm it. The transmitting means transmits a data packet including the proposal content to the terminal.

[0490] Step 8:

[0491] The device displays the suggestions to the user.

[0492] The device receives the proposed data from the server and displays it to the user. The user can then review the proposed solution and view detailed information on the device screen. For example, the proposed solution might say, "Amazon S3 - A cost-effective, recommended cloud-based data backup solution."

[0493] In this way, each step ensures a smooth process from user input to the proposal of the optimal solution.

[0494] Example 1

[0495] 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."

[0496] In traditional systems, even when users input their specific needs and requirements, the process for connecting that information to the optimal solution is often inefficient. It also requires a lot of manual work and takes a long time to find the correct solution. This can lead to reduced operational efficiency and user dissatisfaction.

[0497] 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.

[0498] In this invention, the server includes input means for a user to input specific needs and requirements, transmission means for transmitting the input needs and requirements to the information processing device, analysis means for analyzing the received needs and requirements, search means for searching for related solution information based on the analysis results, generation means for generating optimal solution proposals from the search results, and display means for displaying the generated proposals to the user, thereby making it possible to quickly and accurately propose solutions based on the user's input.

[0499] "Input means" is a device or interface through which a user inputs their specific needs or requirements.

[0500] The "transmission means" is a device or protocol for transmitting input needs and requirements to an information processing device.

[0501] "Analysis means" is a device or software for analyzing received needs or requirements.

[0502] The "search means" is a device or software for searching for related solution information based on the analysis results.

[0503] The "generation means" is a device or software for generating optimal solution proposals from search results.

[0504] A "display means" is a device or interface for displaying generated suggestions to a user.

[0505] "Solution information" is information about solutions that address user needs and requirements.

[0506] A "storage device" is a data storage device for storing solution information.

[0507] System Overview

[0508] The present invention relates to a system that allows users to input specific needs and requirements, and an information processing device analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, significantly improving work efficiency.

[0509] Specific system configuration

[0510] This system consists of three main elements: users, terminals, and servers. The specific configuration and functions of each element are explained below.

[0511] User operations and devices

[0512] The user enters their needs and requirements using an input form on the device. The information is organized in JSON format and sent to the server via HTTPS. The device uses a form written in React that runs on a web browser.

[0513] Examples:

[0514] The user enters their requirements for "cloud-based data backup," "low cost," and "easy setup." Once they've completed the input, they press the "Submit" button.

[0515] Server Processing

[0516] The server receives the JSON data sent from the device. The received data is passed to an AI analysis engine, which converts the data into text format and begins analysis. The generative AI model used is, for example, OpenAI's GPT-3.

[0517] Examples:

[0518] An example of a prompt is as follows:

[0519] Please suggest the best solution for the following requirements:

[0520] Cloud-based data backup

[0521] Low cost

[0522] Easy to set up

[0523] The server searches for the best solution information from a database based on the analyzed keywords. In addition to the internal database, it utilizes external resources (e.g., APIs of cloud service providers).

[0524] The search results are generated as optimal solution recommendations. The recommendations are presented in a user-friendly format. An example recommendation might be, "Amazon S3 - A cost-conscious, recommended cloud-based data backup solution."

[0525] View Suggestions

[0526] The device receives the proposed data sent from the server and displays it to the user, providing detailed information and links so the user can easily take the next action.

[0527] Examples:

[0528] The content displayed on the terminal will be as follows:

[0529] Recommended solutions:

[0530] 1. Amazon S3 - A cost-effective and recommended cloud-based data backup solution.

[0531] [More details here]

[0532] 2. Google Drive - A convenient cloud-based data backup solution that's easy to set up.

[0533] [More details here]

[0534] In this way, the process from user input to server analysis and display on the terminal allows users to efficiently obtain information and improve work efficiency.

[0535] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0536] System program processing flow

[0537] Step 1:

[0538] Users enter their needs and requirements into an input form on their device. For example, they might enter "cloud-based data backup," "low cost," and "easy setup." This input form is written in React and runs on a web browser, with the input data organized in JSON format.

[0539] Input: User needs and requirements (e.g., "cloud-based data backup," "low cost," "easy to set up")

[0540] Output: Cleaned JSON data

[0541] Step 2:

[0542] The device sends the entered JSON data to the server via HTTPS, and this communication is encrypted to ensure security.

[0543] Input: Organized JSON data

[0544] Output: JSON data sent to the server

[0545] Step 3:

[0546] The server receives the JSON data sent from the device. The received data is passed to an AI analysis engine and converted into text format. The generative AI model used here is, for example, OpenAI's GPT-3.

[0547] Input: JSON data received from the terminal

[0548] Output: Data converted to text format

[0549] Step 4:

[0550] The server inputs the converted data into text format into an AI analysis engine, which then analyzes the received text data and extracts important keywords and conditions.

[0551] Input: Data converted to text format (e.g., "Cloud-based data backup," "Low cost," "Easy to set up")

[0552] Output: Extracted keywords and conditions

[0553] Step 5:

[0554] The server searches for the best solution information from an internal database or external resources based on the extracted keywords and conditions, for example, by using a cloud service provider's API to find the relevant solution. This search includes filtering and ranking.

[0555] Input: Extracted keywords or conditions (e.g., "cloud-based," "low-cost," "easy to set up")

[0556] Output: Search results (list of optimal solution information)

[0557] Step 6:

[0558] The server generates optimal solution proposals based on the search results, including specific product or service names and features.

[0559] Input: Search results (list of best solution information)

[0560] Output: Generated recommendations (e.g., "Amazon S3 - Cost-sensitive and recommended cloud-based data backup solutions")

[0561] Step 7:

[0562] The device receives the proposed data sent from the server and displays it to the user, showing detailed information about the proposed solution and related links.

[0563] Input: Proposal data sent from the server

[0564] Output: The recommendation that will be displayed to the user (e.g., "Amazon S3 - A cost-sensitive and recommended cloud-based data backup solution")

[0565] This series of processing steps allows the user to obtain the optimal solution efficiently and quickly.

[0566] (Application example 1)

[0567] 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."

[0568] Conventional food delivery systems have the problem that users must individually search for the type of food they want, their budget, delivery time, etc., which is time-consuming. It is also difficult to quickly and accurately obtain information on the restaurant and menu that best matches the user's criteria. This situation often makes it difficult for users to easily find the food they want, resulting in inconvenience.

[0569] 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.

[0570] In this invention, the server includes input means for a user to input specific needs and requirements, transmission means for transmitting the input needs and requirements to the server, analysis means for analyzing the received needs and requirements, search means for searching for related solution information based on the analysis results, generation means for generating optimal solution proposals from the search results, display means for displaying the generated proposals to the user, and means for inputting conditions such as the user's food preferences, budget, and delivery time and suggesting optimal restaurants and dishes based on these conditions, thereby enabling users to quickly and accurately find dishes and restaurants that meet their desired conditions.

[0571] "User" means any individual or entity that uses the Service or System.

[0572] "Needs" are the demands and desires that users have for specific services or products.

[0573] "Requirements" are the conditions or criteria that a user must meet to meet a particular need.

[0574] "Input means" refers to a device or interface that allows a user to input their needs and requirements into the system.

[0575] "Transmission means" refers to the communication functions and protocols used to send data entered by the user to the server.

[0576] "Analysis means" refers to algorithms or programs for analyzing received needs and requirements and extracting relevant information.

[0577] "Search means" refers to the function of searching for related solutions and data from a database based on the information obtained by the analysis means.

[0578] "Generation means" refers to a function or program for creating optimal proposals based on the information obtained by the search means.

[0579] "Display means" refers to a display or interface for showing the generated suggestions to the user.

[0580] "Cooking preferences" refers to the user's preferences for specific ingredients, cooking methods, etc.

[0581] A "budget" refers to the funds or expenses that a user plans to allocate for purchases or uses.

[0582] "Delivery time" refers to the time it takes from placing an order to completing delivery.

[0583] A "restaurant" is a commercial establishment that serves food and beverages.

[0584] A "prompt" is text that provides instructions or information to a generative AI model.

[0585] MODE FOR CARRYING OUT THE INVENTION

[0586] This invention relates to a system in which a user inputs specific needs and requirements, and an AI analyzes the input content to generate optimal solution proposals. Specific embodiments for implementing this invention are described below.

[0587] System configuration

[0588] User

[0589] Users use a device such as a smartphone to input conditions such as specific food preferences, budget, and delivery time. For example, they can input detailed needs and requirements such as "I want spicy pizza," "under 2,000 yen," and "delivery within 45 minutes."

[0590] Terminal

[0591] The user's input information is sent to the server by the terminal (smartphone or tablet) via a transmission means. The terminal has the function of formatting the data into an appropriate format and sending it to the server as a data packet.

[0592] server

[0593] The server uses a generative AI model to analyze the received user needs and requirements. Specifically, it uses an AI analysis engine (e.g., OpenAI GPT-4) to extract search criteria. The analysis means searches a database for relevant restaurant and cuisine information based on the analyzed keywords and criteria. The server generates appropriate restaurant and menu suggestions based on the analysis results.

[0594] Database

[0595] The database stores data such as menu information, prices, delivery times, etc. The search function allows users to quickly extract information that matches their requirements.

[0596] Generate and view suggestions

[0597] The proposal generated on the server is sent to the user's terminal along with detailed information. The generating means generates an optimal solution (e.g., "Spicy pizza at a nearby pizza place - 1,800 yen"). The display means on the terminal allows the user to quickly and accurately check the proposal.

[0598] Natural language processing explanation

[0599] Specific names of hardware and software

[0600] Hardware: Smartphones, servers (e.g., Amazon AWS)

[0601] Software: Generative AI models (e.g., OpenAI GPT-4), database systems

[0602] Data processing and calculation

[0603] 1. Data reception and analysis: The user enters their food preferences, budget, and delivery time into an input form on their smartphone and sends the information to the server.

[0604] 2. Data transmission: The terminal transmits data to the server by the transmission means.

[0605] 3. Data analysis: The AI ​​analysis engine on the server analyzes the data and searches the database for restaurant information that meets the criteria.

[0606] 4. Proposal generation: Using the generation method, the AI ​​generates optimal restaurant and menu suggestions and provides feedback to the user.

[0607] Adding specific examples

[0608] Specific examples

[0609] When a user types, "I want a spicy pizza that costs under 2,000 yen and can be delivered within 45 minutes," the AI ​​searches for nearby restaurants that meet the criteria and generates suggestions such as "Spicy pizza from Pizza Shop X - 1,800 yen."

[0610] Prompt Sentence Examples

[0611] The user entered the following criteria:

[0612] Cuisine: Pizza

[0613] Budget: Under 2000 yen

[0614] Delivery time: within 45 minutes

[0615] Specific requirements: Spicy

[0616] Based on this, please suggest the best restaurant and menu.

[0617] By implementing the present invention based on the above aspects, a user can quickly and accurately find food and restaurants that meet his or her desired conditions.

[0618] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0619] Step 1:

[0620] Users input criteria such as specific food preferences, budget, and delivery time into a form on their smartphone. For example, they enter detailed requirements such as "pizza," "under 2000 yen," "within 45 minutes," and "spicy." This input data is organized as a data packet in JSON format.

[0621] input:

[0622] Types of cuisine

[0623] budget

[0624] Delivery time

[0625] Specific requirements

[0626] output:

[0627] Organized data packets (e.g., JSON format)

[0628] Operation:

[0629] The user operates the input form on the smartphone and enters the required conditions.

[0630] Step 2:

[0631] The terminal sends the input data packet to the server using a communication protocol such as an HTTP POST request. At this time, the data entered in the input form is sent to the server appropriately.

[0632] input:

[0633] Reordered data packets (output of step 1)

[0634] output:

[0635] Data packets sent to the server

[0636] Operation:

[0637] The device formats the data appropriately and sends it to the server.

[0638] Step 3:

[0639] The server passes the received data packets to an analysis engine (e.g., a generative AI model). The analysis engine extracts important keywords and conditions based on the input data. For example, it might extract keywords such as "pizza," "under 2,000 yen," "within 45 minutes," and "spicy."

[0640] input:

[0641] Received data packets (output of step 2)

[0642] output:

[0643] Extracted keywords and conditions

[0644] Operation:

[0645] The server uses a generative AI model to analyze the input data and obtain important keywords and conditions.

[0646] Step 4:

[0647] The server searches the database for relevant restaurant and food information based on the keywords and conditions extracted by the analysis engine. For example, it searches for restaurants that meet the conditions "pizza," "under 2,000 yen," "within 45 minutes," and "spicy."

[0648] input:

[0649] Extracted keywords and conditions (output of Step 3)

[0650] output:

[0651] Restaurant and food information extracted from the database

[0652] Operation:

[0653] The server performs a database search and extracts information that matches the criteria.

[0654] Step 5:

[0655] The server generates optimal suggestions based on the search results. The generation means creates suggestions suitable for the user, such as "Spicy pizza from pizza shop Y - 1800 yen."

[0656] input:

[0657] Restaurant and dish information extracted from the database (output of step 4)

[0658] output:

[0659] Optimal proposal content

[0660] Operation:

[0661] The server puts together the best suggestions and generates the information to show the user.

[0662] Step 6:

[0663] The generated suggestions are sent to the terminal and are fed back to the user via the display means. The user can check the suggestions and use them as a reference for deciding what to order.

[0664] input:

[0665] Optimal proposal (output of step 5)

[0666] output:

[0667] Displaying suggestions to users

[0668] Operation:

[0669] The server sends the generated proposals to the terminal, which displays them to the user.

