system

Abstract

We provide the system. [Solution] A means for the user to input desired content in natural language on an information processing terminal, A central processing unit that receives and analyzes input data transmitted from the aforementioned information processing terminal, A means including a generative model that retrieves relevant service information from a database based on the aforementioned analysis results and selects the optimal option, means for transmitting and displaying the aforementioned optimal choice to the information processing terminal, A means of receiving user purchase information for services and sharing profits with the service provider, 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 method for controlling a persona chatbot, which is 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 character of the chatbot, 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] When a user searches for a specific service, there is a problem that it takes time and effort to find the optimal option from a vast amount of information. In such a situation of information overload, users are often confused by irrelevant results or miss appropriate options. In addition, the burden associated with manual information comparison and selection is also large. Therefore, there is a need for a system that automatically proposes a service that quickly and accurately responds to user requests and reduces the trouble of selection.

Means for Solving the Problems

[0005] This invention comprises the steps of receiving and analyzing input data from a central processing unit based on the user's intentions entered in natural language through an information processing terminal. Based on the analysis results, it utilizes a generative model to retrieve relevant service information from a database and selects and provides the user with the most suitable option. Furthermore, it transmits the information of the selected service to the information processing terminal and displays it in an appropriate format, enabling the user to easily compare and select. In addition, the central processing unit manages the purchase information of the service selected by the user and automatically distributes profits with the service provider, thereby realizing efficient transactions. Through these functions, it is possible to quickly find the desired service while minimizing the burden on the user.

[0006] An "information processing terminal" is an electronic device that allows users to input information in natural language and receive service suggestions.

[0007] A "user" is an individual or group that uses an information processing terminal to request a specific service.

[0008] A "central processing unit" is a computer device that receives data transmitted from information processing terminals, performs analysis, and selects service information.

[0009] "Input data" refers to natural language text information that a user inputs into an information processing terminal.

[0010] A "generative model" is an artificial intelligence model that analyzes input data and selects the optimal service based on the user's preferences.

[0011] A "database" is a collection of information that stores related service information, which a central processing unit can access and retrieve.

[0012] The "optimal option" is the service proposal selected by the generative model that best matches the user's wishes and conditions.

[0013] "Display" refers to the visual presentation of selected service information on an information processing terminal in a format that the user can confirm.

[0014] "Purchase information" refers to data that shows the transaction details related to the service selected by the user.

[0015] "Profit sharing" is a transaction process in which revenue is shared between the service provider and the system operator. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]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 Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine. **Modes for Carrying Out the Invention**

[0017] 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.

[0018] First, the language used in the following description will be explained.

[0019] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single 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.

[0020] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention relates to an information processing system for enabling users to quickly and appropriately select services. Specific embodiments of the invention are described below.

[0038] This system's basic components are an information processing terminal where users input their desired actions and services in natural language, and a central processing unit (server) that processes the input data and selects services that meet the user's needs. When a user searches for services using the information processing terminal, location information and past usage history are transmitted from the terminal to the server during the input stage.

[0039] The server analyzes the received data based on a generative model and identifies relevant keywords. This lays the foundation for concretizing user preferences and proposing the most suitable services. Based on the keywords obtained as a result of the analysis, the server retrieves highly relevant services from the database and narrows down the options.

[0040] The selected service information is transmitted from the server to the information processing terminal and presented to the user by the terminal. The information is displayed in a visually easy-to-understand format, allowing the user to easily compare options. Once the user selects a specific service and decides to purchase it, the purchase information is sent to the server, completing the transaction.

[0041] Furthermore, this system incorporates a profit-sharing mechanism between the user and the service provider. Once a user's purchase of a service is confirmed, the system is designed to automatically share revenue with the service provider. As a result, users can smoothly enjoy the desired services, and service providers and operators can cooperate to conduct business efficiently.

