system

Abstract

We provide the system. [Solution] A means of receiving information about consultations from users, A search means for obtaining relevant vendor information from a database based on the aforementioned consultation content, An evaluation method for assigning reliability ratings to acquired vendor information, A transmission means for sending evaluated vendor information to the user's terminal, A means of updating the database to save user selection information, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] An object of the present invention is to solve the problem that it is difficult to find reliable merchants or services in a region. Another problem is to reduce the risk of inappropriate service selection due to insufficient information or inaccurate evaluation, and to enable the provision of reliable life support services in a society with an increasing aging population and single-person households.

Means for Solving the Problems

[0005] This invention provides a search means for receiving consultation content from a user and retrieving relevant service provider information from a database based on that content. Furthermore, it includes a transmission means for assigning a reliability rating to the retrieved service provider information using an evaluation means for assessing reliability, and for transmitting the evaluated service provider information to the user's terminal. This makes it possible to select service providers based on highly reliable information, thereby improving the quality of community-based support. In addition, by updating the database with the user's selection information, the system ensures that service provider information is always provided in its most up-to-date state.

[0006] A "user" is an individual or legal entity that wishes to use the system for consultation or to utilize the services.

[0007] "Consultation content" refers to the specific problems or requests that users seek to resolve through the system.

[0008] "Receiving means" refers to the function or process within the system that receives the content of inquiries from users.

[0009] A "provider" is an organization or individual business owner that provides a specific service.

[0010] A "database" is a digital information storage system used to accumulate and manage vendor information and evaluation data.

[0011] "Search method" refers to a function or process for identifying and extracting necessary vendor information from a database.

[0012] "Reliability evaluation" refers to the results of assessing the quality and reliability of services provided by a vendor using numerical values ​​and criteria.

[0013] "Evaluation method" refers to a function or process that judges and quantifies the reliability of a business based on multiple criteria.

[0014] "Transmission means" refers to a function or process that delivers evaluated vendor information to the user's terminal.

[0015] The "terminal" is a digital device used to utilize the system, including personal computers and smartphones.

[0016] The "selection information" is information on the merchant or service content selected by the user on the system.

[0017] The "updating means" is a function or process that records new information and selection status in the system's database to maintain the accuracy and currency of the information.

Brief Description of Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing apparatus and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing apparatus and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing apparatus and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing apparatus and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] This invention aims to build an integrated platform for providing reliable community-based support services. The system operates through a program and functions through the cooperation of users, terminals, and servers.

[0040] First, users use their devices to input information about problems or inquiries that have occurred in their area. For example, if a user wants "air conditioner repair," they use their device to fill in the details of the inquiry and the desired service, and then submit the request.

[0041] Next, the terminal sends the user's input to the server. The server receives this information and retrieves relevant vendor information from its database. Specifically, it filters for vendors related to "air conditioner repair" and organizes the results.

[0042] The server performs a reliability assessment on the acquired vendor information. This assessment considers factors such as past performance, customer reviews, and feedback from the local community. This assessment allows for the definition of a vendor's reliability rank.

[0043] The server then sends the evaluation results along with detailed information about the vendors to the user's device. The user can then review this information on their device and select their preferred vendor.

[0044] When a user selects a service provider, the device reports the selection information to the server. This information is recorded in a database by the server and used for future evaluation updates and service improvements.

[0045] Furthermore, user feedback and selection information are automatically reflected in the database, contributing to further improvements in service quality. This system facilitates the provision of community-based services and serves as an effective means of quickly resolving household and equipment-related issues.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] Users use their devices to enter their inquiry details and residential area information into a dedicated input form. For example, if they want to request a water leak repair, they enter that information, fill in the necessary details, and press the submit button.

[0049] Step 2:

[0050] The terminal organizes the input data and sends it to the server using a secure communication protocol. During this process, the data is encrypted to maintain confidentiality.

[0051] Step 3:

[0052] The server searches its database for relevant service providers based on the consultation details and regional information received from the terminal. The server executes a query and lists the relevant service providers.

[0053] Step 4:

[0054] The server performs a reliability assessment on the acquired vendor information. This assessment uses factors such as the vendor's past performance, feedback from evaluation agencies, and customer reviews. A reliability rank is then assigned to each vendor.

[0055] Step 5:

[0056] The server reorganizes vendor information, adding reliability ratings, and sends it to the user's terminal. This information package includes vendor contact information, available services, and pricing.

[0057] Step 6:

[0058] The user reviews the transmitted vendor information on their device and selects their preferred vendor. The user then examines the details and makes a decision to proceed with a specific service request.

[0059] Step 7:

[0060] The terminal then resends the user's selected vendor information to the server. This includes the ID of the selected vendor and the associated query details.

[0061] Step 8:

[0062] The server receives user selection information and records it in the database. This information is useful for future evaluation updates and improving vendor reliability, leading to an overall improvement in system quality.

[0063] (Example 1)

[0064] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0065] There is a need for a platform that can provide life support services that can respond quickly and reliably to the diverse challenges and needs faced by users in their communities. However, with conventional systems, it has been difficult to quickly find reliable service providers, and there have been limitations in improving user satisfaction.

[0066] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0067] In this invention, the server includes a device for receiving the content of a problem from a user, a device for acquiring relevant vendor information from an information source based on the content of the problem, and a device for storing the user's selection information and updating the information source. This makes it possible to quickly acquire highly reliable vendor information and propose it to the user.

[0068] A "user" is an individual or organization that uses the system to input their issues and needs and receives services from that system.

[0069] A "receiving device" is a device that receives the task details from the user in digital format and passes them on to the next processing device.

[0070] A "source of information" refers to a database or other information provider that the system accesses to obtain vendor information.

[0071] An "acquisition device" is a device used to retrieve relevant vendor information from information sources based on the content of the received issue.

[0072] An "evaluation device" is a device that assigns reliability based on acquired vendor information, taking into account past performance and evaluations.

[0073] A "transmission device" is a device that has the function of transmitting evaluated vendor information to the user's device.

[0074] A "storage device" is a device that records user selection information and uses it for future data analysis and system improvement.

[0075] An "update device" is a device that keeps information sources up-to-date based on user selections and feedback.

[0076] "Feedback information" refers to information received from users regarding their evaluations of services and vendors, as well as suggestions for improvement.

[0077] "Reliability evaluation" is an assessment that expresses the reliability of a service provider as a numerical value or rank, and is an important indicator for users when choosing a service provider.

[0078] This system is an integrated platform for effectively providing local life support services, with users, terminals, and servers working together. The system is designed to quickly resolve the wide range of challenges users may encounter.

[0079] Users input task details via a dedicated application using devices such as smartphones or computers. This input includes specific service requests, such as "I would like to request air conditioner repair." The entered task details are transmitted to a server via the internet.

[0080] The server analyzes the received issue and retrieves relevant vendor information from a database or other sources. Based on the vendor information, the server performs a reliability assessment and uses an algorithm to calculate a rating rank for each vendor. This algorithm takes into account past performance, rating scores, and feedback from the local community.

[0081] Next, the server organizes the evaluated vendor information and sends it back to the terminal, helping the user select a trustworthy vendor. The user selects the best vendor from the provided list and reports their selection to the server. This information is stored in a database and used to update vendor ratings and improve services in the future.

[0082] As a concrete example, when a user requests a "garden pruning service," they enter their request into a terminal and send it to the server. The server filters highly-rated gardeners in the area and presents them to the user along with their reliability ranking. The user can then select from the list and utilize the service.

[0083] The generative AI model is used by the system to learn from external data and suggest the most suitable vendors. An example of a prompt might be: "Explain how the server evaluates vendor reliability and presents appropriate options to the user on a service platform specializing in local problem solving." Through this implementation, the system supports the provision of fast, reliable services tailored to local needs.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user opens a dedicated application on their device, enters the details of the problem or inquiry, and presses the submit button. The input includes a specific request, such as "I would like to request air conditioner repair." The device then formats the user's request data and sends it to the server via the internet.

[0087] Step 2:

[0088] The server receives data sent from the terminal and analyzes its contents. It receives user requests as input and extracts keywords using its analysis engine. Specifically, based on the keyword "air conditioner repair," it instructs the server to retrieve relevant contractor information from the database.

[0089] Step 3:

[0090] The server performs a database search to retrieve relevant vendor information. Using the extracted keywords as input, it filters the database to obtain a list of "air conditioner repair" vendors. As output, it creates a list of vendors that appear to be reliable.

[0091] Step 4:

[0092] The server applies a reliability evaluation algorithm to the acquired vendor information. The input consists of the vendor's past performance and customer evaluation data. By performing data calculations, the server assigns a rank to each vendor and outputs the evaluation result by calculating the reliability rank.

[0093] Step 5:

[0094] The server organizes vendor information with reliability rankings and prepares it for transmission to the terminal. As input, it processes the ranked vendor list and formats it into a user-friendly format. As output, it creates vendor information to be sent to the terminal.

[0095] Step 6:

[0096] The user reviews the list of rated service providers displayed on the terminal and selects the service provider they wish to use. The terminal then confirms the information of the selected service provider and sends it to the server as output.

[0097] Step 7:

[0098] The terminal sends the selected vendor information to the server, which receives it and stores it in a database. The input includes the selected vendor information, which is stored for future service improvements and reliability evaluation updates. The output is the updated database.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] To provide prompt and reliable life support services in local communities, it is necessary to have information on appropriate products and services that meet the needs of users. However, the current system is insufficient in obtaining the information users need and in evaluating the reliability of service providers, making it difficult to achieve satisfactory results for users. To solve this problem, it is necessary to build a system that provides accurate and reliable information quickly and improves convenience.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes a receiving means using a terminal device that receives inquiries from users, a search means for obtaining relevant provider information from an information recording medium based on the inquiries, and an evaluation means for assigning a reliability rating to the obtained provider information. This makes it possible to quickly select products and services that users need within their region and provide the information while ensuring its reliability.

[0104] A "terminal device" is a portable information processing device used by users to input and receive information.

[0105] An "information recording medium" is a data storage device or medium used to store provider information and reliability data, and to retrieve them.

[0106] "Reliability assessment" is the process of quantifying or ranking the trustworthiness of a provider based on factors such as the provider's track record, customer reviews, and opinions from evaluation organizations.

[0107] A "portable information processing device" is a device that can process and communicate information while being mobile, and includes smartphones and tablets.

[0108] "Selection" is the process of finding the appropriate information or item from among multiple pieces of information based on specified criteria.

[0109] An "evaluation body" is a professional institution or organization that evaluates goods or services based on specific criteria.

[0110] The system for implementing this invention mainly consists of the cooperation of a server, a terminal device, and a mobile information processing device. The user uses a mobile information processing device (e.g., a smartphone) to input their desire to acquire local products and services. The terminal device receives this input information and transmits it to the server.

[0111] Based on the received information, the server searches for relevant provider information from the information storage medium. This includes retrieving details of commercially available products and information on local service providers from the database. An evaluation method is used to assign a reliability rating to the retrieved provider information. This evaluation method calculates the reliability of the provider by considering feedback from evaluation organizations and past performance.

[0112] Finally, the server sends the evaluated provider information to the user's mobile device. This allows the user to easily view reliable information and select the services and products they need.

[0113] For example, if a user requests information on "recommended refrigerator items," the server will list highly-rated products in the area and send that information to the user. This allows users to efficiently select products both inside and outside the store.

[0114] An example of a prompt to be input into the generating AI model is: "The user inputs an inquiry about products or services they want in the store. The server performs a reliability evaluation and returns the results to the app, allowing the user to make the best choice. How can this process be made more effective?" This invention enables the provision of locally focused information and improves user convenience.

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The user uses a mobile information processing device to input details about the desired product or service. The entered information is received by a terminal device. The data entered consists of details about the desired product or service.

[0118] Step 2:

[0119] The terminal sends the received consultation details to the server. Based on this information, the server searches for relevant provider information from its information storage medium. The input here is the consultation details from the user, and the output is provider information. The server uses a search algorithm to extract highly relevant provider information.

[0120] Step 3:

[0121] The server performs a reliability assessment on the acquired provider information. This process assigns a reliability score to providers based on feedback from multiple evaluation organizations and past usage data. The input is provider information and reliability evaluation criteria, while the output is provider information with assigned reliability scores.