[0670] As a result, users can quickly and accurately obtain suggestions for dishes and restaurants that meet their desired conditions.

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

[0672] System Overview

[0673] This invention combines an emotion engine with a system in which users input their specific needs and requirements, and AI analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, and by making proposals that take the user's emotions into consideration, it is possible to provide more appropriate and satisfying solutions.

[0674] Specific operation of the system

[0675] This system is composed of three main elements: the user, the device, and the server. By incorporating an emotion engine, it is possible to realize suggestions based on the user's emotional state. The specific operation of each element is explained below.

[0676] User Operation

[0677] 1. Use of the input form

[0678] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup."

[0679] 2. Confirm your input

[0680] Users can review the input and make corrections or additions as necessary, allowing them to specify the conditions for the desired solution in detail.

[0681] Terminal handling

[0682] 1. Data transmission

[0683] The terminal sends the user's input information to the server, organized as data packets.

[0684] 2. Emotional Engine Activation

[0685] The device sends the user's facial expression and voice data to the emotion engine, which analyzes the user's emotions. For example, it uses a camera and microphone to detect the user's smile, tone of voice, stress level, etc.

[0686] Server Processing

[0687] 1. Data Reception and Analysis

[0688] The server receives the data packets sent from the device and the emotion data from the emotion engine, and passes them to the AI ​​analysis engine.

[0689] An AI analytics engine analyzes the received data and extracts relevant keywords, conditions, and emotional states, such as "cloud-based," "data backup," "low cost," "easy to set up," and "high stress."

[0690] 2. Database Search

[0691] The server searches for relevant solution information from an internal database or external resources based on the keywords, conditions, and emotional data extracted by the analysis means.

[0692] For example, it detects information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-setup cloud-based data backup solutions."

[0693] 3. Proposal Generation

[0694] The server uses the generation means to generate optimal solution proposals for the user based on the search results and emotion data. For example, if the user is in a high stress state, the server will prioritize proposing easier and less time-consuming solutions.

[0695] It generates detailed proposals such as "Amazon S3 - cost-conscious, easy to set up" and "Google Drive - convenient and easy to use."

[0696] View Suggestions

[0697] 1. Displaying the results

[0698] The device displays the proposed data sent from the server to the user, who can then review the proposal and take next steps to request more information or take specific actions.

[0699] For example, suggestions like "Amazon S3 - A cost-effective, recommended cloud-based data backup solution" are displayed, along with detailed documentation and links.

[0700] Specific Examples

[0701] As a concrete example, consider a user who needs a "cloud-based data backup solution" and is looking for a solution that is low-cost and easy to set up. The user enters their requirements, and the device sends the information to the server. Then, an emotion engine recognizes the user's high stress level from their facial expressions and voice. The server uses an analysis engine to search a database for optimal solution information and generates suggestions that take the user's emotional state into account. Finally, the device displays suggestions such as "Amazon S3" and "Google Drive" to the user, allowing the user to quickly find the optimal solution.

[0702] In this way, by using this system, users can not only obtain information efficiently and achieve work efficiency, but also improve satisfaction through suggestions that take their emotional state into consideration.

[0703] The processing flow will be explained below.

[0704] Step 1:

[0705] Users enter their needs and requirements using an input form.

[0706] The device displays a form for users to enter details about the solution they are looking for, such as "cloud-based data backup," "low cost," and "easy setup."

[0707] Step 2:

[0708] The user checks the input information and makes corrections or additions as necessary.

[0709] The terminal displays a confirmation screen for the user to confirm the input, and the user can check whether the input needs and requirements are correct and make corrections or additions if necessary. For example, change "low cost" to "minimum cost."

[0710] Step 3:

[0711] The terminal transmits the input information to the server.

[0712] After the user confirms the input, the terminal sends the information organized as a data packet to the server, where the input conditions are included in the data packet.

[0713] Step 4:

[0714] The device sends the user's facial expressions and voice data to an emotion engine to recognize the user's emotions.

[0715] The device sends the user's facial expressions and voice via a camera and microphone to the emotion engine, which then analyzes the user's emotional state. For example, it examines smiles, tone of voice, and stress levels, and recognizes them as "high stress."

[0716] Step 5:

[0717] The server receives the data packets and analyzes them using the analysis means.

[0718] The server receives the data packets and emotion data sent from the device and passes them to the AI ​​analysis engine. The AI ​​analysis engine analyzes the received data and extracts related keywords and conditions, such as "cloud-based," "data backup," "low cost," "easy to set up," and "high stress."

[0719] Step 6:

[0720] Based on the analysis results, the server searches for solution information from resources inside and outside the database.

[0721] The server searches for relevant solution information from an internal database or external resources based on the keywords, conditions, and sentiment data extracted by the analysis method. For example, it searches for information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-configure cloud-based data backup solutions."

[0722] Step 7:

[0723] The server generates an optimal solution proposal.

[0724] The server generates optimal solution suggestions for the user based on the acquired information and emotional data. For example, if the user is in a high-stress state, it will prioritize solutions that are easier and less time-consuming. It generates detailed suggestions such as "Amazon S3 - cost-conscious, easy to set up" or "Google Drive - convenient and easy to use."

[0725] Step 8:

[0726] The server transmits the generated proposal data to the terminal.

[0727] The server transmits the generated proposal data to the terminal so that the user can confirm it. The transmitting means transmits a data packet including the proposal content to the terminal.

[0728] Step 9:

[0729] The device displays the suggestions to the user.

[0730] The device receives the proposed data from the server and displays it to the user. The user can then review the proposed solution and view detailed information on the device screen. For example, the device may display a suggestion such as "Amazon S3 - A cost-effective, recommended cloud-based data backup solution," along with detailed documentation and links.

[0731] In this way, each step ensures a smooth process from user input to the proposal of the optimal solution. In addition, by combining it with an emotion engine, it is possible to make more appropriate proposals that take into account the user's emotional state.

[0732] Example 2

[0733] 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."

[0734] In conventional systems, users can input their specific needs and requirements and then propose optimal solutions based on the results. However, proposals are often made without taking into account the user's emotional state. This can leave users feeling stressed or dissatisfied, and there are issues with the quality of proposals and satisfaction not being sufficiently improved.

[0735] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes an input means for the user to input specific needs and requirements, a transmission means for transmitting the input needs and requirements to the server, an emotion analysis means for analyzing the emotional state of the user on the terminal, an analysis means for analyzing the received needs, requirements, and emotional state, a search means for searching for related solution information based on the analysis results, a generation means for generating an optimal solution proposal taking into account the search results and the user's emotional state, and a display means for displaying the generated proposal to the user. This makes it possible to propose an appropriate solution according to the user's emotional state, thereby improving user satisfaction.

[0736] "Input means" is an interface through which a user inputs their specific needs and requirements.

[0737] "Transmission means" is a function for transmitting input needs and requirements to a server.

[0738] The "emotion analysis means" is a function for analyzing the user's emotional state from facial expressions, voice, etc.

[0739] "Analysis means" is a device or software for analyzing received needs, requirements and emotional states.

[0740] The "search means" is a function for searching for related solution information based on the analysis results.

[0741] The "generation means" is a function for generating optimal solution proposals taking into account the search results and the emotional state of the user.

[0742] The "display means" is an interface for displaying the generated solution proposal to the user.

[0743] A "server" is a computer device that receives user needs, requirements, and emotional data, analyzes, searches, and generates suggestions.

[0744] A "terminal" is a device that a user uses to input their needs and requirements and analyze emotional data.

[0745] This invention combines an emotion engine with a system in which a user inputs specific needs and requirements, and a server analyzes those needs and requirements to generate optimal solution proposals. Specifically, it consists of three main elements: the user, the terminal, and the server.

[0746] User Operation

[0747] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup." They can then review their input and make corrections or additions if necessary. The more accurate and detailed this information is, the more likely it is that the optimal solution will be suggested.

[0748] Terminal handling

[0749] The device organizes the user's input information into data packets and sends them to the server. Communication protocols such as HTTP POST requests are used for data transmission. Furthermore, the device uses an emotion engine to collect the user's facial expressions and voice data and analyze their emotional state. Specifically, the device collects data using the built-in camera and microphone, and analyzes it using an emotion recognition API (e.g., a general emotion recognition platform).

[0750] Server Processing

[0751] The server receives the data packets and sentiment analysis data sent from the device and passes them to the analysis engine. The analysis engine uses an NLP library (e.g., a general natural language processing library) to extract relevant keywords, conditions, and emotional states from the received data. Next, a search function runs to search for relevant solution information based on the analysis results. SQL queries and API calls are used for database searches.

[0752] The server then generates optimal solution proposals based on the search results and the user's emotional state. A template engine (e.g., a general template engine) is used to generate the proposals, forming specific proposal content. If the user is in a high-stress state, easier and less time-consuming solutions are prioritized.

[0753] View Suggestions

[0754] The device receives the recommendations sent from the server and displays them to the user, either as a web browser widget or a dedicated application. The user can review the recommendations and select next steps for more information or specific actions. For example, a recommendation might be "Amazon S3 - a cost-conscious, recommended cloud-based data backup solution," with corresponding detailed documentation and links provided.

[0755] Examples and prompts

[0756] As a concrete example, consider a situation where a user in need of a "cloud-based data backup solution" is looking for a solution that is low-cost and easy to set up. The user enters their requirements, and the device sends that information to the server. An emotion engine then recognizes the user's high stress level from their facial expressions and voice. The server uses an analysis engine to search a database for optimal solution information and generates suggestions that take the user's emotional state into account. Finally, the device displays suggestions such as "general cloud storage services" to the user, allowing the user to quickly find the optimal solution.

[0757] Example prompt sentence:

[0758] Generate a proposal for a high-stress user looking for a cloud-based data backup solution that is low-cost and easy to set up.

[0759] By using this system, users can not only obtain information efficiently and achieve work efficiency, but also improve satisfaction through suggestions that take their emotional state into account.

[0760] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0761] Step 1:

[0762] The user enters their needs and requirements using an input form displayed on the device. The input information includes "cloud-based data backup," "low cost," and "easy setup." This clearly defines the user's requirements. For example, if a user enters "low cost, easy setup cloud storage," the requirement is recorded as data.

[0763] Step 2:

[0764] The user checks the input and makes corrections or additions as necessary. The input in this step is a review and correction of the information entered in the previous step. For example, by changing "low cost" to "annual cost less than $100," more specific requirements are determined. This checked and corrected data is passed to the next step as the final output.

[0765] Step 3:

[0766] The device sends the organized user input information to the server, formatted as a data packet in JSON or XML format. For example, a requirement for "low-cost cloud-based data backup" is sent to the server using an HTTP POST request. The input in this step is the user's requirement information, and the output is a data packet sent to the server.

[0767] Step 4:

[0768] At the same time, the device starts an emotion engine, collecting and analyzing the user's facial expressions and voice data. The data is captured using a camera and microphone, and analyzed using an emotion recognition API (e.g., a general emotion recognition platform). The analysis result is an emotional state such as "high stress" or "moderate." This analyzed emotion data is also sent to the server. The input is the original emotional state data, and the output is the analyzed emotion data.

[0769] Step 5:

[0770] The server receives data packets and emotional data sent from the device and passes them to the AI ​​analysis engine. The received data is in JSON or XML format and is fed to the analysis engine. For example, an NLP library (e.g., a general natural language processing library) is used to extract keywords and conditions such as "cloud-based," "low cost," and "easily configurable," as well as the emotional state ("high stress"). The input of this step is the user's requirements and emotional data, and the output is the extracted keywords and emotional state.

[0771] Step 6:

[0772] The server searches for relevant solution information from databases and external resources based on the analyzed keywords, conditions, and sentiment data. It uses SQL queries and API calls to retrieve entries containing, for example, "low-cost, easy-to-configure cloud backup solutions." The input is the analysis results, and the output is the searched solution information.

[0773] Step 7:

[0774] The server uses a template engine (e.g., a general template engine) to generate optimal solution proposals based on the search results and sentiment data. For example, it generates proposals such as "Amazon S3 - cost-effective and easy to set up" and "Google Drive - convenient and easy to use." Since the user is in a high-stress state at this time, it prioritizes simpler solutions. The generated proposals are formatted in a format appropriate for the user. The inputs are search results and sentiment data, and the output is the generated proposal text.

[0775] Step 8:

[0776] The terminal receives the generated recommendation data from the server and displays it to the user. The display format can be a web browser widget or a dedicated application. For example, the recommendation content may be "Amazon S3 - A cost-conscious, recommended cloud-based data backup solution" and provide a link to more information. The input is the generated recommendation text, and the output is a visual display to the user.

[0777] Through these processing steps, users are efficiently offered solutions that meet their requirements and can achieve higher satisfaction because the suggestions take into account the user's emotional state.

[0778] (Application example 2)

[0779] 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."

[0780] Conventional solution proposal systems were able to make optimal proposals based on the user's needs and requirements, but they were unable to take the user's emotional state into consideration. As a result, they were unable to make proposals that were optimized for the user's psychological state, such as high stress or relaxed state, which led to a problem of reduced user satisfaction.

[0781] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion analysis means for analyzing the user's emotions, means for adjusting the solution proposal based on the emotion analysis results, and analysis means for analyzing the received needs and requirements. This makes it possible to propose an optimal solution based on the user's emotional state.

[0782] "Input means" refers to the means by which a user inputs their specific needs and requirements.

[0783] The "transmission means" is a means for transmitting the input needs and requirements to the server.

[0784] "Analysis means" is a means for analyzing received needs and requirements.