[0042] For example, if a user enters "I want to go to a highly-rated Italian restaurant in Tokyo" into an information processing terminal, that request is sent to the server. Based on the location information, the server extracts Italian restaurants near the user's current location from its database and presents the best option based on rating, distance, and price. When the user makes a reservation at the selected restaurant, that information is transmitted to the service provider, and the revenue-sharing system is activated.

[0043] This invention enables users to quickly find appropriate services from a vast amount of information and to conduct transactions efficiently.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user activates the information processing terminal and inputs the desired service in natural language. The terminal receives the input text data and combines it with the user's location information and past usage history to create a data packet.

[0047] Step 2:

[0048] The terminal sends the created data packet to the server. During this process, the data is securely encrypted according to the communication protocol.

[0049] Step 3:

[0050] The server decodes the received data packets and analyzes the input text data using natural language processing techniques. This allows it to identify the service the user desires.

[0051] Step 4:

[0052] Based on the analysis results, the server searches the database for information on relevant services. A generative model is used to select the appropriate service, taking into account factors such as past user preferences, review ratings, distance, and price.

[0053] Step 5:

[0054] The server creates a list of selected service information and sends it to the terminal in a visually easy-to-understand format.

[0055] Step 6:

[0056] The terminal displays a list of received services to the user. The user reviews this list and selects the desired service from the presented options.

[0057] Step 7:

[0058] Once the user confirms their selection, the device sends the service purchase information to the server.

[0059] Step 8:

[0060] The server receives the purchase information and notifies the selected service provider of the transaction. Furthermore, it initiates a profit-sharing process within the system and distributes the revenue according to the set percentage.

[0061] (Example 1)

[0062] 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."

[0063] In modern society, it is difficult for users to quickly and accurately select the services they desire from a vast amount of information. Furthermore, there is a need to effectively utilize location information and past behavioral history when finding the optimal service that matches the user's needs. In addition, it is necessary to streamline the purchase process of the selected service and ensure fair profit sharing between the user and the service provider.

[0064] 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.

[0065] In this invention, the server includes means for receiving and analyzing input data, location information, and usage history transmitted from the information processing terminal; means including generation technology for obtaining relevant options from a data storage device based on the analysis results and selecting an optimized option based on evaluation, distance, and price; and profit sharing means for receiving specific selections and service purchase information by the user and sharing profits with the provider. This enables the provision of optimal services that meet the user's wishes, as well as the streamlining of the purchase process and smooth profit sharing with businesses.

[0066] An "information processing terminal" is a device that allows users to input information in natural language and send the desired content or data to a server.

[0067] A "central processing unit" is a computer system that receives data transmitted from information processing terminals and analyzes its contents.

[0068] "Generative technology" refers to a wide range of techniques used to derive the optimal choice based on the results of data analysis.

[0069] A "data storage device" is a storage medium that stores services and related information and accesses them as needed.

[0070] A "profit-sharing mechanism" is a system for appropriately distributing profits between service providers and users based on service purchase information from users.

[0071] "Natural language processing techniques" are technologies that enable computers to understand, analyze, and process content expressed by users in natural language.

[0072] This invention describes a specific embodiment of a system that allows users to efficiently select and purchase services.

[0073] The user inputs their desired service into an information processing terminal using natural language. The terminal transmits the input text data, location information, and past usage history to a server. This provides the basic data needed to realize the user's wishes. The terminal used is expected to be a smartphone or personal computer.

[0074] The server uses a generative AI model to analyze the received data. This model applies natural language processing techniques to analyze user requests and extract relevant keywords. The software used includes natural language processing libraries and cloud-based AI services. Using the results of this analysis, the server retrieves service information from data storage and narrows down the options to those with high ratings and that meet the distance and price criteria.

[0075] The selected service information is transmitted to the information processing terminal in a visually easy-to-understand format. The terminal presents this information to the user, supporting them in making the optimal choice. Once the user completes the purchase of the specified service, the information necessary for profit sharing is returned to the server, ensuring that profits are distributed reliably with the relevant businesses.