[0122] Step 4:

[0123] The server transmits the evaluated provider information to the user's mobile information processing device. The user then selects products or services based on the received information. The input here is provider information, including reliability ratings, and the output is detailed information displayed to the user.

[0124] Step 5:

[0125] The information selected by the user is sent back to the server via the terminal device, and a process is executed to update the selected provider information. This ensures that the information recording medium reflects the latest user selection data. The input is the user's selection information, and the output is the updated provider information database.

[0126] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0127] This invention is a system that combines an emotion engine with a platform that provides reliable community-based life support services, thereby enabling the delivery of services that respond to the user's emotions. In this system, the user, terminal, and server work in cooperation.

[0128] The user first enters the details of their inquiry and their location through their device. At this time, the emotion engine recognizes the user's emotions from their conversational style and input method, and generates an emotion status. For example, if the user strongly indicates urgency, the emotion status will be determined to be high urgency.

[0129] Next, the terminal sends the user's input and emotional status to the server. The server searches its database for relevant vendor information based on the received data. In doing so, it takes the emotional status into consideration and prioritizes selecting vendors who can respond quickly if the situation is urgent.

[0130] The server then assigns a reliability rating to the retrieved vendor information. The emotion engine further dynamically adjusts the evaluation criteria based on the user's emotions to select the best vendor for the user. For example, if the user expresses anxiety, it prioritizes suggesting vendors with higher reliability ratings.

[0131] The server ultimately sends information, including the adjusted vendor information and ratings, to the user's terminal. The user can then select a vendor based on this information. The selected vendor's information is then fed back to the server. This information is used to update the database and is reflected in subsequent service provision.

[0132] This system enables the personalization of the user experience through emotion recognition, making locally-focused service delivery more effective and smoother. By offering service suggestions that take user emotions into consideration, it can improve convenience and satisfaction.

[0133] The following describes the processing flow.

[0134] Step 1:

[0135] The user enters their consultation details and location using a device. During input, an emotion engine analyzes the user's emotions on the device and generates an emotion status. For example, it detects urgency and anxiety from the user's voice and text during input.

[0136] Step 2:

[0137] The terminal transmits the user's consultation details, local information, and emotional status to the server. An encrypted data transfer protocol is used for this purpose.

[0138] Step 3:

[0139] The server searches its database for relevant vendor information based on the received information. Depending on the emotional status, for example, if the situation is "high urgency," it performs filtering to prioritize vendors that can provide 24-hour service.

[0140] Step 4:

[0141] The server performs a reliability assessment on vendor information. The evaluation method calculates the vendor's reliability using multiple feedback data, and this determines the vendor's rank. If the emotional status is "anxious," reliable vendors are prioritized and selected.

[0142] Step 5:

[0143] The server aggregates information on selected vendors and reliability evaluation results, and transmits them to the user's terminal. This includes vendor contact information, service details, and quotation information.

[0144] Step 6:

[0145] The user reviews the vendor information received through their device and selects their preferred vendor. Once the user confirms their selection, the device sends that information to the server, where it is recorded in the database.

[0146] Step 7:

[0147] The server updates the database based on user selection information. This data is used for future evaluations and is reflected in updating the vendor list and improving reliability ratings. The server uses this data to improve the overall service quality of the system.

[0148] (Example 2)

[0149] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0150] In local service provision, there is a challenge in the lack of personalized service proposals that respond to the user's emotions. This can lead to decreased user satisfaction and convenience, and make it difficult to select the right service provider.

[0151] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0152] In this invention, the server includes means for receiving information and sentiment data from users, means for searching a database for vendor information based on the information and sentiment data, and means for assigning a reliability evaluation to the retrieved vendor information that takes sentiment data into consideration. This makes it possible to propose appropriate and reliable services based on the user's sentiment.

[0153] A "user" is an individual or organization that seeks consultation or service provision through the system.

[0154] "Information" refers to data such as consultation details and local information that users input into the system.

[0155] "Emotional data" refers to information that indicates the emotional state of a user, analyzed based on the user's input and methods.

[0156] "Receiving means" refers to a device or program that has the function of acquiring information and emotional data from users.

[0157] A "search tool" is a device or program that has the function of searching a database for relevant vendor information based on received information and sentiment data.

[0158] "Evaluation means" refers to a device or program that has the function of evaluating the reliability of retrieved vendor information by reflecting received sentiment data.

[0159] "Transmission means" refers to a device or program that has the function of sending evaluated vendor information to the user's terminal.

[0160] An "update mechanism" is a device or program that has the function of saving user-selected data and updating the system's database with new information.

[0161] This invention aims to realize a system that proposes optimal services while considering the user's emotions in a community-based service delivery platform. In this system, the terminal, server, and emotion engine work together to provide personalized services that respond to the user's inquiries and emotions.

[0162] First, the user inputs their consultation details and local information using a computer terminal. The terminal is equipped with emotion recognition software, which analyzes the user's input and emotional status using an emotion engine. This emotion engine generates emotional data based on the user's input speed, tone, and keywords in the content. This software analyzes emotions using, for example, NLP libraries and AI algorithms.

[0163] Next, the terminal sends the collected information and sentiment data to the server. The server uses its database to search for relevant vendor information based on the received information. The search is prioritized based on the user's sentiment data. The server then performs a reliability evaluation of the retrieved vendor information, taking the sentiment data into account. This reliability evaluation is dynamically adjusted according to the user's sentiment status to select the most suitable vendor.

[0164] For example, if a user enters "I need medical services that can respond to a sudden change in my health," the emotion engine will determine that this is a "high-priority" situation. This information is sent to the server, which then lists medical services that can respond immediately and displays highly reliable providers first.

[0165] One example of inputting a prompt into a generative AI model is, "Based on the user's sentiment data, please tell me which vendor is most appropriate." This prompt allows the sentiment engine to dynamically suggest the most suitable service.

[0166] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0167] Step 1:

[0168] The user uses a device to input their inquiry details and location information. A sample input example is provided: "I'm looking for care services. Please specify the area (Tokyo)." The entered information is sent to the emotion engine and added to an internal queue for analysis.

[0169] Step 2:

[0170] The device passes the input to the emotion engine, which analyzes the user's emotions. The emotion engine uses a natural language processing library to generate the user's emotional status (e.g., urgency or anxiety level) from the input keywords, input speed, and context. As a result, an emotional status such as "reassured" or "highly urgent" is output.

[0171] Step 3:

[0172] The terminal sends user input information and generated emotion status to the server. The data sent includes text information and numerical emotion indicators. For example, it might be sent with statuses such as "care services" and "high urgency."

[0173] Step 4:

[0174] The server performs a database search based on the received data. Here, it prioritizes relevant vendor information according to their emotional status. Specifically, it uses an SQL query to extract vendors with the tags "nursing care" and "emergency response available" as priority, and outputs them as a list.

[0175] Step 5:

[0176] The server performs a reliability assessment based on the search results. The evaluation criteria are dynamically adjusted based on the output of the sentiment engine, so for example, vendors with "high ratings" and "quick response capabilities" are ranked higher in the list.

[0177] Step 6:

[0178] The server sends the final evaluated vendor information to the terminal. The output data is formatted as a vendor list with reliability scores and reaches the terminal.

[0179] Step 7:

[0180] The user makes a selection based on the provided vendor information. As a result of the selection, the selected vendor information is sent from the terminal to the server and recorded as feedback. This information will be used for future database adjustments and updates to evaluation criteria.

[0181] (Application Example 2)

[0182] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0183] In modern life support services, it is crucial to quickly and accurately select the appropriate service provider that can respond to the diverse emotions of users. However, conventional systems struggle to personalize services that fully consider users' emotions, and thus fail to adequately improve user satisfaction. Furthermore, the services provided tend to be unbalanced in terms of reliability and speed, without being optimized according to the user's emotional state. To solve this problem, it is necessary to recognize the user's emotions and optimize services accordingly.

[0184] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0185] In this invention, the server includes receiving means for receiving consultation content from users and analyzing their emotions; searching means for obtaining relevant business information from a data set based on the consultation content and the analyzed emotions; and evaluation means for performing a reliability evaluation on the obtained business information and dynamically adjusting the evaluation criteria based on the emotions. This makes it possible to select an appropriate business and personalize services according to the user's emotions.

[0186] A "receiving means" refers to a device or system that receives the content of a consultation from a user and analyzes their emotions based on the content and input method.

[0187] A "search tool" refers to a device or mechanism for appropriately obtaining relevant business information from a database based on the received consultation content and analyzed emotions.

[0188] "Evaluation methods" refer to devices or mechanisms that perform reliability assessments on acquired business information and dynamically adjust evaluation criteria based on user sentiment.

[0189] "Transmission means" refers to devices or mechanisms for accurately and quickly transmitting evaluated business information to user devices.

[0190] An "update mechanism" refers to a device or system for saving user selection information and periodically updating the data collection.

[0191] An "emotion engine" is a program or system that recognizes the user's emotions and uses that information to personalize services.

[0192] "Spatial information" refers to geographical data and location information, and is used to filter business information within a specific region.

[0193] "Opinions" refer to evaluations and feedback information provided by multiple evaluation organizations, and are the basis for appropriately updating the reliability assessment of a business operator.

[0194] "Optimization" refers to taking into account the emotional state of the user and making the most effective and efficient choices in the process of providing a service.

[0195] The system for realizing this invention consists of a user terminal, a server, and an emotion engine. The user inputs the consultation details using the user terminal. The input information is received by a receiving means, and the emotion engine on the terminal analyzes the emotions. The emotion engine generates an emotion status using a text analysis library (e.g., TextBlob or VADER).

[0196] The server receives the consultation details and emotional status via a search mechanism and retrieves relevant business information from the database based on this information. The server executes database queries (e.g., SQL queries) to filter and retrieve business information. By utilizing spatial information during this process, it is possible to narrow down the search to only the most appropriate businesses based on location.

[0197] The evaluation system assesses the reliability of the acquired information and dynamically adjusts the evaluation criteria according to the emotional status. This process incorporates feedback from multiple evaluation organizations. As a result of the evaluation, the most suitable service provider is selected to match the user's choice. This evaluation process is based on statistical methods and machine learning models, using data analysis tools such as Python and R.

[0198] Subsequently, the evaluated service provider information is sent to the user's terminal using a transmission method. The user selects a service provider from the presented information, and this selection information is sent to the server via an update method and reflected in the database. The updated data will be used to improve future service provision, enabling better choices that meet the user's needs.

[0199] For example, if a user says, "I'm really tired today, so I want to order from a place where I can feel safe," the emotion engine will identify "fatigue" and "safety" as keywords and prioritize suggesting highly trustworthy businesses.

[0200] Examples of prompts for a generative AI model include:

[0201] "If a user enters, 'I'm really tired today, so I want to order from a reliable source,' what kind of sentiment analysis should be performed? And then, generate a list of highly reliable service providers."

[0202] It is in that form.

[0203] In this way, the entire system works in coordination, enabling the delivery of effective services that respond to the user's emotions.

[0204] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0205] Step 1:

[0206] The user inputs their consultation details using a terminal. The entered text data is passed to a receiving device, where an initial analysis is performed by the emotion engine. The input is the user's consultation details, and the output is data with an added emotion status. At this time, a text analysis library is used to identify emotion cues such as "urgency" and "sense of security" from the context.

[0207] Step 2:

[0208] The server receives consultation content with emotional status sent from the terminal. Next, it uses a search mechanism to match the consultation content and emotional status with related information in the database. The input is consultation data with emotional status, and the output is a set of related business information. Filtering is performed through database queries based on spatial information and past evaluation data.

[0209] Step 3:

[0210] The server uses evaluation tools to assess the reliability of acquired business information and performs dynamic evaluations based on emotional status. The input is the acquired business information, and the output is a list of businesses with added reliability ratings. Depending on the emotional state, evaluations are performed using statistical analysis and machine learning models based on feedback from multiple evaluation organizations.

[0211] Step 4:

[0212] The server transmits a list of trusted service providers to the user's terminal via a transmission method. The output list is sorted according to the evaluation criteria, with the most relevant service provider information displayed at the top. This process uses a communication protocol to efficiently and quickly transfer data.