[0785] The "search means" is a means for searching for related solution information based on the analysis results.

[0786] The "generation means" is a means for generating an optimal solution proposal from the search results.

[0787] The "display means" is a means for displaying the generated proposal to the user.

[0788] The "emotion analysis means" is a means for analyzing the user's emotions.

[0789] "Adjustment means" refers to a means for adjusting a solution proposal based on the results of sentiment analysis.

[0790] A "database" is a data storage device for storing information on each solution.

[0791] The present invention is a system that proposes optimal solutions taking into account the emotional state of the user. The system consists of the following main components:

[0792] 1. System Configuration

[0793] User Operation

[0794] The user uses the input means to input their specific needs and requirements. For example, they can input the genres and conditions they want to watch on the "content distribution service." Furthermore, a camera and microphone are used to collect facial expressions and voice data, and an emotion analysis means is used to analyze the user's emotions.

[0795] Terminal handling

[0796] The input means is used to collect needs and requirements from the user, which are then transmitted to the server by the transmission means. The collected facial expression and voice data is analyzed by the emotion analysis means and transmitted to the server as emotion data.

[0797] Server Processing

[0798] The server analyzes the needs and requirements data and emotion analysis data received by the transmission means using the analysis means. Based on the analysis results, related solution information is searched for using the search means. The searched information is generated as an optimal solution proposal by the generation means. An adjustment means adjusts the proposal content based on the emotion analysis data to generate a proposal that is optimal for the user's emotional state. In addition, each piece of solution information is stored in a database.

[0799] View Suggestions

[0800] The final solution proposal is displayed to the user using a display means, and the user can check the proposal, obtain more detailed information, or take specific actions.

[0801] 2. Working Example

[0802] For example, suppose a user wants to watch an "action movie" on a streaming service. The user inputs this request using the input means, and the input data is sent to the server. At the same time, an emotion analysis means using a camera and microphone analyzes the user's emotional state and determines, for example, that the user is in a "high stress state." Based on this, the server analyzes the received data using the analysis means and searches for information on related action movies using the search means.

[0803] Based on these search results, the generation means generates a suggestion of an action movie that will help the user relax. For example, instead of "action movies that get you excited," the generation means may adjust the suggestion to "action movies that are relaxing." The display means then displays the most suitable suggestion to the user. The user can then decide whether to watch the suggested movie.

[0804] In this way, using emotion analysis makes it possible to make suggestions that are tailored to the user's psychological state, thereby improving user satisfaction.

[0805] 3. Example prompts

[0806] For example, the following could be entered as a specific example of a prompt sentence for a generative AI model:

[0807] "If the user says they want to watch an action movie, and their current emotion is analyzed as high stress, generate recommendations for relaxing action movies based on this data."

[0808] The above is a specific embodiment of the present invention. This system makes it possible to propose optimal solutions according to the emotional state of the user.

[0809] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0810] Step 1:

[0811] The user uses an input means to input their specific needs or requirements. For example, the user may input a need such as "I want to watch an action movie," and the input data is captured by the terminal. The input acts as text data, which is used for further processing.

[0812] Step 2:

[0813] The terminal sends the input data of needs and requirements to the server. Using the transmission means, text data is sent to the server, and the server receives this data. The input data is packetized in JSON format and sent.

[0814] Step 3:

[0815] The device collects the user's facial expressions and voice data and analyzes their emotional state using emotion analysis means. Using a camera and microphone, the emotion engine analyzes the user's emotions based on the collected data. The analysis results in emotional states such as "high stress" and "relaxed."

[0816] Step 4:

[0817] The server uses an analysis means to analyze the needs and requirements data and emotion analysis data received from the terminal. The received text data and emotion data are passed to the analysis means, which extracts keywords from the input content and analyzes the emotional state.

[0818] Step 5:

[0819] Based on the keywords and emotion data extracted by the analysis means, the search means searches the database for related solution information. For example, a search is performed using the keywords "action movie" and "relaxation" to collect related information.

[0820] Step 6:

[0821] The server uses the generation means to generate optimal solution proposals based on the information collected by the search means. The generation means selects optimal solutions and constructs proposals based on the collected information and emotion data. For example, a list of "relaxing action movies" is generated.

[0822] Step 7:

[0823] The generated solution proposals are adapted to the sentiment analysis results using a tuning mechanism that further refines the proposals and restructures them to best suit the user's current emotional state.

[0824] Step 8:

[0825] The final proposal is sent from the server to the terminal and displayed to the user using the display means, allowing the user to visually confirm the proposal and decide on an action based on it.

[0826] These are the specific processing steps of the system that proposes optimal solutions based on the user's needs and emotional state.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] [Third embodiment]

[0831] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0832] 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.

[0833] 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).

[0834] 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.

[0835] 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.

[0836] 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).

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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."

[0843] System Overview

[0844] This invention relates to a system in which users input their specific needs and requirements, and AI analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, significantly improving work efficiency.

[0845] Specific operation of the system

[0846] This system consists of three main elements: the user, the terminal, and the server. The specific operation of each element is explained below.

[0847] User Operation

[0848] 1. Use of the input form

[0849] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup."

[0850] 2. Confirm your input

[0851] Users can review the input and make corrections or additions as necessary, allowing them to specify the conditions for the desired solution in detail.

[0852] Terminal handling

[0853] 1. Data transmission

[0854] The terminal sends the user's input information to the server, organized as data packets.

[0855] Server Processing

[0856] 1. Data Reception and Analysis

[0857] The server receives the data packets sent from the device and passes them to the AI ​​analysis engine.

[0858] The AI ​​analysis engine analyzes the incoming data and extracts keywords and conditions, such as "cloud-based," "data backup," "low cost," and "easy setup."

[0859] 2. Database Search

[0860] The server searches for relevant solution information from an internal database or external resources based on the keywords and conditions extracted by the analysis means.

[0861] For example, information such as "Amazon S3" and "Google Drive" is identified as a "low-cost, easy-to-setup cloud-based data backup solution."

[0862] 3. Proposal Generation

[0863] The server generates optimal solution proposals for the user based on the search results, and the proposals are provided along with detailed information.

[0864] For example, specific recommendations such as "Amazon S3 - a cost-conscious, recommended cloud-based data backup solution" are generated.

[0865] View Suggestions

[0866] 1. Displaying the results

[0867] The device displays the proposed data sent from the server to the user, who can then review the proposal and take next steps to request more information or take specific actions.

[0868] For example, suggestions such as "Google Drive - easy to set up and convenient" are displayed, along with detailed documentation and links.

[0869] Specific Examples

[0870] As a concrete example, consider a user who needs a cloud-based data backup solution and is looking for a low-cost, easy-to-setup solution. The user enters their requirements, and the device sends the information to the server. The server uses an AI analysis engine to search the database for optimal solution information and generate a proposal. Finally, the device displays suggestions such as "Amazon S3" and "Google Drive" to the user, allowing the user to quickly find the optimal solution.

[0871] In this way, by using this system, users can efficiently obtain information and achieve greater work efficiency.

[0872] The processing flow will be explained below.

[0873] Step 1:

[0874] Users enter their needs and requirements using an input form.

[0875] The device presents the user with a form where they can enter details about the solution they are looking for, such as "cloud-based data backup," "low cost," and "easy setup."

[0876] Step 2:

[0877] The user checks the input information and makes corrections or additions as necessary.

[0878] The terminal displays a confirmation screen for the user to confirm the input, and the user can check whether the input needs and requirements are correct and make corrections or additions if necessary. For example, change "low cost" to "minimum cost."

[0879] Step 3:

[0880] The terminal transmits the input information to the server.

[0881] After the user confirms the input, the terminal sends the information organized as a data packet to the server, where the input conditions are included in the data packet.

[0882] Step 4:

[0883] The server receives the data packets and analyzes them using the analysis means.

[0884] The server receives data packets sent from the device and passes them to the AI ​​analysis engine. The AI ​​analysis engine analyzes the received data and extracts related keywords and conditions. For example, "cloud-based," "data backup," "low cost," and "easy setup" are extracted.

[0885] Step 5:

[0886] The server searches the database based on the analysis results.

[0887] The server searches for relevant solution information from internal databases or external resources based on keywords and conditions extracted by the analysis method. For example, it finds information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-configure cloud-based data backup solutions."

[0888] Step 6:

[0889] The server generates an optimal solution proposal.

[0890] The server generates optimal solution proposals for the user based on the information obtained by the search means. The generation means organizes and lists the detailed proposals for each solution. For example, it generates specific proposals such as "Amazon S3 - cost-conscious, easy to set up" and "Google Drive - convenient and easy to use."

[0891] Step 7:

[0892] The server transmits the generated proposal data to the terminal.

[0893] The server transmits the generated proposal data to the terminal so that the user can confirm it. The transmitting means transmits a data packet including the proposal content to the terminal.

[0894] Step 8:

[0895] The device displays the suggestions to the user.

[0896] The device receives the proposed data from the server and displays it to the user. The user can then review the proposed solution and view detailed information on the device screen. For example, the proposed solution might say, "Amazon S3 - A cost-effective, recommended cloud-based data backup solution."

[0897] In this way, each step ensures a smooth process from user input to the proposal of the optimal solution.

[0898] Example 1

[0899] 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."

[0900] In traditional systems, even when users input their specific needs and requirements, the process for connecting that information to the optimal solution is often inefficient. It also requires a lot of manual work and takes a long time to find the correct solution. This can lead to reduced operational efficiency and user dissatisfaction.

[0901] 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.

[0902] In this invention, the server includes input means for a user to input specific needs and requirements, transmission means for transmitting the input needs and requirements to the information processing device, analysis means for analyzing the received needs and requirements, search means for searching for related solution information based on the analysis results, generation means for generating optimal solution proposals from the search results, and display means for displaying the generated proposals to the user, thereby making it possible to quickly and accurately propose solutions based on the user's input.

[0903] "Input means" is a device or interface through which a user inputs their specific needs or requirements.

[0904] The "transmission means" is a device or protocol for transmitting input needs and requirements to an information processing device.

[0905] "Analysis means" is a device or software for analyzing received needs or requirements.

[0906] The "search means" is a device or software for searching for related solution information based on the analysis results.

[0907] The "generation means" is a device or software for generating optimal solution proposals from search results.

[0908] A "display means" is a device or interface for displaying generated suggestions to a user.

[0909] "Solution information" is information about solutions that address user needs and requirements.

[0910] A "storage device" is a data storage device for storing solution information.

[0911] System Overview

[0912] The present invention relates to a system that allows users to input specific needs and requirements, and an information processing device analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, significantly improving work efficiency.

[0913] Specific system configuration

[0914] This system consists of three main elements: users, terminals, and servers. The specific configuration and functions of each element are explained below.

[0915] User operations and devices

[0916] The user enters their needs and requirements using an input form on the device. The information is organized in JSON format and sent to the server via HTTPS. The device uses a form written in React that runs on a web browser.

[0917] Examples:

[0918] The user enters their requirements for "cloud-based data backup," "low cost," and "easy setup." Once they've completed the input, they press the "Submit" button.

[0919] Server Processing

[0920] The server receives the JSON data sent from the device. The received data is passed to an AI analysis engine, which converts the data into text format and begins analysis. The generative AI model used is, for example, OpenAI's GPT-3.

[0921] Examples:

[0922] An example of a prompt is as follows:

[0923] Please suggest the best solution for the following requirements:

[0924] Cloud-based data backup

[0925] Low cost

[0926] Easy to set up

[0927] The server searches for the best solution information from a database based on the analyzed keywords. In addition to the internal database, it utilizes external resources (e.g., APIs of cloud service providers).

[0928] The search results are generated as optimal solution recommendations. The recommendations are presented in a user-friendly format. An example recommendation might be, "Amazon S3 - A cost-conscious, recommended cloud-based data backup solution."

[0929] View Suggestions

[0930] The device receives the proposed data sent from the server and displays it to the user, providing detailed information and links so the user can easily take the next action.

[0931] Examples:

[0932] The content displayed on the terminal will be as follows:

[0933] Recommended solutions:

[0934] 1. Amazon S3 - A cost-effective and recommended cloud-based data backup solution.

[0935] [More details here]

[0936] 2. Google Drive - A convenient cloud-based data backup solution that's easy to set up.

[0937] [More details here]

[0938] In this way, the process from user input to server analysis and display on the terminal allows users to efficiently obtain information and improve work efficiency.

[0939] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0940] System program processing flow

[0941] Step 1:

[0942] Users enter their needs and requirements into an input form on their device. For example, they might enter "cloud-based data backup," "low cost," and "easy setup." This input form is written in React and runs on a web browser, with the input data organized in JSON format.

[0943] Input: User needs and requirements (e.g., "cloud-based data backup," "low cost," "easy to set up")

[0944] Output: Cleaned JSON data

[0945] Step 2:

[0946] The device sends the entered JSON data to the server via HTTPS, and this communication is encrypted to ensure security.

[0947] Input: Organized JSON data

[0948] Output: JSON data sent to the server

[0949] Step 3:

[0950] The server receives the JSON data sent from the device. The received data is passed to an AI analysis engine and converted into text format. The generative AI model used here is, for example, OpenAI's GPT-3.

[0951] Input: JSON data received from the terminal

[0952] Output: Data converted to text format

[0953] Step 4:

[0954] The server inputs the converted data into text format into an AI analysis engine, which then analyzes the received text data and extracts important keywords and conditions.