[0076] As a concrete example, consider a case where a user inputs, "I want to go to a highly-rated Italian restaurant in Tokyo." This input is sent to the server, which then considers location information, ratings, price, etc., to list suitable Italian restaurants.

[0077] An example of a prompt message might be, "The user is looking for a highly-rated Italian restaurant in Tokyo. Please suggest available services." This system allows users to quickly and efficiently select and use the desired service from a vast amount of information.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The user inputs their desired service into an information processing terminal using natural language. The input is stored as text data on the terminal. At the same time, the user's location information is obtained using the terminal's location information system, and past usage history is retrieved from the terminal's storage. This data is prepared as basic information necessary for service selection.

[0081] Step 2:

[0082] The device sends text data, location information, and usage history to the server. The transmitted data is received by the server and stored in preparation for the next analysis step. This gives the server a foundation to comprehensively understand the user's requests and their background information.

[0083] Step 3:

[0084] The server inputs the received text data into a generating AI model. This model uses natural language processing techniques to analyze the meaning of the input natural language and extract relevant keywords. For example, it identifies keywords such as "Tokyo," "Italian food," and "highly rated," and passes that data to the next processing step.

[0085] Step 4:

[0086] The server searches a data storage device based on the extracted keywords. This data storage device contains a lot of service information. The server filters the options to find the one that best matches the user's requirements in terms of rating, distance, and price. In this process, a database search algorithm is used to quickly retrieve results that match the user's criteria.

[0087] Step 5:

[0088] The server sends filtered options to the terminal. The terminal receives these options and prepares to present them to the user in a visually easy-to-understand format. The user can then browse and compare the options presented in a list format to select the best service.

[0089] Step 6:

[0090] The user makes a reservation or purchase for a service selected through their device. The purchase information obtained as a result of this operation is then sent back to the server, which receives the information.

[0091] Step 7:

[0092] The server distributes revenue appropriately between the service provider and the user based on the received purchase information. This profit-sharing process is handled by an automated calculation program, including the transfer of funds to the service provider. This ensures a smooth service experience for users and strengthens cooperation between service providers and server operators.

[0093] (Application Example 1)

[0094] 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."

[0095] In today's information-saturated world, it's not easy for users to quickly and accurately find the services and products they desire. This is especially true when using physical stores; choosing the best store from a vast array of options is difficult, and smooth reservations and purchases are essential. A system is needed to address these challenges.

[0096] 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.

[0097] In this invention, the server includes means for receiving user requests in natural language, means for selecting the most suitable candidates considering location information and past history, and means for visually displaying relevant candidates. This enables users to efficiently find their desired services or stores and complete transactions smoothly.

[0098] An "information processing device" is a terminal that allows users to input their desired information in natural language.

[0099] A "central processing unit" is a processing unit that receives input data transmitted from information processing units and performs analysis on it.

[0100] A "generative model" is a component that has the function of retrieving relevant service information from a database based on the analysis results and selecting the optimal option.

[0101] "Visual presentation" refers to a method of presenting information in a format that is easy for users to understand.

[0102] A "profit-sharing mechanism" is a system that allows users to share profits with businesses based on the transactions they have conducted.

[0103] "Natural language processing technology" is a technology used to understand and analyze user input.

[0104] "Location information" refers to data about the user's current location.

[0105] "History" refers to past usage records.

[0106] This invention is an information processing system for efficiently finding the services and products that users desire. To implement this system, an information processing device is provided, which allows users to input their desired information in natural language. This information processing device may include common computing devices such as smartphones and tablets.

[0107] The input data is transmitted to the central processing unit (CCU) via the internet. The CCU is a server that uses natural language processing techniques to analyze the input. Specifically, existing natural language processing libraries such as "Google Cloud Natural Language" and "Microsoft Text Analytics" are available. The CCU analyzes the input and identifies relevant keywords and phrases.

[0108] The analyzed data is used to retrieve relevant service information from the database using a generative model. A generative model is a computational model that suggests the optimal option based on the analysis results. The selected information is returned to the information processing device in a visually easy-to-understand format. Users can then select the most suitable service based on this information.