[0213] Step 5:

[0214] The user makes a selection from a list of service providers displayed on their device. This selection information is sent to the server via an update mechanism and used to update the database. The user's selection information is retrieved and used to update the database, contributing to improved search accuracy in subsequent searches.

[0215] Through this series of processes, it becomes possible to provide flexible and personalized services based on the user's emotions.

[0216] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0217] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0218] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0222] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0223] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0224] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0225] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0226] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0227] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0228] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0229] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0230] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0231] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0232] This invention aims to build an integrated platform for providing reliable community-based support services. The system operates through a program and functions through the cooperation of users, terminals, and servers.

[0233] First, users use their devices to input information about problems or inquiries that have occurred in their area. For example, if a user wants "air conditioner repair," they use their device to fill in the details of the inquiry and the desired service, and then submit the request.

[0234] Next, the terminal sends the user's input to the server. The server receives this information and retrieves relevant vendor information from its database. Specifically, it filters for vendors related to "air conditioner repair" and organizes the results.

[0235] The server performs a reliability assessment on the acquired vendor information. This assessment considers factors such as past performance, customer reviews, and feedback from the local community. This assessment allows for the definition of a vendor's reliability rank.

[0236] The server then sends the evaluation results along with detailed information about the vendors to the user's device. The user can then review this information on their device and select their preferred vendor.

[0237] When a user selects a service provider, the device reports the selection information to the server. This information is recorded in a database by the server and used for future evaluation updates and service improvements.

[0238] Furthermore, user feedback and selection information are automatically reflected in the database, contributing to further improvements in service quality. This system facilitates the provision of community-based services and serves as an effective means of quickly resolving household and equipment-related issues.

[0239] The following describes the processing flow.

[0240] Step 1:

[0241] Users use their devices to enter their inquiry details and residential area information into a dedicated input form. For example, if they want to request a water leak repair, they enter that information, fill in the necessary details, and press the submit button.

[0242] Step 2:

[0243] The terminal organizes the input data and sends it to the server using a secure communication protocol. During this process, the data is encrypted to maintain confidentiality.

[0244] Step 3:

[0245] The server searches its database for relevant service providers based on the consultation details and regional information received from the terminal. The server executes a query and lists the relevant service providers.

[0246] Step 4:

[0247] The server performs a reliability assessment on the acquired vendor information. This assessment utilizes the vendor's past performance, feedback from evaluation agencies, and customer reviews. A reliability rank is then assigned to each vendor.

[0248] Step 5:

[0249] The server reorganizes vendor information, adding reliability ratings, and sends it to the user's terminal. This information package includes vendor contact information, available services, and pricing.

[0250] Step 6:

[0251] The user reviews the transmitted vendor information on their device and selects their preferred vendor. The user then examines the details and makes a decision to proceed with a specific service request.

[0252] Step 7:

[0253] The terminal then resends the user's selected vendor information to the server. This includes the ID of the selected vendor and the associated query details.

[0254] Step 8:

[0255] The server receives user selection information and records it in the database. This information is useful for future evaluation updates and improving vendor reliability, leading to overall system quality improvement.

[0256] (Example 1)

[0257] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0258] There is a need for a platform that can provide life support services that can respond quickly and reliably to the diverse challenges and needs faced by users in their communities. However, with conventional systems, it has been difficult to quickly find reliable service providers, and there have been limitations in improving user satisfaction.

[0259] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0260] In this invention, the server includes a device for receiving the content of a problem from a user, a device for acquiring relevant vendor information from an information source based on the content of the problem, and a device for storing the user's selection information and updating the information source. This makes it possible to quickly acquire highly reliable vendor information and propose it to the user.

[0261] A "user" is an individual or organization that uses the system to input their issues and needs and receives services from that system.

[0262] A "receiving device" is a device that receives the task details from the user in digital format and passes them on to the next processing device.

[0263] A "source of information" refers to a database or other information provider that the system accesses to obtain vendor information.

[0264] An "acquisition device" is a device used to retrieve relevant vendor information from information sources based on the content of the received issue.

[0265] An "evaluation device" is a device that assigns reliability based on acquired vendor information, taking into account past performance and evaluations.

[0266] A "transmission device" is a device that has the function of transmitting evaluated vendor information to the user's device.

[0267] A "storage device" is a device that records user selection information and uses it for future data analysis and system improvement.

[0268] An "update device" is a device that keeps information sources up-to-date based on user selections and feedback.

[0269] "Feedback information" refers to information received from users regarding their evaluations of services and vendors, as well as suggestions for improvement.

[0270] "Reliability evaluation" is an assessment that expresses the reliability of a service provider as a numerical value or rank, and is an important indicator for users when choosing a service provider.

[0271] This system is an integrated platform for effectively providing local life support services, with users, terminals, and servers working together. The system is designed to quickly resolve the wide range of challenges users may encounter.

[0272] Users input task details via a dedicated application using devices such as smartphones or computers. This input includes specific service requests, such as "I would like to request air conditioner repair." The entered task details are transmitted to a server via the internet.

[0273] The server analyzes the received issue and retrieves relevant vendor information from a database or other sources. Based on the vendor information, the server performs a reliability assessment and uses an algorithm to calculate a rating rank for each vendor. This algorithm takes into account past performance, rating scores, and feedback from the local community.

[0274] Next, the server organizes the evaluated vendor information and sends it back to the terminal, helping the user select a trustworthy vendor. The user selects the best vendor from the provided list and reports their selection to the server. This information is stored in a database and used to update vendor ratings and improve services in the future.

[0275] As a concrete example, when a user requests a "garden pruning service," they enter their request into a terminal and send it to the server. The server filters highly-rated gardeners in the area and presents them to the user along with their reliability ranking. The user can then select from the list and utilize the service.

[0276] The generative AI model is used by the system to learn from external data and suggest the most suitable vendors. An example of a prompt might be: "Explain how the server evaluates vendor reliability and presents appropriate options to the user on a service platform specializing in local problem solving." Through this implementation, the system supports the provision of fast, reliable services tailored to local needs.

[0277] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0278] Step 1:

[0279] The user opens a dedicated application on their device, enters the details of the problem or inquiry, and presses the submit button. The input includes a specific request, such as "I would like to request air conditioner repair." The device then formats the user's request data and sends it to the server via the internet.

[0280] Step 2:

[0281] The server receives the data sent from the terminal and analyzes its content. It receives the user's request as input and extracts keywords using an analysis engine. As a specific operation, it issues an instruction to be able to obtain relevant contractor information from the database based on the keyword "air conditioner repair".

[0282] Step 3:

[0283] The server performs a database search to obtain relevant contractor information. Using the extracted keywords as input, it filters the database to obtain a list of "air conditioner repair" contractors. As output, it creates a list of contractors that seem reliable.

[0284] Step 4:

[0285] The server applies a reliability evaluation algorithm to the obtained contractor information. The input is the past performance of the contractors and the evaluation data from customers. By performing data calculations to rank each contractor and calculate the reliability rank, it outputs the evaluation results.

[0286] Step 5:

[0287] The server organizes the contractor information with reliability ranks and prepares to send it to the terminal. Using the ranked contractor list as input, it processes and formats it into a user-friendly form. As output, it creates the contractor information to be sent to the terminal.

[0288] Step 6:

[0289] The user checks the list of contractors with reliability evaluations displayed on the terminal and selects the contractor to be used. As output, the information of the selected contractor is confirmed and sent from the terminal to the server.

[0290] Step 7:

[0291] The terminal sends the selected vendor information to the server, which receives it and stores it in a database. The input includes the selected vendor information, which is stored for future service improvements and reliability evaluation updates. The output is the updated database.

[0292] (Application Example 1)

[0293] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0294] To provide prompt and reliable life support services in local communities, it is necessary to have information on appropriate products and services that meet the needs of users. However, the current system is insufficient in obtaining the information users need and in evaluating the reliability of service providers, making it difficult to achieve satisfactory results for users. To solve this problem, it is necessary to build a system that provides accurate and reliable information quickly and improves convenience.

[0295] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0296] In this invention, the server includes a receiving means using a terminal device that receives inquiries from users, a search means for obtaining relevant provider information from an information recording medium based on the inquiries, and an evaluation means for assigning a reliability rating to the obtained provider information. This makes it possible to quickly select products and services that users need within their region and provide the information while ensuring its reliability.

[0297] A "terminal device" is a portable information processing device used by users to input and receive information.

[0298] An "information recording medium" is a data storage device or medium used to store provider information and reliability data, and to retrieve them.

[0299] "Reliability assessment" is the process of quantifying or ranking the trustworthiness of a provider based on factors such as the provider's track record, customer reviews, and opinions from evaluation organizations.

[0300] A "portable information processing device" is a device that can process and communicate information while being mobile, and includes smartphones and tablets.

[0301] "Selection" is the process of finding the appropriate information or item from among multiple pieces of information based on specified criteria.

[0302] An "evaluation body" is a professional institution or organization that evaluates goods or services based on specific criteria.

[0303] The system for implementing this invention mainly consists of the cooperation of a server, a terminal device, and a mobile information processing device. The user uses a mobile information processing device (e.g., a smartphone) to input their desire to acquire local products and services. The terminal device receives this input information and transmits it to the server.

[0304] Based on the received information, the server searches for relevant provider information from the information storage medium. This includes retrieving details of commercially available products and information on local service providers from the database. An evaluation method is used to assign a reliability rating to the retrieved provider information. This evaluation method calculates the reliability of the provider by considering feedback from evaluation organizations and past performance.

[0305] Finally, the server sends the evaluated provider information to the user's mobile device. This allows the user to easily view reliable information and select the services and products they need.

[0306] For example, if a user requests information on "recommended refrigerator items," the server will list highly-rated products in the area and send that information to the user. This allows users to efficiently select products both inside and outside the store.

[0307] As an example of a prompt sentence to be input into the AI model, there is one such as "The user inputs an inquiry regarding products and services required within the store. The server conducts a reliability assessment and returns the result to the application so that the user can make an optimal choice. How can this process be made effective?" This invention enables local community-based information provision and improvement of user convenience.

[0308] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The user uses a portable information processing device to input the consultation content regarding the required products and services. The input information is received by the terminal device. The data to be input is the details of the desired products and services.

[0311] Step 2:

[0312] The terminal transmits the received consultation content to the server. Based on this information, the server searches for relevant provider information from the information recording medium. The input here is the consultation content from the user, and the output is the provider information. The server uses a search algorithm to extract highly relevant provider information.

[0313] Step 3:

[0314] The server conducts a reliability assessment on the obtained provider information. In this process, a reliability score is assigned to the provider based on feedback obtained from multiple evaluation organizations and past usage records. The input is the provider information and the reliability assessment criteria, and the output is the provider information with the reliability score assigned.

[0315] Step 4:

[0316] The server transmits the evaluated provider information to the user's mobile information processing device. The user then selects products or services based on the received information. The input here is provider information, including reliability ratings, and the output is detailed information displayed to the user.

[0317] Step 5:

[0318] The information selected by the user is sent back to the server via the terminal device, and a process is executed to update the selected provider information. This ensures that the information recording medium reflects the latest user selection data. The input is the user's selection information, and the output is the updated provider information database.

[0319] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0320] This invention is a system that combines an emotion engine with a platform that provides reliable community-based life support services, thereby enabling the delivery of services that respond to the user's emotions. In this system, the user, terminal, and server work in cooperation.

[0321] The user first enters the details of their inquiry and their location through their device. At this time, the emotion engine recognizes the user's emotions from their conversational style and input method, and generates an emotion status. For example, if the user strongly indicates urgency, the emotion status will be determined to be high urgency.

[0322] Next, the terminal sends the user's input and emotional status to the server. The server searches its database for relevant vendor information based on the received data. In doing so, it takes the emotional status into consideration and prioritizes selecting vendors who can respond quickly if the situation is urgent.

[0323] The server then assigns a reliability rating to the retrieved vendor information. The emotion engine further dynamically adjusts the evaluation criteria based on the user's emotions to select the best vendor for the user. For example, if the user expresses anxiety, it prioritizes suggesting vendors with higher reliability ratings.

[0324] The server ultimately sends information, including the adjusted vendor information and ratings, to the user's terminal. The user can then select a vendor based on this information. The selected vendor's information is then fed back to the server. This information is used to update the database and is reflected in subsequent service provision.