[0955] Input: Data converted to text format (e.g., "Cloud-based data backup," "Low cost," "Easy to set up")

[0956] Output: Extracted keywords and conditions

[0957] Step 5:

[0958] The server searches for the best solution information from an internal database or external resources based on the extracted keywords and conditions, for example, by using a cloud service provider's API to find the relevant solution. This search includes filtering and ranking.

[0959] Input: Extracted keywords or conditions (e.g., "cloud-based," "low-cost," "easy to set up")

[0960] Output: Search results (list of optimal solution information)

[0961] Step 6:

[0962] The server generates optimal solution proposals based on the search results, including specific product or service names and features.

[0963] Input: Search results (list of best solution information)

[0964] Output: Generated recommendations (e.g., "Amazon S3 - Cost-sensitive and recommended cloud-based data backup solutions")

[0965] Step 7:

[0966] The device receives the proposed data sent from the server and displays it to the user, showing detailed information about the proposed solution and related links.

[0967] Input: Proposal data sent from the server

[0968] Output: The recommendation that will be displayed to the user (e.g., "Amazon S3 - A cost-sensitive and recommended cloud-based data backup solution")

[0969] This series of processing steps allows the user to obtain the optimal solution efficiently and quickly.

[0970] (Application example 1)

[0971] 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."

[0972] Conventional food delivery systems have the problem that users must individually search for the type of food they want, their budget, delivery time, etc., which is time-consuming. It is also difficult to quickly and accurately obtain information on the restaurant and menu that best matches the user's criteria. This situation often makes it difficult for users to easily find the food they want, resulting in inconvenience.

[0973] 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.

[0974] In this invention, the server includes input means for a user to input specific needs and requirements, transmission means for transmitting the input needs and requirements to the server, analysis means for analyzing the received needs and requirements, search means for searching for related solution information based on the analysis results, generation means for generating optimal solution proposals from the search results, display means for displaying the generated proposals to the user, and means for inputting conditions such as the user's food preferences, budget, and delivery time and suggesting optimal restaurants and dishes based on these conditions, thereby enabling users to quickly and accurately find dishes and restaurants that meet their desired conditions.

[0975] "User" means any individual or entity that uses the Service or System.

[0976] "Needs" are the demands and desires that users have for specific services or products.

[0977] "Requirements" are the conditions or criteria that a user must meet to meet a particular need.

[0978] "Input means" refers to a device or interface that allows a user to input their needs and requirements into the system.

[0979] "Transmission means" refers to the communication functions and protocols used to send data entered by the user to the server.

[0980] "Analysis means" refers to algorithms or programs for analyzing received needs and requirements and extracting relevant information.

[0981] "Search means" refers to the function of searching for related solutions and data from a database based on the information obtained by the analysis means.

[0982] "Generation means" refers to a function or program for creating optimal proposals based on the information obtained by the search means.

[0983] "Display means" refers to a display or interface for showing the generated suggestions to the user.

[0984] "Cooking preferences" refers to the user's preferences for specific ingredients, cooking methods, etc.

[0985] A "budget" refers to the funds or expenses that a user plans to allocate for purchases or uses.

[0986] "Delivery time" refers to the time it takes from placing an order to completing delivery.

[0987] A "restaurant" is a commercial establishment that serves food and beverages.

[0988] A "prompt" is text that provides instructions or information to a generative AI model.

[0989] MODE FOR CARRYING OUT THE INVENTION

[0990] This invention relates to a system in which a user inputs specific needs and requirements, and an AI analyzes the input content to generate optimal solution proposals. Specific embodiments for implementing this invention are described below.

[0991] System configuration

[0992] User

[0993] Users use a device such as a smartphone to input conditions such as specific food preferences, budget, and delivery time. For example, they can input detailed needs and requirements such as "I want spicy pizza," "under 2,000 yen," and "delivery within 45 minutes."

[0994] Terminal

[0995] The user's input information is sent to the server by the terminal (smartphone or tablet) via a transmission means. The terminal has the function of formatting the data into an appropriate format and sending it to the server as a data packet.

[0996] server

[0997] The server uses a generative AI model to analyze the received user needs and requirements. Specifically, it uses an AI analysis engine (e.g., OpenAI GPT-4) to extract search criteria. The analysis means searches a database for relevant restaurant and cuisine information based on the analyzed keywords and criteria. The server generates appropriate restaurant and menu suggestions based on the analysis results.

[0998] Database

[0999] The database stores data such as menu information, prices, delivery times, etc. The search function allows users to quickly extract information that matches their requirements.

[1000] Generate and view suggestions

[1001] The proposal generated on the server is sent to the user's terminal along with detailed information. The generating means generates an optimal solution (e.g., "Spicy pizza at a nearby pizza place - 1,800 yen"). The display means on the terminal allows the user to quickly and accurately check the proposal.

[1002] Natural language processing explanation

[1003] Specific names of hardware and software

[1004] Hardware: Smartphones, servers (e.g., Amazon AWS)

[1005] Software: Generative AI models (e.g., OpenAI GPT-4), database systems

[1006] Data processing and calculation

[1007] 1. Data reception and analysis: The user enters their food preferences, budget, and delivery time into an input form on their smartphone and sends the information to the server.

[1008] 2. Data transmission: The terminal transmits data to the server by the transmission means.

[1009] 3. Data analysis: The AI ​​analysis engine on the server analyzes the data and searches the database for restaurant information that meets the criteria.

[1010] 4. Proposal generation: Using the generation method, the AI ​​generates optimal restaurant and menu suggestions and provides feedback to the user.

[1011] Adding specific examples

[1012] Specific examples

[1013] When a user types, "I want a spicy pizza that costs under 2,000 yen and can be delivered within 45 minutes," the AI ​​searches for nearby restaurants that meet the criteria and generates suggestions such as "Spicy pizza from Pizza Shop X - 1,800 yen."

[1014] Prompt Sentence Examples

[1015] The user entered the following criteria:

[1016] Cuisine: Pizza

[1017] Budget: Under 2000 yen

[1018] Delivery time: within 45 minutes

[1019] Specific requirements: Spicy

[1020] Based on this, please suggest the best restaurant and menu.

[1021] By implementing the present invention based on the above aspects, a user can quickly and accurately find food and restaurants that meet his or her desired conditions.

[1022] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1023] Step 1:

[1024] Users input criteria such as specific food preferences, budget, and delivery time into a form on their smartphone. For example, they enter detailed requirements such as "pizza," "under 2000 yen," "within 45 minutes," and "spicy." This input data is organized as a data packet in JSON format.

[1025] input:

[1026] Types of cuisine

[1027] budget

[1028] Delivery time

[1029] Specific requirements

[1030] output:

[1031] Organized data packets (e.g., JSON format)

[1032] Operation:

[1033] The user operates the input form on the smartphone and enters the required conditions.

[1034] Step 2:

[1035] The terminal sends the input data packet to the server using a communication protocol such as an HTTP POST request. At this time, the data entered in the input form is sent to the server appropriately.

[1036] input:

[1037] Reordered data packets (output of step 1)

[1038] output:

[1039] Data packets sent to the server

[1040] Operation:

[1041] The device formats the data appropriately and sends it to the server.

[1042] Step 3:

[1043] The server passes the received data packets to an analysis engine (e.g., a generative AI model). The analysis engine extracts important keywords and conditions based on the input data. For example, it might extract keywords such as "pizza," "under 2,000 yen," "within 45 minutes," and "spicy."

[1044] input:

[1045] Received data packets (output of step 2)

[1046] output:

[1047] Extracted keywords and conditions

[1048] Operation:

[1049] The server uses a generative AI model to analyze the input data and obtain important keywords and conditions.

[1050] Step 4:

[1051] The server searches the database for relevant restaurant and food information based on the keywords and conditions extracted by the analysis engine. For example, it searches for restaurants that meet the conditions "pizza," "under 2,000 yen," "within 45 minutes," and "spicy."

[1052] input:

[1053] Extracted keywords and conditions (output of Step 3)

[1054] output:

[1055] Restaurant and food information extracted from the database

[1056] Operation:

[1057] The server performs a database search and extracts information that matches the criteria.

[1058] Step 5:

[1059] The server generates optimal suggestions based on the search results. The generation means creates suggestions suitable for the user, such as "Spicy pizza from pizza shop Y - 1800 yen."

[1060] input:

[1061] Restaurant and dish information extracted from the database (output of step 4)

[1062] output:

[1063] Optimal proposal content

[1064] Operation:

[1065] The server puts together the best suggestions and generates the information to show the user.

[1066] Step 6:

[1067] The generated suggestions are sent to the terminal and are fed back to the user via the display means. The user can check the suggestions and use them as a reference for deciding what to order.

[1068] input:

[1069] Optimal proposal (output of step 5)

[1070] output:

[1071] Displaying suggestions to users

[1072] Operation:

[1073] The server sends the generated proposals to the terminal, which displays them to the user.

[1074] As a result, users can quickly and accurately obtain suggestions for dishes and restaurants that meet their desired conditions.

[1075] 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.

[1076] System Overview

[1077] This invention combines an emotion engine with a system in which users input their specific needs and requirements, and AI analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, and by making proposals that take the user's emotions into consideration, it is possible to provide more appropriate and satisfying solutions.

[1078] Specific operation of the system

[1079] This system is composed of three main elements: the user, the device, and the server. By incorporating an emotion engine, it is possible to realize suggestions based on the user's emotional state. The specific operation of each element is explained below.

[1080] User Operation

[1081] 1. Use of the input form

[1082] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup."

[1083] 2. Confirm your input

[1084] Users can review the input and make corrections or additions as necessary, allowing them to specify the conditions for the desired solution in detail.

[1085] Terminal handling

[1086] 1. Data transmission

[1087] The terminal sends the user's input information to the server, organized as data packets.

[1088] 2. Emotional Engine Activation

[1089] The device sends the user's facial expression and voice data to the emotion engine, which analyzes the user's emotions. For example, it uses a camera and microphone to detect the user's smile, tone of voice, stress level, etc.

[1090] Server Processing

[1091] 1. Data Reception and Analysis

[1092] The server receives the data packets sent from the device and the emotion data from the emotion engine, and passes them to the AI ​​analysis engine.

[1093] An AI analytics engine analyzes the received data and extracts relevant keywords, conditions, and emotional states, such as "cloud-based," "data backup," "low cost," "easy to set up," and "high stress."

[1094] 2. Database Search

[1095] The server searches for relevant solution information from an internal database or external resources based on the keywords, conditions, and emotional data extracted by the analysis means.

[1096] For example, it detects information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-setup cloud-based data backup solutions."

[1097] 3. Proposal Generation

[1098] The server uses the generation means to generate optimal solution proposals for the user based on the search results and emotion data. For example, if the user is in a high stress state, the server will prioritize proposing easier and less time-consuming solutions.

[1099] It generates detailed proposals such as "Amazon S3 - cost-conscious, easy to set up" and "Google Drive - convenient and easy to use."

[1100] View Suggestions

[1101] 1. Displaying the results

[1102] The device displays the proposed data sent from the server to the user, who can then review the proposal and take next steps to request more information or take specific actions.

[1103] For example, suggestions like "Amazon S3 - A cost-effective, recommended cloud-based data backup solution" are displayed, along with detailed documentation and links.

[1104] Specific Examples

[1105] As a concrete example, consider a user who needs a "cloud-based data backup solution" and is looking for a solution that is low-cost and easy to set up. The user enters their requirements, and the device sends the information to the server. Then, an emotion engine recognizes the user's high stress level from their facial expressions and voice. The server uses an analysis engine to search a database for optimal solution information and generates suggestions that take the user's emotional state into account. Finally, the device displays suggestions such as "Amazon S3" and "Google Drive" to the user, allowing the user to quickly find the optimal solution.

[1106] In this way, by using this system, users can not only obtain information efficiently and achieve work efficiency, but also improve satisfaction through suggestions that take their emotional state into consideration.

[1107] The processing flow will be explained below.

[1108] Step 1:

[1109] Users enter their needs and requirements using an input form.

[1110] The device displays a form for users to enter details about the solution they are looking for, such as "cloud-based data backup," "low cost," and "easy setup."

[1111] Step 2:

[1112] The user checks the input information and makes corrections or additions as necessary.

[1113] The terminal displays a confirmation screen for the user to confirm the input, and the user can check whether the input needs and requirements are correct and make corrections or additions if necessary. For example, change "low cost" to "minimum cost."

[1114] Step 3:

[1115] The terminal transmits the input information to the server.

[1116] After the user confirms the input, the terminal sends the information organized as a data packet to the server, where the input conditions are included in the data packet.

[1117] Step 4:

[1118] The device sends the user's facial expressions and voice data to an emotion engine to recognize the user's emotions.

[1119] The device sends the user's facial expressions and voice via a camera and microphone to the emotion engine, which then analyzes the user's emotional state. For example, it examines smiles, tone of voice, and stress levels, and recognizes them as "high stress."

[1120] Step 5:

[1121] The server receives the data packets and analyzes them using the analysis means.

[1122] The server receives the data packets and emotion data sent from the device and passes them to the AI ​​analysis engine. The AI ​​analysis engine analyzes the received data and extracts related keywords and conditions, such as "cloud-based," "data backup," "low cost," "easy to set up," and "high stress."

[1123] Step 6:

[1124] Based on the analysis results, the server searches for solution information from resources inside and outside the database.

[1125] The server searches for relevant solution information from an internal database or external resources based on the keywords, conditions, and sentiment data extracted by the analysis method. For example, it searches for information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-configure cloud-based data backup solutions."

[1126] Step 7:

[1127] The server generates an optimal solution proposal.