[0109] The system has the ability to provide optimal suggestions by considering the user's location information and past usage history. Location information is obtained using the smartphone's GPS function. Past history is recorded in a database linked to the user account and can be individually customized.

[0110] As a concrete example, consider a scenario where a user inputs "I want to eat delicious pasta this weekend" into an information processing device. The server analyzes this input and visually displays a list of the most suitable Italian restaurants. Based on the displayed information, the user can select a restaurant and make a reservation. Furthermore, once the transaction is complete, profit sharing is automatically handled between the user and the restaurant.

[0111] An example of a prompt statement is as follows:

[0112] "Based on the user's input: 'I want to eat delicious pasta this weekend,' please list the top 5 Italian restaurants using the user's current location and past history."

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The terminal receives the user's request, entered in natural language. This request may include, for example, "I want to eat delicious pasta on the weekend." At this point, the input data is the user's text instruction. The terminal prepares to send this input to the server.

[0116] Step 2:

[0117] The server receives input data sent from the terminal. Based on the received data, it performs natural language processing to analyze the user's preferences. For example, it extracts keywords such as "pasta" and "weekend." Technologies such as Google Cloud Natural Language are used for this data processing. As a result of the analysis, relevant keywords are output.

[0118] Step 3:

[0119] The server uses a generative AI model to perform service information retrieval based on the analysis results. The server queries the database using keywords as arguments to obtain the most relevant store information. At this point, the input is a list of keywords based on the analysis results, and the output is a list of relevant store information. The database contains store locations, ratings, price ranges, availability, etc.

[0120] Step 4:

[0121] The server formats the acquired store information for visual display on the terminal. Here, the information is visually organized in map or list format so that users can easily compare it. The terminal receives the assembled display data and displays the results on the user's screen.

[0122] Step 5:

[0123] The terminal accepts the user's selection. The user selects a service of interest from the presented options and performs a reservation or purchase operation. This operation is sent from the terminal to the server, where processing continues. The input is the user's selection information, and the output is the reservation / purchase information for the selected service.

[0124] Step 6:

[0125] The server receives and processes the selected reservation or purchase information. This processing includes reservation confirmation and purchase procedures with the selected service provider. The system automatically calculates profit sharing and notifies relevant parties as needed. Finally, the user receives feedback on the transaction completion status and confirmation information.

[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 relates to an information processing system that allows users to efficiently select the services they desire, and more particularly to a system that incorporates an emotion engine that recognizes user emotions and optimizes suggested services. Specific embodiments of the invention will be described below.

[0128] This system consists of an information processing terminal, a central processing unit (server), a generative model, and an emotion engine. Users use the information processing terminal to input their desired services in natural language. The terminal transmits the input information to the server, simultaneously sending the user's location information and past usage history.

[0129] The server analyzes the received data and uses generative models and natural language processing techniques to pinpoint the specific services the user desires. The emotion engine then analyzes the user's emotional state from the input language data. This analysis determines how the user is feeling and optimizes the services suggested by the generative model.

[0130] Relevant service information retrieved from the database is presented to the user as the best option, taking into account the user's current emotional state and past emotional history. This allows the user to select a service that resonates with their emotions.

[0131] For example, if a user enters "I'm tired and want to find a spa where I can relax," the server analyzes this information to select spa facilities, and the emotion engine detects "fatigue." Based on this, it emphasizes and suggests services that are particularly relaxing. The user reviews the suggested list on their device, selects a suitable facility, and makes a reservation. Once the selection is complete, the server initiates the profit-sharing process, ensuring a smooth transaction.

[0132] In this way, the present invention provides optimal services that meet the psychological needs of users, improves user satisfaction, and enables efficient market transactions.

[0133] The following describes the processing flow.

[0134] Step 1:

[0135] The user activates the information processing terminal and inputs the desired service in natural language. The terminal creates a data packet that includes the input text data, as well as the user's location information and past usage history.