[0325] This system enables the personalization of the user experience through emotion recognition, making locally-focused service delivery more effective and smoother. By offering service suggestions that take user emotions into consideration, it can improve convenience and satisfaction.

[0326] The following describes the processing flow.

[0327] Step 1:

[0328] The user enters their consultation details and location using a device. During input, an emotion engine analyzes the user's emotions on the device and generates an emotion status. For example, it detects urgency and anxiety from the user's voice and text during input.

[0329] Step 2:

[0330] The terminal transmits the user's consultation details, local information, and emotional status to the server. An encrypted data transfer protocol is used for this purpose.

[0331] Step 3:

[0332] The server searches its database for relevant vendor information based on the received information. Depending on the emotional status, for example, if the situation is "high urgency," it performs filtering to prioritize vendors that can provide 24-hour service.

[0333] Step 4:

[0334] The server performs a reliability assessment on vendor information. The evaluation method calculates the vendor's reliability using multiple feedback data, and this determines the vendor's rank. If the emotional status is "anxious," reliable vendors are prioritized and selected.

[0335] Step 5:

[0336] The server aggregates information on selected vendors and reliability evaluation results, and transmits them to the user's terminal. This includes vendor contact information, service details, and quotation information.

[0337] Step 6:

[0338] The user reviews the vendor information received through their device and selects their preferred vendor. Once the user confirms their selection, the device sends that information to the server, where it is recorded in the database.

[0339] Step 7:

[0340] The server updates the database based on user selection information. This data is used for future evaluations and is reflected in updating the vendor list and improving reliability ratings. The server uses this data to improve the overall service quality of the system.

[0341] (Example 2)

[0342] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0343] In local service provision, there is a challenge in the lack of personalized service proposals that respond to the user's emotions. This can lead to decreased user satisfaction and convenience, and make it difficult to select the right service provider.

[0344] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0345] In this invention, the server includes means for receiving information and sentiment data from users, means for searching a database for vendor information based on the information and sentiment data, and means for assigning a reliability evaluation to the retrieved vendor information that takes sentiment data into consideration. This makes it possible to propose appropriate and reliable services based on the user's sentiment.

[0346] A "user" is an individual or organization that seeks consultation or service provision through the system.

[0347] "Information" refers to data such as consultation details and local information that users input into the system.

[0348] "Emotional data" refers to information that indicates the emotional state of a user, analyzed based on the user's input and methods.

[0349] "Receiving means" refers to a device or program that has the function of acquiring information and emotional data from users.

[0350] A "search tool" is a device or program that has the function of searching a database for relevant vendor information based on received information and sentiment data.

[0351] "Evaluation means" refers to a device or program that has the function of evaluating the reliability of retrieved vendor information by reflecting received sentiment data.

[0352] "Transmission means" refers to a device or program that has the function of sending evaluated vendor information to the user's terminal.

[0353] An "update mechanism" is a device or program that has the function of saving user-selected data and updating the system's database with new information.

[0354] This invention aims to realize a system that proposes optimal services while considering the user's emotions in a community-based service delivery platform. In this system, the terminal, server, and emotion engine work together to provide personalized services that respond to the user's inquiries and emotions.

[0355] First, the user inputs their consultation details and local information using a computer terminal. The terminal is equipped with emotion recognition software, which analyzes the user's input and emotional status using an emotion engine. This emotion engine generates emotional data based on the user's input speed, tone, and keywords in the content. This software analyzes emotions using, for example, NLP libraries and AI algorithms.

[0356] Next, the terminal sends the collected information and sentiment data to the server. The server uses its database to search for relevant vendor information based on the received information. The search is prioritized based on the user's sentiment data. The server then performs a reliability evaluation of the retrieved vendor information, taking the sentiment data into account. This reliability evaluation is dynamically adjusted according to the user's sentiment status to select the most suitable vendor.

[0357] For example, if a user enters "I need medical services that can respond to a sudden change in my health," the emotion engine will determine that this is a "high-priority" situation. This information is sent to the server, which then lists medical services that can respond immediately and displays highly reliable providers first.

[0358] One example of inputting a prompt into a generative AI model is, "Based on the user's sentiment data, please tell me which vendor is most appropriate." This prompt allows the sentiment engine to dynamically suggest the most suitable service.

[0359] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0360] Step 1:

[0361] The user uses a device to input their inquiry details and location information. A sample input example is provided: "I'm looking for care services. Please specify the area (Tokyo)." The entered information is sent to the emotion engine and added to an internal queue for analysis.

[0362] Step 2:

[0363] The device passes the input to the emotion engine, which analyzes the user's emotions. The emotion engine uses a natural language processing library to generate the user's emotional status (e.g., urgency or anxiety level) from the input keywords, input speed, and context. As a result, an emotional status such as "reassured" or "highly urgent" is output.

[0364] Step 3:

[0365] The terminal sends user input information and generated emotion status to the server. The data sent includes text information and numerical emotion indicators. For example, it might be sent with statuses such as "care services" and "high urgency."

[0366] Step 4:

[0367] The server performs a database search based on the received data. Here, it prioritizes relevant vendor information according to their emotional status. Specifically, it uses an SQL query to extract vendors with the tags "nursing care" and "emergency response available" as priority, and outputs them as a list.

[0368] Step 5:

[0369] The server performs a reliability assessment based on the search results. The evaluation criteria are dynamically adjusted based on the output of the sentiment engine, so for example, vendors with "high ratings" and "quick response capabilities" are ranked higher in the list.

[0370] Step 6:

[0371] The server sends the final evaluated vendor information to the terminal. The output data is formatted as a vendor list with reliability scores and reaches the terminal.

[0372] Step 7:

[0373] The user makes a selection based on the provided vendor information. As a result of the selection, the selected vendor information is sent from the terminal to the server and recorded as feedback. This information will be used for future database adjustments and updates to evaluation criteria.

[0374] (Application Example 2)

[0375] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0376] In modern life support services, it is crucial to quickly and accurately select the appropriate service provider that can respond to the diverse emotions of users. However, conventional systems struggle to personalize services that fully consider users' emotions, and thus fail to adequately improve user satisfaction. Furthermore, the services provided tend to be unbalanced in terms of reliability and speed, without being optimized according to the user's emotional state. To solve this problem, it is necessary to recognize the user's emotions and optimize services accordingly.

[0377] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0378] In this invention, the server includes receiving means for receiving consultation content from users and analyzing their emotions; searching means for obtaining relevant business information from a data set based on the consultation content and the analyzed emotions; and evaluation means for performing a reliability evaluation on the obtained business information and dynamically adjusting the evaluation criteria based on the emotions. This makes it possible to select an appropriate business and personalize services according to the user's emotions.

[0379] A "receiving means" refers to a device or system that receives the content of a consultation from a user and analyzes their emotions based on the content and input method.

[0380] A "search tool" refers to a device or mechanism for appropriately obtaining relevant business information from a database based on the received consultation content and analyzed emotions.

[0381] "Evaluation methods" refer to devices or mechanisms that perform reliability assessments on acquired business information and dynamically adjust evaluation criteria based on user sentiment.

[0382] "Transmission means" refers to devices or mechanisms for accurately and quickly transmitting evaluated business information to user devices.

[0383] An "update mechanism" refers to a device or system for saving user selection information and periodically updating the data collection.

[0384] An "emotion engine" is a program or system that recognizes the user's emotions and uses that information to personalize services.

[0385] "Spatial information" refers to geographical data and location information, and is used to filter business information within a specific region.

[0386] "Opinions" refer to evaluations and feedback information provided by multiple evaluation organizations, and are the basis for appropriately updating the reliability assessment of a business operator.

[0387] "Optimization" refers to taking into account the emotional state of the user and making the most effective and efficient choices in the process of providing a service.

[0388] The system for realizing this invention consists of a user terminal, a server, and an emotion engine. The user inputs the consultation details using the user terminal. The input information is received by a receiving means, and the emotion engine on the terminal analyzes the emotions. The emotion engine generates an emotion status using a text analysis library (e.g., TextBlob or VADER).

[0389] The server receives the consultation details and emotional status via a search mechanism and retrieves relevant business information from the database based on this information. The server executes database queries (e.g., SQL queries) to filter and retrieve business information. By utilizing spatial information during this process, it is possible to narrow down the search to only the most appropriate businesses based on location.

[0390] The evaluation system assesses the reliability of the acquired information and dynamically adjusts the evaluation criteria according to the emotional status. This process incorporates feedback from multiple evaluation organizations. As a result of the evaluation, the most suitable service provider is selected to match the user's choice. This evaluation process is based on statistical methods and machine learning models, using data analysis tools such as Python and R.

[0391] Subsequently, the evaluated service provider information is sent to the user's terminal using a transmission method. The user selects a service provider from the presented information, and this selection information is sent to the server via an update method and reflected in the database. The updated data will be used to improve future service provision, enabling better choices that meet the user's needs.

[0392] For example, if a user says, "I'm really tired today, so I want to order from a place where I can feel safe," the emotion engine will identify "fatigue" and "safety" as keywords and prioritize suggesting highly trustworthy businesses.

[0393] Examples of prompts for a generative AI model include:

[0394] "If a user enters, 'I'm really tired today, so I want to order from a reliable source,' what kind of sentiment analysis should be performed? And then, generate a list of highly reliable service providers."

[0395] It is in that form.

[0396] In this way, the entire system works in coordination, enabling the delivery of effective services that respond to the user's emotions.

[0397] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0398] Step 1:

[0399] The user inputs their consultation details using a terminal. The entered text data is passed to a receiving device, where an initial analysis is performed by the emotion engine. The input is the user's consultation details, and the output is data with an added emotion status. At this time, a text analysis library is used to identify emotion cues such as "urgency" and "sense of security" from the context.

[0400] Step 2:

[0401] The server receives consultation content with emotional status sent from the terminal. Next, it uses a search mechanism to match the consultation content and emotional status with related information in the database. The input is consultation data with emotional status, and the output is a set of related business information. Filtering is performed through database queries based on spatial information and past evaluation data.

[0402] Step 3:

[0403] The server uses evaluation tools to assess the reliability of acquired business information and performs dynamic evaluations based on emotional status. The input is the acquired business information, and the output is a list of businesses with added reliability ratings. Depending on the emotional state, evaluations are performed using statistical analysis and machine learning models based on feedback from multiple evaluation organizations.

[0404] Step 4:

[0405] The server transmits a list of trusted service providers to the user's terminal via a transmission method. The output list is sorted according to the evaluation criteria, with the most relevant service provider information displayed at the top. This process uses a communication protocol to efficiently and quickly transfer data.

[0406] Step 5:

[0407] The user makes a selection from a list of service providers displayed on their device. This selection information is sent to the server via an update mechanism and used to update the database. The user's selection information is retrieved and used to update the database, contributing to improved search accuracy in subsequent searches.

[0408] Through this series of processes, it becomes possible to provide flexible and personalized services based on the user's emotions.

[0409] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0410] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0411] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0412] [Third Embodiment]

[0413] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0414] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0415] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0416] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0417] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0418] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0419] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0420] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0421] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0422] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0423] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0424] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0425] This invention aims to build an integrated platform for providing reliable community-based support services. The system operates through a program and functions through the cooperation of users, terminals, and servers.

[0426] First, users use their devices to input information about problems or inquiries that have occurred in their area. For example, if a user wants "air conditioner repair," they use their device to fill in the details of the inquiry and the desired service, and then submit the request.

[0427] Next, the terminal sends the user's input to the server. The server receives this information and retrieves relevant vendor information from its database. Specifically, it filters for vendors related to "air conditioner repair" and organizes the results.

[0428] The server performs a reliability assessment on the acquired vendor information. This assessment considers factors such as past performance, customer reviews, and feedback from the local community. This assessment allows for the definition of a vendor's reliability rank.

[0429] The server then sends the evaluation results along with detailed information about the vendors to the user's device. The user can then review this information on their device and select their preferred vendor.

[0430] When a user selects a service provider, the device reports the selection information to the server. This information is recorded in a database by the server and used for future evaluation updates and service improvements.

[0431] Furthermore, user feedback and selection information are automatically reflected in the database, contributing to further improvements in service quality. This system facilitates the provision of community-based services and serves as an effective means of quickly resolving household and equipment-related issues.