[1128] The server generates optimal solution suggestions for the user based on the acquired information and emotional data. For example, if the user is in a high-stress state, it will prioritize solutions that are easier and less time-consuming. It generates detailed suggestions such as "Amazon S3 - cost-conscious, easy to set up" or "Google Drive - convenient and easy to use."

[1129] Step 8:

[1130] The server transmits the generated proposal data to the terminal.

[1131] The server transmits the generated proposal data to the terminal so that the user can confirm it. The transmitting means transmits a data packet including the proposal content to the terminal.

[1132] Step 9:

[1133] The device displays the suggestions to the user.

[1134] The device receives the proposed data from the server and displays it to the user. The user can then review the proposed solution and view detailed information on the device screen. For example, the device may display a suggestion such as "Amazon S3 - A cost-effective, recommended cloud-based data backup solution," along with detailed documentation and links.

[1135] In this way, each step ensures a smooth process from user input to the proposal of the optimal solution. In addition, by combining it with an emotion engine, it is possible to make more appropriate proposals that take into account the user's emotional state.

[1136] Example 2

[1137] 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."

[1138] In conventional systems, users can input their specific needs and requirements and then propose optimal solutions based on the results. However, proposals are often made without taking into account the user's emotional state. This can leave users feeling stressed or dissatisfied, and there are issues with the quality of proposals and satisfaction not being sufficiently improved.

[1139] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes an input means for the user to input specific needs and requirements, a transmission means for transmitting the input needs and requirements to the server, an emotion analysis means for analyzing the emotional state of the user on the terminal, an analysis means for analyzing the received needs, requirements, and emotional state, a search means for searching for related solution information based on the analysis results, a generation means for generating an optimal solution proposal taking into account the search results and the user's emotional state, and a display means for displaying the generated proposal to the user. This makes it possible to propose an appropriate solution according to the user's emotional state, thereby improving user satisfaction.

[1140] "Input means" is an interface through which a user inputs their specific needs and requirements.

[1141] "Transmission means" is a function for transmitting input needs and requirements to a server.

[1142] The "emotion analysis means" is a function for analyzing the user's emotional state from facial expressions, voice, etc.

[1143] "Analysis means" is a device or software for analyzing received needs, requirements and emotional states.

[1144] The "search means" is a function for searching for related solution information based on the analysis results.

[1145] The "generation means" is a function for generating optimal solution proposals taking into account the search results and the emotional state of the user.

[1146] The "display means" is an interface for displaying the generated solution proposal to the user.

[1147] A "server" is a computer device that receives user needs, requirements, and emotional data, analyzes, searches, and generates suggestions.

[1148] A "terminal" is a device that a user uses to input their needs and requirements and analyze emotional data.

[1149] This invention combines an emotion engine with a system in which a user inputs specific needs and requirements, and a server analyzes those needs and requirements to generate optimal solution proposals. Specifically, it consists of three main elements: the user, the terminal, and the server.

[1150] User Operation

[1151] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup." They can then review their input and make corrections or additions if necessary. The more accurate and detailed this information is, the more likely it is that the optimal solution will be suggested.

[1152] Terminal handling

[1153] The device organizes the user's input information into data packets and sends them to the server. Communication protocols such as HTTP POST requests are used for data transmission. Furthermore, the device uses an emotion engine to collect the user's facial expressions and voice data and analyze their emotional state. Specifically, the device collects data using the built-in camera and microphone, and analyzes it using an emotion recognition API (e.g., a general emotion recognition platform).

[1154] Server Processing

[1155] The server receives the data packets and sentiment analysis data sent from the device and passes them to the analysis engine. The analysis engine uses an NLP library (e.g., a general natural language processing library) to extract relevant keywords, conditions, and emotional states from the received data. Next, a search function runs to search for relevant solution information based on the analysis results. SQL queries and API calls are used for database searches.

[1156] The server then generates optimal solution proposals based on the search results and the user's emotional state. A template engine (e.g., a general template engine) is used to generate the proposals, forming specific proposal content. If the user is in a high-stress state, easier and less time-consuming solutions are prioritized.

[1157] View Suggestions

[1158] The device receives the recommendations sent from the server and displays them to the user, either as a web browser widget or a dedicated application. The user can review the recommendations and select next steps for more information or specific actions. For example, a recommendation might be "Amazon S3 - a cost-conscious, recommended cloud-based data backup solution," with corresponding detailed documentation and links provided.

[1159] Examples and prompts

[1160] As a concrete example, consider a situation where a user in need of a "cloud-based data backup solution" is looking for a solution that is low-cost and easy to set up. The user enters their requirements, and the device sends that information to the server. An emotion engine then recognizes the user's high stress level from their facial expressions and voice. The server uses an analysis engine to search a database for optimal solution information and generates suggestions that take the user's emotional state into account. Finally, the device displays suggestions such as "general cloud storage services" to the user, allowing the user to quickly find the optimal solution.

[1161] Example prompt sentence:

[1162] Generate a proposal for a high-stress user looking for a cloud-based data backup solution that is low-cost and easy to set up.

[1163] By using this system, users can not only obtain information efficiently and achieve work efficiency, but also improve satisfaction through suggestions that take their emotional state into account.

[1164] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1165] Step 1:

[1166] The user enters their needs and requirements using an input form displayed on the device. The input information includes "cloud-based data backup," "low cost," and "easy setup." This clearly defines the user's requirements. For example, if a user enters "low cost, easy setup cloud storage," the requirement is recorded as data.

[1167] Step 2:

[1168] The user checks the input and makes corrections or additions as necessary. The input in this step is a review and correction of the information entered in the previous step. For example, by changing "low cost" to "annual cost less than $100," more specific requirements are determined. This checked and corrected data is passed to the next step as the final output.

[1169] Step 3:

[1170] The device sends the organized user input information to the server, formatted as a data packet in JSON or XML format. For example, a requirement for "low-cost cloud-based data backup" is sent to the server using an HTTP POST request. The input in this step is the user's requirement information, and the output is a data packet sent to the server.

[1171] Step 4:

[1172] At the same time, the device starts an emotion engine, collecting and analyzing the user's facial expressions and voice data. The data is captured using a camera and microphone, and analyzed using an emotion recognition API (e.g., a general emotion recognition platform). The analysis result is an emotional state such as "high stress" or "moderate." This analyzed emotion data is also sent to the server. The input is the original emotional state data, and the output is the analyzed emotion data.

[1173] Step 5:

[1174] The server receives data packets and emotional data sent from the device and passes them to the AI ​​analysis engine. The received data is in JSON or XML format and is fed to the analysis engine. For example, an NLP library (e.g., a general natural language processing library) is used to extract keywords and conditions such as "cloud-based," "low cost," and "easily configurable," as well as the emotional state ("high stress"). The input of this step is the user's requirements and emotional data, and the output is the extracted keywords and emotional state.

[1175] Step 6:

[1176] The server searches for relevant solution information from databases and external resources based on the analyzed keywords, conditions, and sentiment data. It uses SQL queries and API calls to retrieve entries containing, for example, "low-cost, easy-to-configure cloud backup solutions." The input is the analysis results, and the output is the searched solution information.

[1177] Step 7:

[1178] The server uses a template engine (e.g., a general template engine) to generate optimal solution proposals based on the search results and sentiment data. For example, it generates proposals such as "Amazon S3 - cost-effective and easy to set up" and "Google Drive - convenient and easy to use." Since the user is in a high-stress state at this time, it prioritizes simpler solutions. The generated proposals are formatted in a format appropriate for the user. The inputs are search results and sentiment data, and the output is the generated proposal text.

[1179] Step 8:

[1180] The terminal receives the generated recommendation data from the server and displays it to the user. The display format can be a web browser widget or a dedicated application. For example, the recommendation content may be "Amazon S3 - A cost-conscious, recommended cloud-based data backup solution" and provide a link to more information. The input is the generated recommendation text, and the output is a visual display to the user.

[1181] Through these processing steps, users are efficiently offered solutions that meet their requirements and can achieve higher satisfaction because the suggestions take into account the user's emotional state.

[1182] (Application example 2)

[1183] 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."

[1184] Conventional solution proposal systems were able to make optimal proposals based on the user's needs and requirements, but they were unable to take the user's emotional state into consideration. As a result, they were unable to make proposals that were optimized for the user's psychological state, such as high stress or relaxed state, which led to a problem of reduced user satisfaction.

[1185] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion analysis means for analyzing the user's emotions, means for adjusting the solution proposal based on the emotion analysis results, and analysis means for analyzing the received needs and requirements. This makes it possible to propose an optimal solution based on the user's emotional state.

[1186] "Input means" refers to the means by which a user inputs their specific needs and requirements.

[1187] The "transmission means" is a means for transmitting the input needs and requirements to the server.

[1188] "Analysis means" is a means for analyzing received needs and requirements.

[1189] The "search means" is a means for searching for related solution information based on the analysis results.

[1190] The "generation means" is a means for generating an optimal solution proposal from the search results.

[1191] The "display means" is a means for displaying the generated proposal to the user.

[1192] The "emotion analysis means" is a means for analyzing the user's emotions.

[1193] "Adjustment means" refers to a means for adjusting a solution proposal based on the results of sentiment analysis.

[1194] A "database" is a data storage device for storing information on each solution.

[1195] The present invention is a system that proposes optimal solutions taking into account the emotional state of the user. The system consists of the following main components:

[1196] 1. System Configuration

[1197] User Operation

[1198] The user uses the input means to input their specific needs and requirements. For example, they can input the genres and conditions they want to watch on the "content distribution service." Furthermore, a camera and microphone are used to collect facial expressions and voice data, and an emotion analysis means is used to analyze the user's emotions.

[1199] Terminal handling

[1200] The input means is used to collect needs and requirements from the user, which are then transmitted to the server by the transmission means. The collected facial expression and voice data is analyzed by the emotion analysis means and transmitted to the server as emotion data.

[1201] Server Processing

[1202] The server analyzes the needs and requirements data and emotion analysis data received by the transmission means using the analysis means. Based on the analysis results, related solution information is searched for using the search means. The searched information is generated as an optimal solution proposal by the generation means. An adjustment means adjusts the proposal content based on the emotion analysis data to generate a proposal that is optimal for the user's emotional state. In addition, each piece of solution information is stored in a database.

[1203] View Suggestions

[1204] The final solution proposal is displayed to the user using a display means, and the user can check the proposal, obtain more detailed information, or take specific actions.

[1205] 2. Working Example

[1206] For example, suppose a user wants to watch an "action movie" on a streaming service. The user inputs this request using the input means, and the input data is sent to the server. At the same time, an emotion analysis means using a camera and microphone analyzes the user's emotional state and determines, for example, that the user is in a "high stress state." Based on this, the server analyzes the received data using the analysis means and searches for information on related action movies using the search means.

[1207] Based on these search results, the generation means generates a suggestion of an action movie that will help the user relax. For example, instead of "action movies that get you excited," the generation means may adjust the suggestion to "action movies that are relaxing." The display means then displays the most suitable suggestion to the user. The user can then decide whether to watch the suggested movie.

[1208] In this way, using emotion analysis makes it possible to make suggestions that are tailored to the user's psychological state, thereby improving user satisfaction.

[1209] 3. Example prompts

[1210] For example, the following could be entered as a specific example of a prompt sentence for a generative AI model:

[1211] "If the user says they want to watch an action movie, and their current emotion is analyzed as high stress, generate recommendations for relaxing action movies based on this data."

[1212] The above is a specific embodiment of the present invention. This system makes it possible to propose optimal solutions according to the emotional state of the user.

[1213] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1214] Step 1:

[1215] The user uses an input means to input their specific needs or requirements. For example, the user may input a need such as "I want to watch an action movie," and the input data is captured by the terminal. The input acts as text data, which is used for further processing.

[1216] Step 2:

[1217] The terminal sends the input data of needs and requirements to the server. Using the transmission means, text data is sent to the server, and the server receives this data. The input data is packetized in JSON format and sent.

[1218] Step 3:

[1219] The device collects the user's facial expressions and voice data and analyzes their emotional state using emotion analysis means. Using a camera and microphone, the emotion engine analyzes the user's emotions based on the collected data. The analysis results in emotional states such as "high stress" and "relaxed."

[1220] Step 4:

[1221] The server uses an analysis means to analyze the needs and requirements data and emotion analysis data received from the terminal. The received text data and emotion data are passed to the analysis means, which extracts keywords from the input content and analyzes the emotional state.

[1222] Step 5:

[1223] Based on the keywords and emotion data extracted by the analysis means, the search means searches the database for related solution information. For example, a search is performed using the keywords "action movie" and "relaxation" to collect related information.

[1224] Step 6:

[1225] The server uses the generation means to generate optimal solution proposals based on the information collected by the search means. The generation means selects optimal solutions and constructs proposals based on the collected information and emotion data. For example, a list of "relaxing action movies" is generated.

[1226] Step 7:

[1227] The generated solution proposals are adapted to the sentiment analysis results using a tuning mechanism that further refines the proposals and restructures them to best suit the user's current emotional state.

[1228] Step 8:

[1229] The final proposal is sent from the server to the terminal and displayed to the user using the display means, allowing the user to visually confirm the proposal and decide on an action based on it.

[1230] These are the specific processing steps of the system that proposes optimal solutions based on the user's needs and emotional state.

[1231] 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.

[1232] 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.

[1233] 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.

[1234] [Fourth embodiment]

[1235] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1236] 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.

[1237] 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).

[1238] 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.

[1239] 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.

[1240] 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).

[1241] 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.