[0136] Step 2:

[0137] The terminal sends the created data packet to the server. At this time, the data is encrypted using a communication protocol.

[0138] Step 3:

[0139] The server analyzes the received data packets. Using natural language processing techniques, it analyzes the input text data to identify the service the user desires.

[0140] Step 4:

[0141] The server activates the emotion engine based on the analysis results. The emotion engine uses information extracted from the user's input to analyze the user's emotional state and determine what psychological state they are in.

[0142] Step 5:

[0143] The server considers the analysis results of the emotion engine and retrieves relevant service information from the database. A generative model is used to combine the best options to match the user's emotional state and adjust the suggestions accordingly.

[0144] Step 6:

[0145] The server lists the selected service information and sends it to the terminal in a visual format. The terminal receives this information and displays it in a way that is easy for the user to understand.

[0146] Step 7:

[0147] The user reviews the service options presented through the device and selects the one that best suits their needs. Once the user confirms their selection, the device sends the purchase information to the server.

[0148] Step 8:

[0149] The server receives purchase information and notifies the relevant service providers of the transaction. Simultaneously, it automatically initiates the profit-sharing process and distributes the revenue according to the established arrangements.

[0150] (Example 2)

[0151] 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".

[0152] The problem that this invention aims to solve is to improve the user experience by enabling service selection according to the user's emotions and realizing information provision optimized for their emotional state. Conventional systems provide information without considering the user's emotional state, which could lead to decreased user satisfaction.

[0153] 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.

[0154] In this invention, the server includes means for inputting information desired by the user in natural language, a central computer for receiving and analyzing the input information transmitted from the means, and means including a generation algorithm for analyzing the user's emotional state, retrieving relevant information from a data warehouse based on the analysis results, and selecting the optimal choice. This enables the provision of optimal choices based on the user's emotions, thereby improving the user experience.

[0155] "A means of inputting information desired by the user in natural language" refers to an input device or interface for users to input the information or service details they require in natural language format.

[0156] A "central computer" is an information processing device that receives input from users, analyzes it, and processes it.

[0157] The phrase "analyzing the user's emotional state" refers to a technology that has an analytical function to analyze the language data entered by the user and determine their emotions and psychological state.

[0158] "Means including a generation algorithm" refers to an apparatus or system that includes an algorithm or model for generating relevant information based on analysis results.

[0159] A "data warehouse" is a database system that centrally manages diverse data and enables high-speed searching and retrieval of necessary information.

[0160] This invention relates to an information processing system that enables users to efficiently select the services they desire, and more particularly to a system that recognizes user emotions and optimizes suggested services. The system's basic components consist of an information processing terminal, a central computer (server), a generation algorithm, and emotion analysis technology.

[0161] Users use an information processing terminal to input their desired service in natural language. An example input might be, "I want to find a place where I can relax." The terminal sends this input information to a server, which simultaneously provides the user's location information and past usage history.

[0162] The server uses natural language processing techniques to analyze the received data and a generative AI model to identify the services the user desires. During this analysis, an emotion engine is used to analyze the user's emotional state from the text they input. For example, it can detect fatigue from the input "tired."

[0163] The generation algorithm retrieves relevant service information from a data repository based on the user's context and emotions, providing the most appropriate service selection. For example, if a user enters "I want to find a yoga class," the server highlights and presents potential yoga classes that can help reduce stress to the user's information processing terminal. This process allows the user to make a choice that suits their emotional state.

[0164] An example of a prompt to input into the generating AI model is as follows: "Assuming the user intends to relax, please suggest the most suitable spa facility."

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The user uses an information processing terminal to input their desired service details in natural language. This input is text data that expresses the user's requests and desires. For example, it might say, "I want to find a relaxing cafe." The entered data is temporarily stored on the terminal.

[0168] Step 2:

[0169] The terminal sends input text data to the server. During this process, sub-data, including the user's location information and past usage history, is sent to the server as packets along with the input natural language data. This information serves as initial data necessary for service selection.