[0432] The following describes the processing flow.

[0433] Step 1:

[0434] Users use their devices to enter their inquiry details and residential area information into a dedicated input form. For example, if they want to request a water leak repair, they enter that information, fill in the necessary details, and press the submit button.

[0435] Step 2:

[0436] The terminal organizes the input data and sends it to the server using a secure communication protocol. During this process, the data is encrypted to maintain confidentiality.

[0437] Step 3:

[0438] The server searches its database for relevant service providers based on the consultation details and regional information received from the terminal. The server executes a query and lists the relevant service providers.

[0439] Step 4:

[0440] The server performs a reliability assessment on the acquired vendor information. This assessment utilizes the vendor's past performance, feedback from evaluation agencies, and customer reviews. A reliability rank is then assigned to each vendor.

[0441] Step 5:

[0442] The server reorganizes vendor information, adding reliability ratings, and sends it to the user's terminal. This information package includes vendor contact information, available services, and pricing.

[0443] Step 6:

[0444] The user reviews the transmitted vendor information on their device and selects their preferred vendor. The user then examines the details and makes a decision to proceed with a specific service request.

[0445] Step 7:

[0446] The terminal then resends the user's selected vendor information to the server. This includes the ID of the selected vendor and the associated query details.

[0447] Step 8:

[0448] The server receives user selection information and records it in the database. This information is useful for future evaluation updates and improving vendor reliability, leading to overall system quality improvement.

[0449] (Example 1)

[0450] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0451] There is a need for a platform that can provide life support services that can respond quickly and reliably to the diverse challenges and needs faced by users in their communities. However, with conventional systems, it has been difficult to quickly find reliable service providers, and there have been limitations in improving user satisfaction.

[0452] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0453] In this invention, the server includes a device for receiving the content of a problem from a user, a device for acquiring relevant vendor information from an information source based on the content of the problem, and a device for storing the user's selection information and updating the information source. This makes it possible to quickly acquire highly reliable vendor information and propose it to the user.

[0454] A "user" is an individual or organization that uses the system to input their issues and needs and receives services from that system.

[0455] A "receiving device" is a device that receives the task details from the user in digital format and passes them on to the next processing device.

[0456] A "source of information" refers to a database or other information provider that the system accesses to obtain vendor information.

[0457] An "acquisition device" is a device used to retrieve relevant vendor information from information sources based on the content of the received issue.

[0458] An "evaluation device" is a device that assigns reliability based on acquired vendor information, taking into account past performance and evaluations.

[0459] A "transmission device" is a device that has the function of transmitting evaluated vendor information to the user's device.

[0460] A "storage device" is a device that records user selection information and uses it for future data analysis and system improvement.

[0461] An "update device" is a device that keeps information sources up-to-date based on user selections and feedback.

[0462] "Feedback information" refers to information received from users regarding their evaluations of services and vendors, as well as suggestions for improvement.

[0463] "Reliability evaluation" is an assessment that expresses the reliability of a service provider as a numerical value or rank, and is an important indicator for users when choosing a service provider.

[0464] This system is an integrated platform for effectively providing local life support services, with users, terminals, and servers working together. The system is designed to quickly resolve the wide range of challenges users may encounter.

[0465] Users input task details via a dedicated application using devices such as smartphones or computers. This input includes specific service requests, such as "I would like to request air conditioner repair." The entered task details are transmitted to a server via the internet.

[0466] The server analyzes the received issue and retrieves relevant vendor information from a database or other sources. Based on the vendor information, the server performs a reliability assessment and uses an algorithm to calculate a rating rank for each vendor. This algorithm takes into account past performance, rating scores, and feedback from the local community.

[0467] Next, the server organizes the evaluated vendor information and sends it back to the terminal, helping the user select a trustworthy vendor. The user selects the best vendor from the provided list and reports their selection to the server. This information is stored in a database and used to update vendor ratings and improve services in the future.

[0468] As a concrete example, when a user requests a "garden pruning service," they enter their request into a terminal and send it to the server. The server filters highly-rated gardeners in the area and presents them to the user along with their reliability ranking. The user can then select from the list and utilize the service.

[0469] The generative AI model is used by the system to learn from external data and suggest the most suitable vendors. An example of a prompt might be: "Explain how the server evaluates vendor reliability and presents appropriate options to the user on a service platform specializing in local problem solving." Through this implementation, the system supports the provision of fast, reliable services tailored to local needs.

[0470] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0471] Step 1:

[0472] The user opens a dedicated application on their device, enters the details of the problem or inquiry, and presses the submit button. The input includes a specific request, such as "I would like to request air conditioner repair." The device then formats the user's request data and sends it to the server via the internet.

[0473] Step 2:

[0474] The server receives data sent from the terminal and analyzes its contents. It receives user requests as input and extracts keywords using its analysis engine. Specifically, based on the keyword "air conditioner repair," it instructs the server to retrieve relevant contractor information from the database.

[0475] Step 3:

[0476] The server performs a database search to retrieve relevant vendor information. Using the extracted keywords as input, it filters the database to obtain a list of "air conditioner repair" vendors. As output, it creates a list of vendors that appear to be reliable.

[0477] Step 4:

[0478] The server applies a reliability evaluation algorithm to the acquired vendor information. The input consists of the vendor's past performance and customer evaluation data. By performing data calculations, the server assigns a rank to each vendor and outputs the evaluation result by calculating the reliability rank.

[0479] Step 5:

[0480] The server organizes vendor information with reliability rankings and prepares it for transmission to the terminal. As input, it processes the ranked vendor list and formats it into a user-friendly format. As output, it creates vendor information to be sent to the terminal.

[0481] Step 6:

[0482] The user reviews the list of rated service providers displayed on the terminal and selects the service provider they wish to use. The terminal then confirms the information of the selected service provider and sends it to the server as output.

[0483] Step 7:

[0484] The terminal sends the selected vendor information to the server, which receives it and stores it in a database. The input includes the selected vendor information, which is stored for future service improvements and reliability evaluation updates. The output is the updated database.

[0485] (Application Example 1)

[0486] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0487] To provide prompt and reliable life support services in local communities, it is necessary to have information on appropriate products and services that meet the needs of users. However, the current system is insufficient in obtaining the information users need and in evaluating the reliability of service providers, making it difficult to achieve satisfactory results for users. To solve this problem, it is necessary to build a system that provides accurate and reliable information quickly and improves convenience.

[0488] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0489] In this invention, the server includes a receiving means using a terminal device that receives inquiries from users, a search means for obtaining relevant provider information from an information recording medium based on the inquiries, and an evaluation means for assigning a reliability rating to the obtained provider information. This makes it possible to quickly select products and services that users need within their region and provide the information while ensuring its reliability.

[0490] A "terminal device" is a portable information processing device used by users to input and receive information.

[0491] An "information recording medium" is a data storage device or medium used to store provider information and reliability data, and to retrieve them.

[0492] "Reliability assessment" is the process of quantifying or ranking the trustworthiness of a provider based on factors such as the provider's track record, customer reviews, and opinions from evaluation organizations.

[0493] A "portable information processing device" is a device that can process and communicate information while being mobile, and includes smartphones and tablets.

[0494] "Selection" is the process of finding the appropriate information or item from among multiple pieces of information based on specified criteria.

[0495] An "evaluation body" is a professional institution or organization that evaluates goods or services based on specific criteria.

[0496] The system for implementing this invention mainly consists of the cooperation of a server, a terminal device, and a mobile information processing device. The user uses a mobile information processing device (e.g., a smartphone) to input their desire to acquire local products and services. The terminal device receives this input information and transmits it to the server.

[0497] Based on the received information, the server searches for relevant provider information from the information storage medium. This includes retrieving details of commercially available products and information on local service providers from the database. An evaluation method is used to assign a reliability rating to the retrieved provider information. This evaluation method calculates the reliability of the provider by considering feedback from evaluation organizations and past performance.

[0498] Finally, the server sends the evaluated provider information to the user's mobile device. This allows the user to easily view reliable information and select the services and products they need.

[0499] For example, if a user requests information on "recommended refrigerator items," the server will list highly-rated products in the area and send that information to the user. This allows users to efficiently select products both inside and outside the store.

[0500] An example of a prompt to be input into the generating AI model is: "The user inputs an inquiry about products or services they want in the store. The server performs a reliability evaluation and returns the results to the app, allowing the user to make the best choice. How can this process be made more effective?" This invention enables the provision of locally focused information and improves user convenience.

[0501] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0502] Step 1:

[0503] The user uses a mobile information processing device to input details about the desired product or service. The entered information is received by a terminal device. The data entered consists of details about the desired product or service.

[0504] Step 2:

[0505] The terminal sends the received consultation details to the server. Based on this information, the server searches for relevant provider information from its information storage medium. The input here is the consultation details from the user, and the output is provider information. The server uses a search algorithm to extract highly relevant provider information.

[0506] Step 3:

[0507] The server performs a reliability assessment on the acquired provider information. This process assigns a reliability score to providers based on feedback from multiple evaluation organizations and past usage data. The input is provider information and reliability evaluation criteria, while the output is provider information with assigned reliability scores.

[0508] Step 4:

[0509] The server transmits the evaluated provider information to the user's mobile information processing device. The user then selects products or services based on the received information. The input here is provider information, including reliability ratings, and the output is detailed information displayed to the user.

[0510] Step 5:

[0511] The information selected by the user is sent back to the server via the terminal device, and a process is executed to update the selected provider information. This ensures that the information recording medium reflects the latest user selection data. The input is the user's selection information, and the output is the updated provider information database.

[0512] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0513] This invention is a system that combines an emotion engine with a platform that provides reliable community-based life support services, thereby enabling the delivery of services that respond to the user's emotions. In this system, the user, terminal, and server work in cooperation.

[0514] The user first enters the details of their inquiry and their location through their device. At this time, the emotion engine recognizes the user's emotions from their conversational style and input method, and generates an emotion status. For example, if the user strongly indicates urgency, the emotion status will be determined to be high urgency.

[0515] Next, the terminal sends the user's input and emotional status to the server. The server searches its database for relevant vendor information based on the received data. In doing so, it takes the emotional status into consideration and prioritizes selecting vendors who can respond quickly if the situation is urgent.

[0516] The server then assigns a reliability rating to the retrieved vendor information. The emotion engine further dynamically adjusts the evaluation criteria based on the user's emotions to select the best vendor for the user. For example, if the user expresses anxiety, it prioritizes suggesting vendors with higher reliability ratings.

[0517] The server ultimately sends information, including the adjusted vendor information and ratings, to the user's terminal. The user can then select a vendor based on this information. The selected vendor's information is then fed back to the server. This information is used to update the database and is reflected in subsequent service provision.

[0518] This system enables the personalization of the user experience through emotion recognition, making locally-focused service delivery more effective and smoother. By offering service suggestions that take user emotions into consideration, it can improve convenience and satisfaction.

[0519] The following describes the processing flow.

[0520] Step 1:

[0521] The user enters their consultation details and location using a device. During input, an emotion engine analyzes the user's emotions on the device and generates an emotion status. For example, it detects urgency and anxiety from the user's voice and text during input.

[0522] Step 2:

[0523] The terminal transmits the user's consultation details, local information, and emotional status to the server. An encrypted data transfer protocol is used for this purpose.

[0524] Step 3:

[0525] The server searches its database for relevant vendor information based on the received information. Depending on the emotional status, for example, if the situation is "high urgency," it performs filtering to prioritize vendors that can provide 24-hour service.

[0526] Step 4:

[0527] The server performs a reliability assessment on vendor information. The evaluation method calculates the vendor's reliability using multiple feedback data, and this determines the vendor's rank. If the emotional status is "anxious," reliable vendors are prioritized and selected.

[0528] Step 5:

[0529] The server aggregates information on selected vendors and reliability evaluation results, and transmits them to the user's terminal. This includes vendor contact information, service details, and quotation information.

[0530] Step 6:

[0531] The user reviews the vendor information received through their device and selects their preferred vendor. Once the user confirms their selection, the device sends that information to the server, where it is recorded in the database.

[0532] Step 7:

[0533] The server updates the database based on user selection information. This data is used for future evaluations and is reflected in updating the vendor list and improving reliability ratings. The server uses this data to improve the overall service quality of the system.