[1242] 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.

[1243] 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.

[1244] 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.

[1245] 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.

[1246] 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.

[1247] 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."

[1248] System Overview

[1249] This invention relates to a system in which users input their specific needs and requirements, and AI analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, significantly improving work efficiency.

[1250] Specific operation of the system

[1251] This system consists of three main elements: the user, the terminal, and the server. The specific operation of each element is explained below.

[1252] User Operation

[1253] 1. Use of the input form

[1254] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup."

[1255] 2. Confirm your input

[1256] Users can review the input and make corrections or additions as necessary, allowing them to specify the conditions for the desired solution in detail.

[1257] Terminal handling

[1258] 1. Data transmission

[1259] The terminal sends the user's input information to the server, organized as data packets.

[1260] Server Processing

[1261] 1. Data Reception and Analysis

[1262] The server receives the data packets sent from the device and passes them to the AI ​​analysis engine.

[1263] The AI ​​analysis engine analyzes the incoming data and extracts keywords and conditions, such as "cloud-based," "data backup," "low cost," and "easy setup."

[1264] 2. Database Search

[1265] The server searches for relevant solution information from an internal database or external resources based on the keywords and conditions extracted by the analysis means.

[1266] For example, information such as "Amazon S3" and "Google Drive" is identified as a "low-cost, easy-to-setup cloud-based data backup solution."

[1267] 3. Proposal Generation

[1268] The server generates optimal solution proposals for the user based on the search results, and the proposals are provided along with detailed information.

[1269] For example, specific recommendations such as "Amazon S3 - a cost-conscious, recommended cloud-based data backup solution" are generated.

[1270] View Suggestions

[1271] 1. Displaying the results

[1272] The device displays the proposed data sent from the server to the user, who can then review the proposal and take next steps to request more information or take specific actions.

[1273] For example, suggestions such as "Google Drive - easy to set up and convenient" are displayed, along with detailed documentation and links.

[1274] Specific Examples

[1275] As a concrete example, consider a user who needs a cloud-based data backup solution and is looking for a low-cost, easy-to-setup solution. The user enters their requirements, and the device sends the information to the server. The server uses an AI analysis engine to search the database for optimal solution information and generate a proposal. Finally, the device displays suggestions such as "Amazon S3" and "Google Drive" to the user, allowing the user to quickly find the optimal solution.

[1276] In this way, by using this system, users can efficiently obtain information and achieve greater work efficiency.

[1277] The processing flow will be explained below.

[1278] Step 1:

[1279] Users enter their needs and requirements using an input form.

[1280] The device presents the user with a form where they can enter details about the solution they are looking for, such as "cloud-based data backup," "low cost," and "easy setup."

[1281] Step 2:

[1282] The user checks the input information and makes corrections or additions as necessary.

[1283] The terminal displays a confirmation screen for the user to confirm the input, and the user can check whether the input needs and requirements are correct and make corrections or additions if necessary. For example, change "low cost" to "minimum cost."

[1284] Step 3:

[1285] The terminal transmits the input information to the server.

[1286] After the user confirms the input, the terminal sends the information organized as a data packet to the server, where the input conditions are included in the data packet.

[1287] Step 4:

[1288] The server receives the data packets and analyzes them using the analysis means.

[1289] The server receives data packets sent from the device and passes them to the AI ​​analysis engine. The AI ​​analysis engine analyzes the received data and extracts related keywords and conditions. For example, "cloud-based," "data backup," "low cost," and "easy setup" are extracted.

[1290] Step 5:

[1291] The server searches the database based on the analysis results.

[1292] The server searches for relevant solution information from internal databases or external resources based on keywords and conditions extracted by the analysis method. For example, it finds information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-configure cloud-based data backup solutions."

[1293] Step 6:

[1294] The server generates an optimal solution proposal.

[1295] The server generates optimal solution proposals for the user based on the information obtained by the search means. The generation means organizes and lists the detailed proposals for each solution. For example, it generates specific proposals such as "Amazon S3 - cost-conscious, easy to set up" and "Google Drive - convenient and easy to use."

[1296] Step 7:

[1297] The server transmits the generated proposal data to the terminal.

[1298] The server transmits the generated proposal data to the terminal so that the user can confirm it. The transmitting means transmits a data packet including the proposal content to the terminal.

[1299] Step 8:

[1300] The device displays the suggestions to the user.

[1301] The device receives the proposed data from the server and displays it to the user. The user can then review the proposed solution and view detailed information on the device screen. For example, the proposed solution might say, "Amazon S3 - A cost-effective, recommended cloud-based data backup solution."

[1302] In this way, each step ensures a smooth process from user input to the proposal of the optimal solution.

[1303] Example 1

[1304] 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."

[1305] In traditional systems, even when users input their specific needs and requirements, the process for connecting that information to the optimal solution is often inefficient. It also requires a lot of manual work and takes a long time to find the correct solution. This can lead to reduced operational efficiency and user dissatisfaction.

[1306] 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.

[1307] In this invention, the server includes input means for a user to input specific needs and requirements, transmission means for transmitting the input needs and requirements to the information processing device, analysis means for analyzing the received needs and requirements, search means for searching for related solution information based on the analysis results, generation means for generating optimal solution proposals from the search results, and display means for displaying the generated proposals to the user, thereby making it possible to quickly and accurately propose solutions based on the user's input.

[1308] "Input means" is a device or interface through which a user inputs their specific needs or requirements.

[1309] The "transmission means" is a device or protocol for transmitting input needs and requirements to an information processing device.

[1310] "Analysis means" is a device or software for analyzing received needs or requirements.

[1311] The "search means" is a device or software for searching for related solution information based on the analysis results.

[1312] The "generation means" is a device or software for generating optimal solution proposals from search results.

[1313] A "display means" is a device or interface for displaying generated suggestions to a user.

[1314] "Solution information" is information about solutions that address user needs and requirements.

[1315] A "storage device" is a data storage device for storing solution information.

[1316] System Overview

[1317] The present invention relates to a system that allows users to input specific needs and requirements, and an information processing device analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, significantly improving work efficiency.

[1318] Specific system configuration

[1319] This system consists of three main elements: users, terminals, and servers. The specific configuration and functions of each element are explained below.

[1320] User operations and devices

[1321] The user enters their needs and requirements using an input form on the device. The information is organized in JSON format and sent to the server via HTTPS. The device uses a form written in React that runs on a web browser.

[1322] Examples:

[1323] The user enters their requirements for "cloud-based data backup," "low cost," and "easy setup." Once they've completed the input, they press the "Submit" button.

[1324] Server Processing

[1325] The server receives the JSON data sent from the device. The received data is passed to an AI analysis engine, which converts the data into text format and begins analysis. The generative AI model used is, for example, OpenAI's GPT-3.

[1326] Examples:

[1327] An example of a prompt is as follows:

[1328] Please suggest the best solution for the following requirements:

[1329] Cloud-based data backup

[1330] Low cost

[1331] Easy to set up

[1332] The server searches for the best solution information from a database based on the analyzed keywords. In addition to the internal database, it utilizes external resources (e.g., APIs of cloud service providers).

[1333] The search results are generated as optimal solution recommendations. The recommendations are presented in a user-friendly format. An example recommendation might be, "Amazon S3 - A cost-conscious, recommended cloud-based data backup solution."

[1334] View Suggestions

[1335] The device receives the proposed data sent from the server and displays it to the user, providing detailed information and links so the user can easily take the next action.

[1336] Examples:

[1337] The content displayed on the terminal will be as follows:

[1338] Recommended solutions:

[1339] 1. Amazon S3 - A cost-effective and recommended cloud-based data backup solution.

[1340] [More details here]

[1341] 2. Google Drive - A convenient cloud-based data backup solution that's easy to set up.

[1342] [More details here]

[1343] In this way, the process from user input to server analysis and display on the terminal allows users to efficiently obtain information and improve work efficiency.

[1344] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1345] System program processing flow

[1346] Step 1:

[1347] Users enter their needs and requirements into an input form on their device. For example, they might enter "cloud-based data backup," "low cost," and "easy setup." This input form is written in React and runs on a web browser, with the input data organized in JSON format.

[1348] Input: User needs and requirements (e.g., "cloud-based data backup," "low cost," "easy to set up")

[1349] Output: Cleaned JSON data

[1350] Step 2:

[1351] The device sends the entered JSON data to the server via HTTPS, and this communication is encrypted to ensure security.

[1352] Input: Organized JSON data

[1353] Output: JSON data sent to the server

[1354] Step 3:

[1355] The server receives the JSON data sent from the device. The received data is passed to an AI analysis engine and converted into text format. The generative AI model used here is, for example, OpenAI's GPT-3.

[1356] Input: JSON data received from the terminal

[1357] Output: Data converted to text format

[1358] Step 4:

[1359] The server inputs the converted data into text format into an AI analysis engine, which then analyzes the received text data and extracts important keywords and conditions.

[1360] Input: Data converted to text format (e.g., "Cloud-based data backup," "Low cost," "Easy to set up")

[1361] Output: Extracted keywords and conditions

[1362] Step 5:

[1363] The server searches for the best solution information from an internal database or external resources based on the extracted keywords and conditions, for example, by using a cloud service provider's API to find the relevant solution. This search includes filtering and ranking.

[1364] Input: Extracted keywords or conditions (e.g., "cloud-based," "low-cost," "easy to set up")

[1365] Output: Search results (list of optimal solution information)

[1366] Step 6:

[1367] The server generates optimal solution proposals based on the search results, including specific product or service names and features.

[1368] Input: Search results (list of best solution information)

[1369] Output: Generated recommendations (e.g., "Amazon S3 - Cost-sensitive and recommended cloud-based data backup solutions")

[1370] Step 7:

[1371] The device receives the proposed data sent from the server and displays it to the user, showing detailed information about the proposed solution and related links.

[1372] Input: Proposal data sent from the server

[1373] Output: The recommendation that will be displayed to the user (e.g., "Amazon S3 - A cost-sensitive and recommended cloud-based data backup solution")

[1374] This series of processing steps allows the user to obtain the optimal solution efficiently and quickly.

[1375] (Application example 1)

[1376] 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."

[1377] Conventional food delivery systems have the problem that users must individually search for the type of food they want, their budget, delivery time, etc., which is time-consuming. It is also difficult to quickly and accurately obtain information on the restaurant and menu that best matches the user's criteria. This situation often makes it difficult for users to easily find the food they want, resulting in inconvenience.

[1378] 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.

[1379] In this invention, the server includes input means for a user to input specific needs and requirements, transmission means for transmitting the input needs and requirements to the server, analysis means for analyzing the received needs and requirements, search means for searching for related solution information based on the analysis results, generation means for generating optimal solution proposals from the search results, display means for displaying the generated proposals to the user, and means for inputting conditions such as the user's food preferences, budget, and delivery time and suggesting optimal restaurants and dishes based on these conditions, thereby enabling users to quickly and accurately find dishes and restaurants that meet their desired conditions.

[1380] "User" means any individual or entity that uses the Service or System.

[1381] "Needs" are the demands and desires that users have for specific services or products.

[1382] "Requirements" are the conditions or criteria that a user must meet to meet a particular need.

[1383] "Input means" refers to a device or interface that allows a user to input their needs and requirements into the system.

[1384] "Transmission means" refers to the communication functions and protocols used to send data entered by the user to the server.

[1385] "Analysis means" refers to algorithms or programs for analyzing received needs and requirements and extracting relevant information.

[1386] "Search means" refers to the function of searching for related solutions and data from a database based on the information obtained by the analysis means.

[1387] "Generation means" refers to a function or program for creating optimal proposals based on the information obtained by the search means.

[1388] "Display means" refers to a display or interface for showing the generated suggestions to the user.

[1389] "Cooking preferences" refers to the user's preferences for specific ingredients, cooking methods, etc.

[1390] A "budget" refers to the funds or expenses that a user plans to allocate for purchases or uses.

[1391] "Delivery time" refers to the time it takes from placing an order to completing delivery.

[1392] A "restaurant" is a commercial establishment that serves food and beverages.

[1393] A "prompt" is text that provides instructions or information to a generative AI model.

[1394] MODE FOR CARRYING OUT THE INVENTION

[1395] This invention relates to a system in which a user inputs specific needs and requirements, and an AI analyzes the input content to generate optimal solution proposals. Specific embodiments for implementing this invention are described below.

[1396] System configuration

[1397] User

[1398] Users use a device such as a smartphone to input conditions such as specific food preferences, budget, and delivery time. For example, they can input detailed needs and requirements such as "I want spicy pizza," "under 2,000 yen," and "delivery within 45 minutes."

[1399] Terminal

[1400] The user's input information is sent to the server by the terminal (smartphone or tablet) via a transmission means. The terminal has the function of formatting the data into an appropriate format and sending it to the server as a data packet.

[1401] server

[1402] The server uses a generative AI model to analyze the received user needs and requirements. Specifically, it uses an AI analysis engine (e.g., OpenAI GPT-4) to extract search criteria. The analysis means searches a database for relevant restaurant and cuisine information based on the analyzed keywords and criteria. The server generates appropriate restaurant and menu suggestions based on the analysis results.

[1403] Database

[1404] The database stores data such as menu information, prices, delivery times, etc. The search function allows users to quickly extract information that matches their requirements.

[1405] Generate and view suggestions

[1406] The proposal generated on the server is sent to the user's terminal along with detailed information. The generating means generates an optimal solution (e.g., "Spicy pizza at a nearby pizza place - 1,800 yen"). The display means on the terminal allows the user to quickly and accurately check the proposal.