[0170] Step 3:

[0171] The server analyzes the received text data and subdata. Natural language processing techniques are used here, leveraging generative AI models to gain a detailed understanding of the user's requests. This analysis clarifies the services the user desires and their content. The output at this point is the identified service request.

[0172] Step 4:

[0173] The server uses sentiment analysis technology to analyze the user's emotional state from their input text. The sentiment engine processes the text and identifies emotions such as "fatigue" and "stress." This analysis is used in the optimization process for selecting service candidates. The output here is data about the user's emotional state.

[0174] Step 5:

[0175] The server uses a generation algorithm to retrieve relevant service information from the data repository. The retrieved data is filtered based on the user's emotional state, location, and past usage history, and ranked to determine the most appropriate and useful service options. The output of this process is an optimized list of service candidates.

[0176] Step 6:

[0177] The terminal presents the user with an optimized list of service candidates sent from the server. The user can review the presented information and make a selection that suits their needs. The input in this step is the list of service candidates from the server, and the output is the user's final selection.

[0178] (Application Example 2)

[0179] 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".

[0180] In modern information processing systems, there is a lack of appropriate suggestions that take into account the psychological state and emotions of users when they select the services they desire. Furthermore, while there is a desire for appropriate environmental adjustments based on emotions within the home, there is a problem in the lack of sufficient efficient mechanisms to achieve this.

[0181] 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.

[0182] In this invention, the server includes means for analyzing data transmitted from an information processing device, means for acquiring relevant service information from a storage unit using a generative model and selecting the optimal option, and means for determining the user's emotional state using an emotion engine and adjusting the environment accordingly. This enables the provision of optimal services and environments based on the user's emotions, thereby improving the user experience.

[0183] An "information processing device" is a device that allows users to input desired information using natural language.

[0184] A "central control unit" is a device that receives and analyzes data transmitted from an information processing unit.

[0185] A "generative model" includes an algorithm that acquires service information based on analysis results and selects the optimal option.

[0186] The term "storage unit" refers to the database where information about related services is stored.

[0187] An "emotion engine" is a technology that identifies and analyzes emotional states from user input data.

[0188] "Means for optimally adjusting the environment" refers to functions that allow users to manipulate environmental settings such as lighting, music, and scent according to their emotional state.

[0189] A "vendor" refers to a business that provides services and is the entity that shares profits based on purchase information from users.

[0190] The server receives natural language input data from the user via an information processing terminal, and this data is analyzed by a central control unit. Using the results of the analysis, the generative model retrieves relevant service information from the storage unit and selects the optimal option. Natural language processing technology is used in this process, making it possible to accurately identify what the user desires.

[0191] Furthermore, the emotion engine analyzes the user's emotional state and issues instructions to the environment control system to provide the optimal environment based on the user's emotions. Specifically, various smart devices respond to this, dynamically adjusting settings such as lighting, music, and scent. For example, if the user says, "I want to relax," the emotion engine analyzes that intention and issues instructions to change the lighting to a warm color while simultaneously playing relaxing music.

[0192] The terminal displays optimal options and adjusted settings sent from the server to the user, who can then enjoy the service by confirming them. Furthermore, once the user ultimately purchases or selects a service, the server receives that information and processes the transaction to arrange profit sharing with the service provider. This entire process allows users to seamlessly receive emotionally resonant services.

[0193] An example of a prompt statement using a generative AI model might be an instruction such as, "Write a program that suggests interior design that will help the user relax." This prompt statement is an important element in conveying the user's intent to the system.

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The user inputs their desired information into the information processing terminal using natural language. The input data is then sent directly to the server. In this process, input is either the user's spoken words or text input, and output is the user's request data sent to the server.

[0197] Step 2:

[0198] The server analyzes the data received by the central control unit. Natural language processing techniques are used for the analysis to clarify the user's intent. Through this process, the services and conditions requested by the user are identified from the input data, and the analysis results are sent as output to the generative model.