[0534] (Example 2)

[0535] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0536] In local service provision, there is a challenge in the lack of personalized service proposals that respond to the user's emotions. This can lead to decreased user satisfaction and convenience, and make it difficult to select the right service provider.

[0537] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0538] In this invention, the server includes means for receiving information and sentiment data from users, means for searching a database for vendor information based on the information and sentiment data, and means for assigning a reliability evaluation to the retrieved vendor information that takes sentiment data into consideration. This makes it possible to propose appropriate and reliable services based on the user's sentiment.

[0539] A "user" is an individual or organization that seeks consultation or service provision through the system.

[0540] "Information" refers to data such as consultation details and local information that users input into the system.

[0541] "Emotional data" refers to information that indicates the emotional state of a user, analyzed based on the user's input and methods.

[0542] "Receiving means" refers to a device or program that has the function of acquiring information and emotional data from users.

[0543] A "search tool" is a device or program that has the function of searching a database for relevant vendor information based on received information and sentiment data.

[0544] "Evaluation means" refers to a device or program that has the function of evaluating the reliability of retrieved vendor information by reflecting received sentiment data.

[0545] "Transmission means" refers to a device or program that has the function of sending evaluated vendor information to the user's terminal.

[0546] An "update mechanism" is a device or program that has the function of saving user-selected data and updating the system's database with new information.

[0547] This invention aims to realize a system that proposes optimal services while considering the user's emotions in a community-based service delivery platform. In this system, the terminal, server, and emotion engine work together to provide personalized services that respond to the user's inquiries and emotions.

[0548] First, the user inputs their consultation details and local information using a computer terminal. The terminal is equipped with emotion recognition software, which analyzes the user's input and emotional status using an emotion engine. This emotion engine generates emotional data based on the user's input speed, tone, and keywords in the content. This software analyzes emotions using, for example, NLP libraries and AI algorithms.

[0549] Next, the terminal sends the collected information and sentiment data to the server. The server uses its database to search for relevant vendor information based on the received information. The search is prioritized based on the user's sentiment data. The server then performs a reliability evaluation of the retrieved vendor information, taking the sentiment data into account. This reliability evaluation is dynamically adjusted according to the user's sentiment status to select the most suitable vendor.

[0550] For example, if a user enters "I need medical services that can respond to a sudden change in my health," the emotion engine will determine that this is a "high-priority" situation. This information is sent to the server, which then lists medical services that can respond immediately and displays highly reliable providers first.

[0551] One example of inputting a prompt into a generative AI model is, "Based on the user's sentiment data, please tell me which vendor is most appropriate." This prompt allows the sentiment engine to dynamically suggest the most suitable service.

[0552] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0553] Step 1:

[0554] The user uses a device to input their inquiry details and location information. A sample input example is provided: "I'm looking for care services. Please specify the area (Tokyo)." The entered information is sent to the emotion engine and added to an internal queue for analysis.

[0555] Step 2:

[0556] The device passes the input to the emotion engine, which analyzes the user's emotions. The emotion engine uses a natural language processing library to generate the user's emotional status (e.g., urgency or anxiety level) from the input keywords, input speed, and context. As a result, an emotional status such as "reassured" or "highly urgent" is output.

[0557] Step 3:

[0558] The terminal sends user input information and generated emotion status to the server. The data sent includes text information and numerical emotion indicators. For example, it might be sent with statuses such as "care services" and "high urgency."

[0559] Step 4:

[0560] The server performs a database search based on the received data. Here, it prioritizes relevant vendor information according to their emotional status. Specifically, it uses an SQL query to extract vendors with the tags "nursing care" and "emergency response available" as priority, and outputs them as a list.

[0561] Step 5:

[0562] The server performs a reliability assessment based on the search results. The evaluation criteria are dynamically adjusted based on the output of the sentiment engine, so for example, vendors with "high ratings" and "quick response capabilities" are ranked higher in the list.

[0563] Step 6:

[0564] The server sends the final evaluated vendor information to the terminal. The output data is formatted as a vendor list with reliability scores and reaches the terminal.

[0565] Step 7:

[0566] The user makes a selection based on the provided vendor information. As a result of the selection, the selected vendor information is sent from the terminal to the server and recorded as feedback. This information will be used for future database adjustments and updates to evaluation criteria.

[0567] (Application Example 2)

[0568] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0569] In modern life support services, it is crucial to quickly and accurately select the appropriate service provider that can respond to the diverse emotions of users. However, conventional systems struggle to personalize services that fully consider users' emotions, and thus fail to adequately improve user satisfaction. Furthermore, the services provided tend to be unbalanced in terms of reliability and speed, without being optimized according to the user's emotional state. To solve this problem, it is necessary to recognize the user's emotions and optimize services accordingly.

[0570] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0571] In this invention, the server includes receiving means for receiving consultation content from users and analyzing their emotions; searching means for obtaining relevant business information from a data set based on the consultation content and the analyzed emotions; and evaluation means for performing a reliability evaluation on the obtained business information and dynamically adjusting the evaluation criteria based on the emotions. This makes it possible to select an appropriate business and personalize services according to the user's emotions.

[0572] A "receiving means" refers to a device or system that receives the content of a consultation from a user and analyzes their emotions based on the content and input method.

[0573] A "search tool" refers to a device or mechanism for appropriately obtaining relevant business information from a database based on the received consultation content and analyzed emotions.

[0574] "Evaluation methods" refer to devices or mechanisms that perform reliability assessments on acquired business information and dynamically adjust evaluation criteria based on user sentiment.

[0575] "Transmission means" refers to devices or mechanisms for accurately and quickly transmitting evaluated business information to user devices.

[0576] An "update mechanism" refers to a device or system for saving user selection information and periodically updating the data collection.

[0577] An "emotion engine" is a program or system that recognizes the user's emotions and uses that information to personalize services.

[0578] "Spatial information" refers to geographical data and location information, and is used to filter business information within a specific region.

[0579] "Opinions" refer to evaluations and feedback information provided by multiple evaluation organizations, and are the basis for appropriately updating the reliability assessment of a business operator.

[0580] "Optimization" refers to taking into account the emotional state of the user and making the most effective and efficient choices in the process of providing a service.

[0581] The system for realizing this invention consists of a user terminal, a server, and an emotion engine. The user inputs the consultation details using the user terminal. The input information is received by a receiving means, and the emotion engine on the terminal analyzes the emotions. The emotion engine generates an emotion status using a text analysis library (e.g., TextBlob or VADER).

[0582] The server receives the consultation details and emotional status via a search mechanism and retrieves relevant business information from the database based on this information. The server executes database queries (e.g., SQL queries) to filter and retrieve business information. By utilizing spatial information during this process, it is possible to narrow down the search to only the most appropriate businesses based on location.

[0583] The evaluation system assesses the reliability of the acquired information and dynamically adjusts the evaluation criteria according to the emotional status. This process incorporates feedback from multiple evaluation organizations. As a result of the evaluation, the most suitable service provider is selected to match the user's choice. This evaluation process is based on statistical methods and machine learning models, using data analysis tools such as Python and R.

[0584] Subsequently, the evaluated service provider information is sent to the user's terminal using a transmission method. The user selects a service provider from the presented information, and this selection information is sent to the server via an update method and reflected in the database. The updated data will be used to improve future service provision, enabling better choices that meet the user's needs.

[0585] For example, if a user says, "I'm really tired today, so I want to order from a place where I can feel safe," the emotion engine will identify "fatigue" and "safety" as keywords and prioritize suggesting highly trustworthy businesses.

[0586] Examples of prompts for a generative AI model include:

[0587] "If a user enters, 'I'm really tired today, so I want to order from a reliable source,' what kind of sentiment analysis should be performed? And then, generate a list of highly reliable service providers."

[0588] It is in that form.

[0589] In this way, the entire system works in coordination, enabling the delivery of effective services that respond to the user's emotions.

[0590] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0591] Step 1:

[0592] The user inputs their consultation details using a terminal. The entered text data is passed to a receiving device, where an initial analysis is performed by the emotion engine. The input is the user's consultation details, and the output is data with an added emotion status. At this time, a text analysis library is used to identify emotion cues such as "urgency" and "sense of security" from the context.

[0593] Step 2:

[0594] The server receives consultation content with emotional status sent from the terminal. Next, it uses a search mechanism to match the consultation content and emotional status with related information in the database. The input is consultation data with emotional status, and the output is a set of related business information. Filtering is performed through database queries based on spatial information and past evaluation data.

[0595] Step 3:

[0596] The server uses evaluation tools to assess the reliability of acquired business information and performs dynamic evaluations based on emotional status. The input is the acquired business information, and the output is a list of businesses with added reliability ratings. Depending on the emotional state, evaluations are performed using statistical analysis and machine learning models based on feedback from multiple evaluation organizations.

[0597] Step 4:

[0598] The server transmits a list of trusted service providers to the user's terminal via a transmission method. The output list is sorted according to the evaluation criteria, with the most relevant service provider information displayed at the top. This process uses a communication protocol to efficiently and quickly transfer data.

[0599] Step 5:

[0600] The user makes a selection from a list of service providers displayed on their device. This selection information is sent to the server via an update mechanism and used to update the database. The user's selection information is retrieved and used to update the database, contributing to improved search accuracy in subsequent searches.

[0601] Through this series of processes, it becomes possible to provide flexible and personalized services based on the user's emotions.

[0602] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0603] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0604] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0605] [Fourth Embodiment]

[0606] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0607] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0608] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0609] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0610] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0611] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0612] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0613] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0614] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0615] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0616] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0617] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0618] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0619] This invention aims to build an integrated platform for providing reliable community-based support services. The system operates through a program and functions through the cooperation of users, terminals, and servers.

[0620] First, users use their devices to input information about problems or inquiries that have occurred in their area. For example, if a user wants "air conditioner repair," they use their device to fill in the details of the inquiry and the desired service, and then submit the request.

[0621] Next, the terminal sends the user's input to the server. The server receives this information and retrieves relevant vendor information from its database. Specifically, it filters for vendors related to "air conditioner repair" and organizes the results.

[0622] The server performs a reliability assessment on the acquired vendor information. This assessment considers factors such as past performance, customer reviews, and feedback from the local community. This assessment allows for the definition of a vendor's reliability rank.

[0623] The server then sends the evaluation results along with detailed information about the vendors to the user's device. The user can then review this information on their device and select their preferred vendor.

[0624] When a user selects a service provider, the device reports the selection information to the server. This information is recorded in a database by the server and used for future evaluation updates and service improvements.

[0625] Furthermore, user feedback and selection information are automatically reflected in the database, contributing to further improvements in service quality. This system facilitates the provision of community-based services and serves as an effective means of quickly resolving household and equipment-related issues.

[0626] The following describes the processing flow.

[0627] Step 1:

[0628] Users use their devices to enter their inquiry details and residential area information into a dedicated input form. For example, if they want to request a water leak repair, they enter that information, fill in the necessary details, and press the submit button.

[0629] Step 2:

[0630] The terminal organizes the input data and sends it to the server using a secure communication protocol. During this process, the data is encrypted to maintain confidentiality.

[0631] Step 3:

[0632] The server searches its database for relevant service providers based on the consultation details and regional information received from the terminal. The server executes a query and lists the corresponding service providers.

[0633] Step 4:

[0634] The server performs a reliability assessment on the acquired vendor information. This assessment uses factors such as the vendor's past performance, feedback from evaluation agencies, and customer reviews. A reliability rank is then assigned to each vendor.

[0635] Step 5:

[0636] The server reorganizes vendor information, adding reliability ratings, and sends it to the user's terminal. This information package includes vendor contact information, available services, and pricing.

[0637] Step 6:

[0638] The user reviews the transmitted vendor information on their device and selects their preferred vendor. The user then examines the details and makes a decision to proceed with a specific service request.

[0639] Step 7:

[0640] The terminal then resends the user's selected vendor information to the server. This includes the ID of the selected vendor and the associated query details.

[0641] Step 8:

[0642] The server receives user selection information and records it in the database. This information is useful for future evaluation updates and improving vendor reliability, leading to overall system quality improvement.