[1407] Natural language processing explanation

[1408] Specific names of hardware and software

[1409] Hardware: Smartphones, servers (e.g., Amazon AWS)

[1410] Software: Generative AI models (e.g., OpenAI GPT-4), database systems

[1411] Data processing and calculation

[1412] 1. Data reception and analysis: The user enters their food preferences, budget, and delivery time into an input form on their smartphone and sends the information to the server.

[1413] 2. Data transmission: The terminal transmits data to the server by the transmission means.

[1414] 3. Data analysis: The AI ​​analysis engine on the server analyzes the data and searches the database for restaurant information that meets the criteria.

[1415] 4. Proposal generation: Using the generation method, the AI ​​generates optimal restaurant and menu suggestions and provides feedback to the user.

[1416] Adding specific examples

[1417] Specific examples

[1418] When a user types, "I want a spicy pizza that costs under 2,000 yen and can be delivered within 45 minutes," the AI ​​searches for nearby restaurants that meet the criteria and generates suggestions such as "Spicy pizza from Pizza Shop X - 1,800 yen."

[1419] Prompt Sentence Examples

[1420] The user entered the following criteria:

[1421] Cuisine: Pizza

[1422] Budget: Under 2000 yen

[1423] Delivery time: within 45 minutes

[1424] Specific requirements: Spicy

[1425] Based on this, please suggest the best restaurant and menu.

[1426] By implementing the present invention based on the above aspects, a user can quickly and accurately find food and restaurants that meet his or her desired conditions.

[1427] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1428] Step 1:

[1429] Users input criteria such as specific food preferences, budget, and delivery time into a form on their smartphone. For example, they enter detailed requirements such as "pizza," "under 2000 yen," "within 45 minutes," and "spicy." This input data is organized as a data packet in JSON format.

[1430] input:

[1431] Types of cuisine

[1432] budget

[1433] Delivery time

[1434] Specific requirements

[1435] output:

[1436] Organized data packets (e.g., JSON format)

[1437] Operation:

[1438] The user operates the input form on the smartphone and enters the required conditions.

[1439] Step 2:

[1440] The terminal sends the input data packet to the server using a communication protocol such as an HTTP POST request. At this time, the data entered in the input form is sent to the server appropriately.

[1441] input:

[1442] Reordered data packets (output of step 1)

[1443] output:

[1444] Data packets sent to the server

[1445] Operation:

[1446] The device formats the data appropriately and sends it to the server.

[1447] Step 3:

[1448] The server passes the received data packets to an analysis engine (e.g., a generative AI model). The analysis engine extracts important keywords and conditions based on the input data. For example, it might extract keywords such as "pizza," "under 2,000 yen," "within 45 minutes," and "spicy."

[1449] input:

[1450] Received data packets (output of step 2)

[1451] output:

[1452] Extracted keywords and conditions

[1453] Operation:

[1454] The server uses a generative AI model to analyze the input data and obtain important keywords and conditions.

[1455] Step 4:

[1456] The server searches the database for relevant restaurant and food information based on the keywords and conditions extracted by the analysis engine. For example, it searches for restaurants that meet the conditions "pizza," "under 2,000 yen," "within 45 minutes," and "spicy."

[1457] input:

[1458] Extracted keywords and conditions (output of Step 3)

[1459] output:

[1460] Restaurant and food information extracted from the database

[1461] Operation:

[1462] The server performs a database search and extracts information that matches the criteria.

[1463] Step 5:

[1464] The server generates optimal suggestions based on the search results. The generation means creates suggestions suitable for the user, such as "Spicy pizza from pizza shop Y - 1800 yen."

[1465] input:

[1466] Restaurant and dish information extracted from the database (output of step 4)

[1467] output:

[1468] Optimal proposal content

[1469] Operation:

[1470] The server puts together the best suggestions and generates the information to show the user.

[1471] Step 6:

[1472] The generated suggestions are sent to the terminal and are fed back to the user via the display means. The user can check the suggestions and use them as a reference for deciding what to order.

[1473] input:

[1474] Optimal proposal (output of step 5)

[1475] output:

[1476] Displaying suggestions to users

[1477] Operation:

[1478] The server sends the generated proposals to the terminal, which displays them to the user.

[1479] As a result, users can quickly and accurately obtain suggestions for dishes and restaurants that meet their desired conditions.

[1480] 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.

[1481] System Overview

[1482] This invention combines an emotion engine with a system in which users input their specific needs and requirements, and AI analyzes the input to generate optimal solution proposals. This system allows users to obtain accurate solution information in a short amount of time, and by making proposals that take the user's emotions into consideration, it is possible to provide more appropriate and satisfying solutions.

[1483] Specific operation of the system

[1484] This system is composed of three main elements: the user, the device, and the server. By incorporating an emotion engine, it is possible to realize suggestions based on the user's emotional state. The specific operation of each element is explained below.

[1485] User Operation

[1486] 1. Use of the input form

[1487] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup."

[1488] 2. Confirm your input

[1489] Users can review the input and make corrections or additions as necessary, allowing them to specify the conditions for the desired solution in detail.

[1490] Terminal handling

[1491] 1. Data transmission

[1492] The terminal sends the user's input information to the server, organized as data packets.

[1493] 2. Emotional Engine Activation

[1494] The device sends the user's facial expression and voice data to the emotion engine, which analyzes the user's emotions. For example, it uses a camera and microphone to detect the user's smile, tone of voice, stress level, etc.

[1495] Server Processing

[1496] 1. Data Reception and Analysis

[1497] The server receives the data packets sent from the device and the emotion data from the emotion engine, and passes them to the AI ​​analysis engine.

[1498] An AI analytics engine analyzes the received data and extracts relevant keywords, conditions, and emotional states, such as "cloud-based," "data backup," "low cost," "easy to set up," and "high stress."

[1499] 2. Database Search

[1500] The server searches for relevant solution information from an internal database or external resources based on the keywords, conditions, and emotional data extracted by the analysis means.

[1501] For example, it detects information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-setup cloud-based data backup solutions."

[1502] 3. Proposal Generation

[1503] The server uses the generation means to generate optimal solution proposals for the user based on the search results and emotion data. For example, if the user is in a high stress state, the server will prioritize proposing easier and less time-consuming solutions.

[1504] It generates detailed proposals such as "Amazon S3 - cost-conscious, easy to set up" and "Google Drive - convenient and easy to use."

[1505] View Suggestions

[1506] 1. Displaying the results

[1507] The device displays the proposed data sent from the server to the user, who can then review the proposal and take next steps to request more information or take specific actions.

[1508] For example, suggestions like "Amazon S3 - A cost-effective, recommended cloud-based data backup solution" are displayed, along with detailed documentation and links.

[1509] Specific Examples

[1510] As a concrete example, consider a user who needs a "cloud-based data backup solution" and is looking for a solution that is low-cost and easy to set up. The user enters their requirements, and the device sends the information to the server. Then, an emotion engine recognizes the user's high stress level from their facial expressions and voice. The server uses an analysis engine to search a database for optimal solution information and generates suggestions that take the user's emotional state into account. Finally, the device displays suggestions such as "Amazon S3" and "Google Drive" to the user, allowing the user to quickly find the optimal solution.

[1511] In this way, by using this system, users can not only obtain information efficiently and achieve work efficiency, but also improve satisfaction through suggestions that take their emotional state into consideration.

[1512] The processing flow will be explained below.

[1513] Step 1:

[1514] Users enter their needs and requirements using an input form.

[1515] The device displays a form for users to enter details about the solution they are looking for, such as "cloud-based data backup," "low cost," and "easy setup."

[1516] Step 2:

[1517] The user checks the input information and makes corrections or additions as necessary.

[1518] The terminal displays a confirmation screen for the user to confirm the input, and the user can check whether the input needs and requirements are correct and make corrections or additions if necessary. For example, change "low cost" to "minimum cost."

[1519] Step 3:

[1520] The terminal transmits the input information to the server.

[1521] After the user confirms the input, the terminal sends the information organized as a data packet to the server, where the input conditions are included in the data packet.

[1522] Step 4:

[1523] The device sends the user's facial expressions and voice data to an emotion engine to recognize the user's emotions.

[1524] The device sends the user's facial expressions and voice via a camera and microphone to the emotion engine, which then analyzes the user's emotional state. For example, it examines smiles, tone of voice, and stress levels, and recognizes them as "high stress."

[1525] Step 5:

[1526] The server receives the data packets and analyzes them using the analysis means.

[1527] The server receives the data packets and emotion data sent from the device and passes them to the AI ​​analysis engine. The AI ​​analysis engine analyzes the received data and extracts related keywords and conditions, such as "cloud-based," "data backup," "low cost," "easy to set up," and "high stress."

[1528] Step 6:

[1529] Based on the analysis results, the server searches for solution information from resources inside and outside the database.

[1530] The server searches for relevant solution information from an internal database or external resources based on the keywords, conditions, and sentiment data extracted by the analysis method. For example, it searches for information such as "Amazon S3," "Google Drive," and "Microsoft OneDrive" as "low-cost, easy-to-configure cloud-based data backup solutions."

[1531] Step 7:

[1532] The server generates an optimal solution proposal.

[1533] The server generates optimal solution suggestions for the user based on the acquired information and emotional data. For example, if the user is in a high-stress state, it will prioritize solutions that are easier and less time-consuming. It generates detailed suggestions such as "Amazon S3 - cost-conscious, easy to set up" or "Google Drive - convenient and easy to use."

[1534] Step 8:

[1535] The server transmits the generated proposal data to the terminal.

[1536] The server transmits the generated proposal data to the terminal so that the user can confirm it. The transmitting means transmits a data packet including the proposal content to the terminal.

[1537] Step 9:

[1538] The device displays the suggestions to the user.

[1539] The device receives the proposed data from the server and displays it to the user. The user can then review the proposed solution and view detailed information on the device screen. For example, the device may display a suggestion such as "Amazon S3 - A cost-effective, recommended cloud-based data backup solution," along with detailed documentation and links.

[1540] In this way, each step ensures a smooth process from user input to the proposal of the optimal solution. In addition, by combining it with an emotion engine, it is possible to make more appropriate proposals that take into account the user's emotional state.

[1541] Example 2

[1542] 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."

[1543] In conventional systems, users can input their specific needs and requirements and then propose optimal solutions based on the results. However, proposals are often made without taking into account the user's emotional state. This can leave users feeling stressed or dissatisfied, and there are issues with the quality of proposals and satisfaction not being sufficiently improved.

[1544] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes an input means for the user to input specific needs and requirements, a transmission means for transmitting the input needs and requirements to the server, an emotion analysis means for analyzing the emotional state of the user on the terminal, an analysis means for analyzing the received needs, requirements, and emotional state, a search means for searching for related solution information based on the analysis results, a generation means for generating an optimal solution proposal taking into account the search results and the user's emotional state, and a display means for displaying the generated proposal to the user. This makes it possible to propose an appropriate solution according to the user's emotional state, thereby improving user satisfaction.

[1545] "Input means" is an interface through which a user inputs their specific needs and requirements.

[1546] "Transmission means" is a function for transmitting input needs and requirements to a server.

[1547] The "emotion analysis means" is a function for analyzing the user's emotional state from facial expressions, voice, etc.

[1548] "Analysis means" is a device or software for analyzing received needs, requirements and emotional states.

[1549] The "search means" is a function for searching for related solution information based on the analysis results.

[1550] The "generation means" is a function for generating optimal solution proposals taking into account the search results and the emotional state of the user.

[1551] The "display means" is an interface for displaying the generated solution proposal to the user.

[1552] A "server" is a computer device that receives user needs, requirements, and emotional data, analyzes, searches, and generates suggestions.

[1553] A "terminal" is a device that a user uses to input their needs and requirements and analyze emotional data.

[1554] This invention combines an emotion engine with a system in which a user inputs specific needs and requirements, and a server analyzes those needs and requirements to generate optimal solution proposals. Specifically, it consists of three main elements: the user, the terminal, and the server.

[1555] User Operation

[1556] Users enter their needs and requirements using a form displayed on their device, such as "cloud-based data backup," "low cost," and "easy setup." They can then review their input and make corrections or additions if necessary. The more accurate and detailed this information is, the more likely it is that the optimal solution will be suggested.

[1557] Terminal handling

[1558] The device organizes the user's input information into data packets and sends them to the server. Communication protocols such as HTTP POST requests are used for data transmission. Furthermore, the device uses an emotion engine to collect the user's facial expressions and voice data and analyze their emotional state. Specifically, the device collects data using the built-in camera and microphone, and analyzes it using an emotion recognition API (e.g., a general emotion recognition platform).

[1559] Server Processing

[1560] The server receives the data packets and sentiment analysis data sent from the device and passes them to the analysis engine. The analysis engine uses an NLP library (e.g., a general natural language processing library) to extract relevant keywords, conditions, and emotional states from the received data. Next, a search function runs to search for relevant solution information based on the analysis results. SQL queries and API calls are used for database searches.

[1561] The server then generates optimal solution proposals based on the search results and the user's emotional state. A template engine (e.g., a general template engine) is used to generate the proposals, forming specific proposal content. If the user is in a high-stress state, easier and less time-consuming solutions are prioritized.

[1562] View Suggestions

[1563] The device receives the recommendations sent from the server and displays them to the user, either as a web browser widget or a dedicated application. The user can review the recommendations and select next steps for more information or specific actions. For example, a recommendation might be "Amazon S3 - a cost-conscious, recommended cloud-based data backup solution," with corresponding detailed documentation and links provided.