[0643] (Example 1)

[0644] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0645] There is a need for a platform that can provide life support services that can respond quickly and reliably to the diverse challenges and needs faced by users in their communities. However, with conventional systems, it has been difficult to quickly find reliable service providers, and there have been limitations in improving user satisfaction.

[0646] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0647] In this invention, the server includes a device for receiving the content of a problem from a user, a device for acquiring relevant vendor information from an information source based on the content of the problem, and a device for storing the user's selection information and updating the information source. This makes it possible to quickly acquire highly reliable vendor information and propose it to the user.

[0648] A "user" is an individual or organization that uses the system to input their issues and needs and receives services from that system.

[0649] A "receiving device" is a device that receives the task details from the user in digital format and passes them on to the next processing device.

[0650] A "source of information" refers to a database or other information provider that the system accesses to obtain vendor information.

[0651] An "acquisition device" is a device used to retrieve relevant vendor information from information sources based on the content of the received issue.

[0652] An "evaluation device" is a device that assigns reliability based on acquired vendor information, taking into account past performance and evaluations.

[0653] A "transmission device" is a device that has the function of transmitting evaluated vendor information to the user's device.

[0654] A "storage device" is a device that records user selection information and uses it for future data analysis and system improvement.

[0655] An "update device" is a device that keeps information sources up-to-date based on user selections and feedback.

[0656] "Feedback information" refers to information received from users regarding their evaluations of services and vendors, as well as suggestions for improvement.

[0657] "Reliability evaluation" is an assessment that expresses the reliability of a service provider as a numerical value or rank, and is an important indicator for users when choosing a service provider.

[0658] This system is an integrated platform for effectively providing local life support services, with users, terminals, and servers working together. The system is designed to quickly resolve the wide range of challenges users may encounter.

[0659] Users input task details via a dedicated application using devices such as smartphones or computers. This input includes specific service requests, such as "I would like to request air conditioner repair." The entered task details are transmitted to a server via the internet.

[0660] The server analyzes the received issue and retrieves relevant vendor information from a database or other sources. Based on the vendor information, the server performs a reliability assessment and uses an algorithm to calculate a rating rank for each vendor. This algorithm takes into account past performance, rating scores, and feedback from the local community.

[0661] Next, the server organizes the evaluated vendor information and sends it back to the terminal, helping the user select a trustworthy vendor. The user selects the best vendor from the provided list and reports their selection to the server. This information is stored in a database and used to update vendor ratings and improve services in the future.

[0662] As a concrete example, when a user requests a "garden pruning service," they enter their request into a terminal and send it to the server. The server filters highly-rated gardeners in the area and presents them to the user along with their reliability ranking. The user can then select from the list and utilize the service.

[0663] The generative AI model is used by the system to learn from external data and suggest the most suitable vendors. An example of a prompt might be: "Explain how the server evaluates vendor reliability and presents appropriate options to the user on a service platform specializing in local problem solving." Through this implementation, the system supports the provision of fast, reliable services tailored to local needs.

[0664] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0665] Step 1:

[0666] The user opens a dedicated application on their device, enters the details of the problem or inquiry, and presses the submit button. The input includes a specific request, such as "I would like to request air conditioner repair." The device then formats the user's request data and sends it to the server via the internet.

[0667] Step 2:

[0668] The server receives data sent from the terminal and analyzes its contents. It receives user requests as input and extracts keywords using its analysis engine. Specifically, based on the keyword "air conditioner repair," it instructs the server to retrieve relevant contractor information from the database.

[0669] Step 3:

[0670] The server performs a database search to retrieve relevant vendor information. Using the extracted keywords as input, it filters the database to obtain a list of "air conditioner repair" vendors. As output, it creates a list of vendors that appear to be reliable.

[0671] Step 4:

[0672] The server applies a reliability evaluation algorithm to the acquired vendor information. The input consists of the vendor's past performance and customer evaluation data. By performing data calculations, the server assigns a rank to each vendor and outputs the evaluation result by calculating the reliability rank.

[0673] Step 5:

[0674] The server organizes vendor information with reliability rankings and prepares it for transmission to the terminal. As input, it processes the ranked vendor list and formats it into a user-friendly format. As output, it creates vendor information to be sent to the terminal.

[0675] Step 6:

[0676] The user reviews the list of rated service providers displayed on the terminal and selects the service provider they wish to use. The terminal then confirms the information of the selected service provider and sends it to the server as output.

[0677] Step 7:

[0678] The terminal sends the selected vendor information to the server, which receives it and stores it in a database. The input includes the selected vendor information, which is stored for future service improvements and reliability evaluation updates. The output is the updated database.

[0679] (Application Example 1)

[0680] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0681] To provide prompt and reliable life support services in local communities, it is necessary to have information on appropriate products and services that meet the needs of users. However, the current system is insufficient in obtaining the information users need and in evaluating the reliability of service providers, making it difficult to achieve satisfactory results for users. To solve this problem, it is necessary to build a system that provides accurate and reliable information quickly and improves convenience.

[0682] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0683] In this invention, the server includes a receiving means using a terminal device that receives inquiries from users, a search means for obtaining relevant provider information from an information recording medium based on the inquiries, and an evaluation means for assigning a reliability rating to the obtained provider information. This makes it possible to quickly select products and services that users need within their region and provide the information while ensuring its reliability.

[0684] A "terminal device" is a portable information processing device used by users to input and receive information.

[0685] An "information recording medium" is a data storage device or medium used to store provider information and reliability data, and to retrieve them.

[0686] "Reliability assessment" is the process of quantifying or ranking the trustworthiness of a provider based on factors such as the provider's track record, customer reviews, and opinions from evaluation organizations.

[0687] A "portable information processing device" is a device that can process and communicate information while being mobile, and includes smartphones and tablets.

[0688] "Selection" is the process of finding the appropriate information or item from among multiple pieces of information based on specified criteria.

[0689] An "evaluation body" is a professional institution or organization that evaluates goods or services based on specific criteria.

[0690] The system for implementing this invention mainly consists of the cooperation of a server, a terminal device, and a mobile information processing device. The user uses a mobile information processing device (e.g., a smartphone) to input their desire to acquire local products and services. The terminal device receives this input information and transmits it to the server.

[0691] Based on the received information, the server searches for relevant provider information from the information storage medium. This includes retrieving details of commercially available products and information on local service providers from the database. An evaluation method is used to assign a reliability rating to the retrieved provider information. This evaluation method calculates the reliability of the provider by considering feedback from evaluation organizations and past performance.

[0692] Finally, the server sends the evaluated provider information to the user's mobile device. This allows the user to easily view reliable information and select the services and products they need.

[0693] For example, if a user requests information on "recommended refrigerator items," the server will list highly-rated products in the area and send that information to the user. This allows users to efficiently select products both inside and outside the store.

[0694] An example of a prompt to be input into the generating AI model is: "The user inputs an inquiry about products or services they want in the store. The server performs a reliability evaluation and returns the results to the app, allowing the user to make the best choice. How can this process be made more effective?" This invention enables the provision of locally focused information and improves user convenience.

[0695] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0696] Step 1:

[0697] The user uses a mobile information processing device to input details about the desired product or service. The entered information is received by a terminal device. The data entered consists of details about the desired product or service.

[0698] Step 2:

[0699] The terminal sends the received consultation details to the server. Based on this information, the server searches for relevant provider information from its information storage medium. The input here is the consultation details from the user, and the output is provider information. The server uses a search algorithm to extract highly relevant provider information.

[0700] Step 3:

[0701] The server performs a reliability assessment on the acquired provider information. This process assigns a reliability score to providers based on feedback from multiple evaluation organizations and past usage data. The input is provider information and reliability evaluation criteria, while the output is provider information with assigned reliability scores.

[0702] Step 4:

[0703] The server transmits the evaluated provider information to the user's mobile information processing device. The user then selects products or services based on the received information. The input here is provider information, including reliability ratings, and the output is detailed information displayed to the user.

[0704] Step 5:

[0705] The information selected by the user is sent back to the server via the terminal device, and a process is executed to update the selected provider information. This ensures that the information recording medium reflects the latest user selection data. The input is the user's selection information, and the output is the updated provider information database.

[0706] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0707] This invention is a system that combines an emotion engine with a platform that provides reliable community-based life support services, thereby enabling the delivery of services that respond to the user's emotions. In this system, the user, terminal, and server work in cooperation.

[0708] The user first enters the details of their inquiry and their location through their device. At this time, the emotion engine recognizes the user's emotions from their conversational style and input method, and generates an emotion status. For example, if the user strongly indicates urgency, the emotion status will be determined to be high urgency.

[0709] Next, the terminal sends the user's input and emotional status to the server. The server searches its database for relevant vendor information based on the received data. In doing so, it takes the emotional status into consideration and prioritizes selecting vendors who can respond quickly if the situation is urgent.

[0710] The server then assigns a reliability rating to the retrieved vendor information. The emotion engine further dynamically adjusts the evaluation criteria based on the user's emotions to select the best vendor for the user. For example, if the user expresses anxiety, it prioritizes suggesting vendors with higher reliability ratings.

[0711] The server ultimately sends information, including the adjusted vendor information and ratings, to the user's terminal. The user can then select a vendor based on this information. The selected vendor's information is then fed back to the server. This information is used to update the database and is reflected in subsequent service provision.

[0712] This system enables the personalization of the user experience through emotion recognition, making locally-focused service delivery more effective and smoother. By offering service suggestions that take user emotions into consideration, it can improve convenience and satisfaction.

[0713] The following describes the processing flow.

[0714] Step 1:

[0715] The user enters their consultation details and location using a device. During input, an emotion engine analyzes the user's emotions on the device and generates an emotion status. For example, it detects urgency and anxiety from the user's voice and text during input.

[0716] Step 2:

[0717] The terminal transmits the user's consultation details, local information, and emotional status to the server. An encrypted data transfer protocol is used for this purpose.

[0718] Step 3:

[0719] The server searches its database for relevant vendor information based on the received information. Depending on the emotional status, for example, if the situation is "high urgency," it performs filtering to prioritize vendors that can provide 24-hour service.

[0720] Step 4:

[0721] The server performs a reliability assessment on vendor information. The evaluation method calculates the vendor's reliability using multiple feedback data, and this determines the vendor's rank. If the emotional status is "anxious," reliable vendors are prioritized and selected.

[0722] Step 5:

[0723] The server aggregates information on selected vendors and reliability evaluation results, and transmits them to the user's terminal. This includes vendor contact information, service details, and quotation information.

[0724] Step 6:

[0725] The user reviews the vendor information received through their device and selects their preferred vendor. Once the user confirms their selection, the device sends that information to the server, where it is recorded in the database.

[0726] Step 7:

[0727] The server updates the database based on user selection information. This data is used for future evaluations and is reflected in updating the vendor list and improving reliability ratings. The server uses this data to improve the overall service quality of the system.

[0728] (Example 2)

[0729] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0730] In local service provision, there is a challenge in the lack of personalized service proposals that respond to the user's emotions. This can lead to decreased user satisfaction and convenience, and make it difficult to select the right service provider.

[0731] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0732] In this invention, the server includes means for receiving information and sentiment data from users, means for searching a database for vendor information based on the information and sentiment data, and means for assigning a reliability evaluation to the retrieved vendor information that takes sentiment data into consideration. This makes it possible to propose appropriate and reliable services based on the user's sentiment.

[0733] A "user" is an individual or organization that seeks consultation or service provision through the system.

[0734] "Information" refers to data such as consultation details and local information that users input into the system.

[0735] "Emotional data" refers to information that indicates the emotional state of a user, analyzed based on the user's input and methods.

[0736] "Receiving means" refers to a device or program that has the function of acquiring information and emotional data from users.

[0737] A "search tool" is a device or program that has the function of searching a database for relevant vendor information based on received information and sentiment data.

[0738] "Evaluation means" refers to a device or program that has the function of evaluating the reliability of retrieved vendor information by reflecting received sentiment data.

[0739] "Transmission means" refers to a device or program that has the function of sending evaluated vendor information to the user's terminal.

[0740] An "update mechanism" is a device or program that has the function of saving user-selected data and updating the system's database with new information.

[0741] This invention aims to realize a system that proposes optimal services while considering the user's emotions in a community-based service delivery platform. In this system, the terminal, server, and emotion engine work together to provide personalized services that respond to the user's inquiries and emotions.