[1564] Examples and prompts

[1565] As a concrete example, consider a situation where a user in need of a "cloud-based data backup solution" is looking for a solution that is low-cost and easy to set up. The user enters their requirements, and the device sends that information to the server. An emotion engine then recognizes the user's high stress level from their facial expressions and voice. The server uses an analysis engine to search a database for optimal solution information and generates suggestions that take the user's emotional state into account. Finally, the device displays suggestions such as "general cloud storage services" to the user, allowing the user to quickly find the optimal solution.

[1566] Example prompt sentence:

[1567] Generate a proposal for a high-stress user looking for a cloud-based data backup solution that is low-cost and easy to set up.

[1568] By using this system, users can not only obtain information efficiently and achieve work efficiency, but also improve satisfaction through suggestions that take their emotional state into account.

[1569] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1570] Step 1:

[1571] The user enters their needs and requirements using an input form displayed on the device. The input information includes "cloud-based data backup," "low cost," and "easy setup." This clearly defines the user's requirements. For example, if a user enters "low cost, easy setup cloud storage," the requirement is recorded as data.

[1572] Step 2:

[1573] The user checks the input and makes corrections or additions as necessary. The input in this step is a review and correction of the information entered in the previous step. For example, by changing "low cost" to "annual cost less than $100," more specific requirements are determined. This checked and corrected data is passed to the next step as the final output.

[1574] Step 3:

[1575] The device sends the organized user input information to the server, formatted as a data packet in JSON or XML format. For example, a requirement for "low-cost cloud-based data backup" is sent to the server using an HTTP POST request. The input in this step is the user's requirement information, and the output is a data packet sent to the server.

[1576] Step 4:

[1577] At the same time, the device starts an emotion engine, collecting and analyzing the user's facial expressions and voice data. The data is captured using a camera and microphone, and analyzed using an emotion recognition API (e.g., a general emotion recognition platform). The analysis result is an emotional state such as "high stress" or "moderate." This analyzed emotion data is also sent to the server. The input is the original emotional state data, and the output is the analyzed emotion data.

[1578] Step 5:

[1579] The server receives data packets and emotional data sent from the device and passes them to the AI ​​analysis engine. The received data is in JSON or XML format and is fed to the analysis engine. For example, an NLP library (e.g., a general natural language processing library) is used to extract keywords and conditions such as "cloud-based," "low cost," and "easily configurable," as well as the emotional state ("high stress"). The input of this step is the user's requirements and emotional data, and the output is the extracted keywords and emotional state.

[1580] Step 6:

[1581] The server searches for relevant solution information from databases and external resources based on the analyzed keywords, conditions, and sentiment data. It uses SQL queries and API calls to retrieve entries containing, for example, "low-cost, easy-to-configure cloud backup solutions." The input is the analysis results, and the output is the searched solution information.

[1582] Step 7:

[1583] The server uses a template engine (e.g., a general template engine) to generate optimal solution proposals based on the search results and sentiment data. For example, it generates proposals such as "Amazon S3 - cost-effective and easy to set up" and "Google Drive - convenient and easy to use." Since the user is in a high-stress state at this time, it prioritizes simpler solutions. The generated proposals are formatted in a format appropriate for the user. The inputs are search results and sentiment data, and the output is the generated proposal text.

[1584] Step 8:

[1585] The terminal receives the generated recommendation data from the server and displays it to the user. The display format can be a web browser widget or a dedicated application. For example, the recommendation content may be "Amazon S3 - A cost-conscious, recommended cloud-based data backup solution" and provide a link to more information. The input is the generated recommendation text, and the output is a visual display to the user.

[1586] Through these processing steps, users are efficiently offered solutions that meet their requirements and can achieve higher satisfaction because the suggestions take into account the user's emotional state.

[1587] (Application example 2)

[1588] 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."

[1589] Conventional solution proposal systems were able to make optimal proposals based on the user's needs and requirements, but they were unable to take the user's emotional state into consideration. As a result, they were unable to make proposals that were optimized for the user's psychological state, such as high stress or relaxed state, which led to a problem of reduced user satisfaction.

[1590] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes emotion analysis means for analyzing the user's emotions, means for adjusting the solution proposal based on the emotion analysis results, and analysis means for analyzing the received needs and requirements. This makes it possible to propose an optimal solution based on the user's emotional state.

[1591] "Input means" refers to the means by which a user inputs their specific needs and requirements.

[1592] The "transmission means" is a means for transmitting the input needs and requirements to the server.

[1593] "Analysis means" is a means for analyzing received needs and requirements.

[1594] The "search means" is a means for searching for related solution information based on the analysis results.

[1595] The "generation means" is a means for generating an optimal solution proposal from the search results.

[1596] The "display means" is a means for displaying the generated proposal to the user.

[1597] The "emotion analysis means" is a means for analyzing the user's emotions.

[1598] "Adjustment means" refers to a means for adjusting a solution proposal based on the results of sentiment analysis.

[1599] A "database" is a data storage device for storing information on each solution.

[1600] The present invention is a system that proposes optimal solutions taking into account the emotional state of the user. The system consists of the following main components:

[1601] 1. System Configuration

[1602] User Operation

[1603] The user uses the input means to input their specific needs and requirements. For example, they can input the genres and conditions they want to watch on the "content distribution service." Furthermore, a camera and microphone are used to collect facial expressions and voice data, and an emotion analysis means is used to analyze the user's emotions.

[1604] Terminal handling

[1605] The input means is used to collect needs and requirements from the user, which are then transmitted to the server by the transmission means. The collected facial expression and voice data is analyzed by the emotion analysis means and transmitted to the server as emotion data.

[1606] Server Processing

[1607] The server analyzes the needs and requirements data and emotion analysis data received by the transmission means using the analysis means. Based on the analysis results, related solution information is searched for using the search means. The searched information is generated as an optimal solution proposal by the generation means. An adjustment means adjusts the proposal content based on the emotion analysis data to generate a proposal that is optimal for the user's emotional state. In addition, each piece of solution information is stored in a database.

[1608] View Suggestions

[1609] The final solution proposal is displayed to the user using a display means, and the user can check the proposal, obtain more detailed information, or take specific actions.

[1610] 2. Working Example

[1611] For example, suppose a user wants to watch an "action movie" on a streaming service. The user inputs this request using the input means, and the input data is sent to the server. At the same time, an emotion analysis means using a camera and microphone analyzes the user's emotional state and determines, for example, that the user is in a "high stress state." Based on this, the server analyzes the received data using the analysis means and searches for information on related action movies using the search means.

[1612] Based on these search results, the generation means generates a suggestion of an action movie that will help the user relax. For example, instead of "action movies that get you excited," the generation means may adjust the suggestion to "action movies that are relaxing." The display means then displays the most suitable suggestion to the user. The user can then decide whether to watch the suggested movie.

[1613] In this way, using emotion analysis makes it possible to make suggestions that are tailored to the user's psychological state, thereby improving user satisfaction.

[1614] 3. Example prompts

[1615] For example, the following could be entered as a specific example of a prompt sentence for a generative AI model:

[1616] "If the user says they want to watch an action movie, and their current emotion is analyzed as high stress, generate recommendations for relaxing action movies based on this data."

[1617] The above is a specific embodiment of the present invention. This system makes it possible to propose optimal solutions according to the emotional state of the user.

[1618] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1619] Step 1:

[1620] The user uses an input means to input their specific needs or requirements. For example, the user may input a need such as "I want to watch an action movie," and the input data is captured by the terminal. The input acts as text data, which is used for further processing.

[1621] Step 2:

[1622] The terminal sends the input data of needs and requirements to the server. Using the transmission means, text data is sent to the server, and the server receives this data. The input data is packetized in JSON format and sent.

[1623] Step 3:

[1624] The device collects the user's facial expressions and voice data and analyzes their emotional state using emotion analysis means. Using a camera and microphone, the emotion engine analyzes the user's emotions based on the collected data. The analysis results in emotional states such as "high stress" and "relaxed."

[1625] Step 4:

[1626] The server uses an analysis means to analyze the needs and requirements data and emotion analysis data received from the terminal. The received text data and emotion data are passed to the analysis means, which extracts keywords from the input content and analyzes the emotional state.

[1627] Step 5:

[1628] Based on the keywords and emotion data extracted by the analysis means, the search means searches the database for related solution information. For example, a search is performed using the keywords "action movie" and "relaxation" to collect related information.

[1629] Step 6:

[1630] The server uses the generation means to generate optimal solution proposals based on the information collected by the search means. The generation means selects optimal solutions and constructs proposals based on the collected information and emotion data. For example, a list of "relaxing action movies" is generated.

[1631] Step 7:

[1632] The generated solution proposals are adapted to the sentiment analysis results using a tuning mechanism that further refines the proposals and restructures them to best suit the user's current emotional state.

[1633] Step 8:

[1634] The final proposal is sent from the server to the terminal and displayed to the user using the display means, allowing the user to visually confirm the proposal and decide on an action based on it.

[1635] These are the specific processing steps of the system that proposes optimal solutions based on the user's needs and emotional state.

[1636] 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.

[1637] 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.

[1638] 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 robot 414.

[1639] 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.

[1640] FIG. 9 illustrates 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 behaviors 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.

[1641] 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.

[1642] 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).

[1643] 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.

[1644] 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."

[1645] 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.

[1646] 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).

[1647] 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.

[1648] 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.

[1649] 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.

[1650] 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.

[1651] 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.

[1652] 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.

[1653] 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.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] The following is further disclosed regarding the above embodiment.

[1658] (Claim 1)

[1659] input means for the user to input their specific needs and requirements;

[1660] a transmitting means for transmitting the input needs and requirements to a server;

[1661] analytical means for analyzing received needs and requirements;

[1662] a search means for searching for related solution information based on the analysis results;

[1663] a generating means for generating an optimal solution proposal from the search results;

[1664] The system includes a display means for displaying the generated suggestions to a user.

[1665] (Claim 2)

[1666] 10. The system of claim 1, further comprising means for providing an input form for a user to input.

[1667] (Claim 3)

[1668] 10. The system of claim 1, further comprising a database for storing each solution information.

[1669] "Example 1"

[1670] (Claim 1)

[1671] input means for the user to input their specific needs and requirements;

[1672] a transmitting means for transmitting the input needs and requirements to the information processing device;

[1673] analytical means for analyzing received needs and requirements;

[1674] A search means for searching for related solution information based on the analysis results;

[1675] A generating means for generating an optimal solution proposal from the search results;

[1676] The system includes a display means for displaying the generated suggestions to a user.

[1677] (Claim 2)

[1678] 10. The system of claim 1, further comprising means for providing an input form for a user to input.

[1679] (Claim 3)

[1680] 10. The system of claim 1, further comprising a storage device for storing each solution information.

[1681] "Application Example 1"

[1682] (Claim 1)

[1683] input means for the user to input their specific needs and requirements;

[1684] a transmitting means for transmitting the input needs and requirements to a server;

[1685] analytical means for analyzing received needs and requirements;

[1686] a search means for searching for related solution information based on the analysis results;

[1687] a generating means for generating an optimal solution proposal from the search results;

[1688] display means for displaying the generated suggestions to the user;

[1689] A means to suggest optimal restaurants and dishes based on user input such conditions as food preferences, budget, and delivery time.

[1690] A system including:

[1691] (Claim 2)

[1692] 10. The system of claim 1, further comprising means for providing an input form for a user to input.

[1693] (Claim 3)

[1694] 10. The system of claim 1, further comprising a database for storing each solution information.

[1695] "Example 2: Combining Emotion Engines"

[1696] (Claim 1)

[1697] input means for the user to input their specific needs and requirements;

[1698] a transmitting means for transmitting the input needs and requirements to a server;

[1699] emotion analysis means for analyzing the emotional state of a user on the terminal;

[1700] analytical means for analyzing received needs, requirements and emotional states;

[1701] a search means for searching for related solution information based on the analysis results;

[1702] a generating means for generating an optimal solution proposal taking into account the search results and the emotional state of the user;

[1703] The system includes a display means for displaying the generated suggestions to a user.

[1704] (Claim 2)

[1705] 10. The system of claim 1, further comprising means for providing an input form for a user to input.

[1706] (Claim 3)

[1707] 10. The system of claim 1, further comprising a database for storing each solution information.

[1708] "Application example 2 when combining emotion engines"

[1709] (Claim 1)

[1710] input means for the user to input their specific needs and requirements;

[1711] a transmitting means for transmitting the input needs and requirements to a server;

[1712] analytical means for analyzing received needs and requirements;

[1713] a search means for searching for related solution information based on the analysis results;

[1714] a generating means for generating an optimal solution proposal from the search results;

[1715] display means for displaying the generated suggestions to the user;

[1716] emotion analysis means for analyzing the emotions of a user;

[1717] The system includes a means for adjusting solution proposals based on sentiment analysis results.

[1718] (Claim 2)

[1719] 10. The system of claim 1, further comprising means for providing an input form for a user to input.

[1720] (Claim 3)

[1721] 10. The system of claim 1, further comprising a database for storing each solution information. [Explanation of symbols]

[1722] 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. input means for the user to input their specific needs and requirements; a transmitting means for transmitting the input needs and requirements to a server; analytical means for analyzing received needs and requirements; a search means for searching for related solution information based on the analysis results; a generating means for generating an optimal solution proposal from the search results; and display means for displaying the generated suggestions to the user.

2. 10. The system of claim 1, further comprising means for providing an input form for user input.

3. The system of claim 1 further comprising a database for storing each solution information.

Images