[0742] First, the user inputs their consultation details and local information using a computer terminal. The terminal is equipped with emotion recognition software, which analyzes the user's input and emotional status using an emotion engine. This emotion engine generates emotional data based on the user's input speed, tone, and keywords in the content. This software analyzes emotions using, for example, NLP libraries and AI algorithms.

[0743] Next, the terminal sends the collected information and sentiment data to the server. The server uses its database to search for relevant vendor information based on the received information. The search is prioritized based on the user's sentiment data. The server then performs a reliability evaluation of the retrieved vendor information, taking the sentiment data into account. This reliability evaluation is dynamically adjusted according to the user's sentiment status to select the most suitable vendor.

[0744] For example, if a user enters "I need medical services that can respond to a sudden change in my health," the emotion engine will determine that this is a "high-priority" situation. This information is sent to the server, which then lists medical services that can respond immediately and displays highly reliable providers first.

[0745] One example of inputting a prompt into a generative AI model is, "Based on the user's sentiment data, please tell me which vendor is most appropriate." This prompt allows the sentiment engine to dynamically suggest the most suitable service.

[0746] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0747] Step 1:

[0748] The user uses a device to input their inquiry details and location information. A sample input example is provided: "I'm looking for care services. Please specify the area (Tokyo)." The entered information is sent to the emotion engine and added to an internal queue for analysis.

[0749] Step 2:

[0750] The device passes the input to the emotion engine, which analyzes the user's emotions. The emotion engine uses a natural language processing library to generate the user's emotional status (e.g., urgency or anxiety level) from the input keywords, input speed, and context. As a result, an emotional status such as "reassured" or "highly urgent" is output.

[0751] Step 3:

[0752] The terminal sends user input information and generated emotion status to the server. The data sent includes text information and numerical emotion indicators. For example, it might be sent with statuses such as "care services" and "high urgency."

[0753] Step 4:

[0754] The server performs a database search based on the received data. Here, it prioritizes relevant vendor information according to their emotional status. Specifically, it uses an SQL query to extract vendors with the tags "nursing care" and "emergency response available" as priority, and outputs them as a list.

[0755] Step 5:

[0756] The server performs a reliability assessment based on the search results. The evaluation criteria are dynamically adjusted based on the output of the sentiment engine, so for example, vendors with "high ratings" and "quick response capabilities" are ranked higher in the list.

[0757] Step 6:

[0758] The server sends the final evaluated vendor information to the terminal. The output data is formatted as a vendor list with reliability scores and reaches the terminal.

[0759] Step 7:

[0760] The user makes a selection based on the provided vendor information. As a result of the selection, the selected vendor information is sent from the terminal to the server and recorded as feedback. This information will be used for future database adjustments and updates to evaluation criteria.

[0761] (Application Example 2)

[0762] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0763] In modern life support services, it is crucial to quickly and accurately select the appropriate service provider that can respond to the diverse emotions of users. However, conventional systems struggle to personalize services that fully consider users' emotions, and thus fail to adequately improve user satisfaction. Furthermore, the services provided tend to be unbalanced in terms of reliability and speed, without being optimized according to the user's emotional state. To solve this problem, it is necessary to recognize the user's emotions and optimize services accordingly.

[0764] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0765] In this invention, the server includes receiving means for receiving consultation content from users and analyzing their emotions; searching means for obtaining relevant business information from a data set based on the consultation content and the analyzed emotions; and evaluation means for performing a reliability evaluation on the obtained business information and dynamically adjusting the evaluation criteria based on the emotions. This makes it possible to select an appropriate business and personalize services according to the user's emotions.

[0766] A "receiving means" refers to a device or system that receives the content of a consultation from a user and analyzes their emotions based on the content and input method.

[0767] A "search tool" refers to a device or mechanism for appropriately obtaining relevant business information from a database based on the received consultation content and analyzed emotions.

[0768] "Evaluation methods" refer to devices or mechanisms that perform reliability assessments on acquired business information and dynamically adjust evaluation criteria based on user sentiment.

[0769] "Transmission means" refers to devices or mechanisms for accurately and quickly transmitting evaluated business information to user devices.

[0770] An "update mechanism" refers to a device or system for saving user selection information and periodically updating the data collection.

[0771] An "emotion engine" is a program or system that recognizes the user's emotions and uses that information to personalize services.

[0772] "Spatial information" refers to geographical data and location information, and is used to filter business information within a specific region.

[0773] "Opinions" refer to evaluations and feedback information provided by multiple evaluation organizations, and are the basis for appropriately updating the reliability assessment of a business operator.

[0774] "Optimization" refers to taking into account the emotional state of the user and making the most effective and efficient choices in the process of providing a service.

[0775] The system for realizing this invention consists of a user terminal, a server, and an emotion engine. The user inputs the consultation details using the user terminal. The input information is received by a receiving means, and the emotion engine on the terminal analyzes the emotions. The emotion engine generates an emotion status using a text analysis library (e.g., TextBlob or VADER).

[0776] The server receives the consultation details and emotional status via a search mechanism and retrieves relevant business information from the database based on this information. The server executes database queries (e.g., SQL queries) to filter and retrieve business information. By utilizing spatial information during this process, it is possible to narrow down the search to only the most appropriate businesses based on location.

[0777] The evaluation system assesses the reliability of the acquired information and dynamically adjusts the evaluation criteria according to the emotional status. This process incorporates feedback from multiple evaluation organizations. As a result of the evaluation, the most suitable service provider is selected to match the user's choice. This evaluation process is based on statistical methods and machine learning models, using data analysis tools such as Python and R.

[0778] Subsequently, the evaluated service provider information is sent to the user's terminal using a transmission method. The user selects a service provider from the presented information, and this selection information is sent to the server via an update method and reflected in the database. The updated data will be used to improve future service provision, enabling better choices that meet the user's needs.

[0779] For example, if a user says, "I'm really tired today, so I want to order from a place where I can feel safe," the emotion engine will identify "fatigue" and "safety" as keywords and prioritize suggesting highly trustworthy businesses.

[0780] Examples of prompts for a generative AI model include:

[0781] "If a user enters, 'I'm really tired today, so I want to order from a reliable source,' what kind of sentiment analysis should be performed? And then, generate a list of highly reliable service providers."

[0782] It is in that form.

[0783] In this way, the entire system works in coordination, enabling the delivery of effective services that respond to the user's emotions.

[0784] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0785] Step 1:

[0786] The user inputs their consultation details using a terminal. The entered text data is passed to a receiving device, where an initial analysis is performed by the emotion engine. The input is the user's consultation details, and the output is data with an added emotion status. At this time, a text analysis library is used to identify emotion cues such as "urgency" and "sense of security" from the context.

[0787] Step 2:

[0788] The server receives consultation content with emotional status sent from the terminal. Next, it uses a search mechanism to match the consultation content and emotional status with related information in the database. The input is consultation data with emotional status, and the output is a set of related business information. Filtering is performed through database queries based on spatial information and past evaluation data.

[0789] Step 3:

[0790] The server uses evaluation tools to assess the reliability of acquired business information and performs dynamic evaluations based on emotional status. The input is the acquired business information, and the output is a list of businesses with added reliability ratings. Depending on the emotional state, evaluations are performed using statistical analysis and machine learning models based on feedback from multiple evaluation organizations.

[0791] Step 4:

[0792] The server transmits a list of trusted service providers to the user's terminal via a transmission method. The output list is sorted according to the evaluation criteria, with the most relevant service provider information displayed at the top. This process uses a communication protocol to efficiently and quickly transfer data.

[0793] Step 5:

[0794] The user makes a selection from a list of service providers displayed on their device. This selection information is sent to the server via an update mechanism and used to update the database. The user's selection information is retrieved and used to update the database, contributing to improved search accuracy in subsequent searches.

[0795] Through this series of processes, it becomes possible to provide flexible and personalized services based on the user's emotions.

[0796] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0797] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0798] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0799] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0800] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0801] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0802] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0803] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0804] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0805] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0806] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0807] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0808] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0809] 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.

[0810] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0811] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0812] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0813] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0814] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0815] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0816] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0817] The following is further disclosed regarding the embodiments described above.

[0818] (Claim 1)

[0819] A means of receiving information about consultations from users,

[0820] A search means for obtaining relevant vendor information from a database based on the aforementioned consultation content,

[0821] An evaluation method for assigning reliability ratings to acquired vendor information,

[0822] A transmission means for sending evaluated vendor information to the user's terminal,

[0823] A means of updating the database to save user selection information,

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1, wherein the search means filters business information using regional information.

[0827] (Claim 3)

[0828] The system according to claim 1, wherein the evaluation means updates the reliability evaluation of a vendor using feedback from multiple evaluation organizations.

[0829] "Example 1"

[0830] (Claim 1)

[0831] A device that receives the content of the issues from the user,

[0832] A device for obtaining relevant vendor information from a source based on the aforementioned problem description,

[0833] A device that assigns a reliability rating to acquired vendor information,

[0834] A device that transmits evaluated vendor information to the user's device,

[0835] A device that stores user selection information and updates information sources,

[0836] A device that improves reliability evaluation by incorporating user feedback information,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, wherein the acquisition device selects vendor information using regional information.

[0840] (Claim 3)

[0841] The system according to claim 1, wherein the evaluation device modifies the reliability evaluation of a vendor using evaluation information from multiple information organizations.

[0842] "Application Example 1"

[0843] (Claim 1)

[0844] A receiving means using a terminal device that receives the content of inquiries from users,

[0845] A search means for obtaining relevant provider information from an information recording medium based on the aforementioned consultation content,

[0846] An evaluation means for assigning a reliability assessment to the acquired provider information,

[0847] A transmission means for transmitting evaluated provider information to the user's mobile information processing device,

[0848] An update method that updates the record using user selection information,

[0849] A means of receiving information regarding requests for product acquisition within the store and providing that product information,

[0850] An information processing system that includes this.

[0851] (Claim 2)

[0852] The information processing system according to claim 1, wherein the search means selects provider information using regional characteristic information.

[0853] (Claim 3)

[0854] The information processing system according to claim 1, wherein the evaluation means updates the reliability evaluation of the provider using opinions from multiple evaluation organizations.

[0855] "Example 2 of combining an emotion engine"

[0856] (Claim 1)

[0857] A receiving means for receiving information and emotional data from users,

[0858] A search means for retrieving vendor information from a database based on the aforementioned information and sentiment data,

[0859] An evaluation method that assigns a reliability rating to the searched vendor information, taking sentiment data into consideration,

[0860] A transmission means for sending evaluated vendor information to the user's terminal,

[0861] A means of updating the database by accumulating user selection data,

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, wherein the search means prioritizes vendor information based on sentiment data.

[0865] (Claim 3)

[0866] The system according to claim 1, wherein the evaluation means dynamically adjusts individual evaluation criteria to update the reliability evaluation.

[0867] "Application example 2 when combining with an emotional engine"

[0868] (Claim 1)

[0869] A receiving method for receiving consultation content from users and analyzing their emotions,

[0870] A search means for obtaining relevant business information from a database based on the aforementioned consultation content and analyzed emotions,

[0871] An evaluation method that performs a reliability assessment on acquired business information and dynamically adjusts the evaluation criteria based on sentiment,

[0872] A transmission means for transmitting evaluated business information to a user device,

[0873] A means of updating the data collection by saving user selection information,

[0874] A system that includes an emotion engine to personalize services in response to the user's emotions.

[0875] (Claim 2)

[0876] The system according to claim 1, wherein the search means filters business information using spatial information.

[0877] (Claim 3)

[0878] The system according to claim 1, wherein the evaluation means updates the reliability evaluation of a business operator using opinions from multiple evaluation organizations and optimizes it based on emotional state. [Explanation of Symbols]

[0879] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving information about consultations from users, A search means for obtaining relevant vendor information from a database based on the aforementioned consultation content, An evaluation method for assigning reliability ratings to acquired vendor information, A transmission means for sending evaluated vendor information to the user's terminal, A means of updating the database to save user selection information, A system that includes this.

2. The system according to claim 1, wherein the search means filters business information using regional information.

3. The system according to claim 1, wherein the evaluation means updates the reliability evaluation of a vendor using feedback from multiple evaluation organizations.

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