[0199] Step 3:

[0200] The generative model retrieves service information from the storage unit based on the analysis results. It selects the optimal option by considering data from related services, past usage history, and location information. The inputs here are the analysis results and data from the storage unit, and the output is optimized service information to be presented to the user.

[0201] Step 4:

[0202] The emotion engine analyzes the user's emotional state based on their input data. The analyzed emotions form the basis for environmental adjustments, and the user's emotional state is sent to the environmental control system as output.

[0203] Step 5:

[0204] The environmental control system adjusts the environment via smart devices based on the results of the emotion engine. Specific actions include adjusting the color temperature of the lighting, selecting music, and activating an aroma diffuser. The input is the result of the emotion engine, and the output is the adjusted environmental settings.

[0205] Step 6:

[0206] The server sends the final selection and configuration information to the terminal and displays it to the user. This allows the user to review the suggested services and optimized environment. Optimization information is used as input, and the output is the information displayed on the user's device.

[0207] Step 7:

[0208] The user confirms the selected service on their device and ultimately purchases or selects the service. This information is sent to the server, which provides the user's selection information as input and generates instructions for profit distribution to the service provider as output.

[0209] 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.

[0210] 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.

[0211] 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.

[0212] [Second Embodiment]

[0213] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0214] 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.

[0215] 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).

[0216] 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.

[0217] 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.

[0218] 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).

[0219] 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.

[0220] 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.

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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".

[0225] This invention relates to an information processing system for enabling users to quickly and appropriately select services. Specific embodiments of the invention are described below.

[0226] This system's basic components are an information processing terminal where users input their desired actions and services in natural language, and a central processing unit (server) that processes the input data and selects services that meet the user's needs. When a user searches for services using the information processing terminal, location information and past usage history are transmitted from the terminal to the server during the input stage.

[0227] The server analyzes the received data based on a generative model and identifies relevant keywords. This lays the foundation for concretizing user preferences and proposing the most suitable services. Based on the keywords obtained as a result of the analysis, the server retrieves highly relevant services from the database and narrows down the options.

[0228] The selected service information is transmitted from the server to the information processing terminal and presented to the user by the terminal. The information is displayed in a visually easy-to-understand format, allowing the user to easily compare options. Once the user selects a specific service and decides to purchase it, the purchase information is sent to the server, completing the transaction.

[0229] Furthermore, this system incorporates a profit-sharing mechanism between the user and the service provider. Once a user's purchase of a service is confirmed, the system is designed to automatically share revenue with the service provider. As a result, users can smoothly enjoy the desired services, and service providers and operators can cooperate to conduct business efficiently.

[0230] For example, if a user enters "I want to go to a highly-rated Italian restaurant in Tokyo" into an information processing terminal, that request is sent to the server. Based on the location information, the server extracts Italian restaurants near the user's current location from its database and presents the best option based on rating, distance, and price. When the user makes a reservation at the selected restaurant, that information is transmitted to the service provider, and the revenue-sharing system is activated.

[0231] This invention enables users to quickly find appropriate services from a vast amount of information and to conduct transactions efficiently.

[0232] The following describes the processing flow.

[0233] Step 1:

[0234] The user activates the information processing terminal and inputs the desired service in natural language. The terminal receives the input text data and combines it with the user's location information and past usage history to create a data packet.

[0235] Step 2:

[0236] The terminal sends the created data packet to the server. During this process, the data is securely encrypted according to the communication protocol.

[0237] Step 3:

[0238] The server decodes the received data packets and analyzes the input text data using natural language processing techniques. This allows it to identify the service the user desires.

[0239] Step 4:

[0240] Based on the analysis results, the server searches the database for information on relevant services. A generative model is used to select the appropriate service, taking into account factors such as past user preferences, review ratings, distance, and price.

[0241] Step 5:

[0242] The server creates a list of selected service information and sends it to the terminal in a visually easy-to-understand format.

[0243] Step 6:

[0244] The terminal displays a list of received services to the user. The user reviews this list and selects the desired service from the presented options.

[0245] Step 7:

[0246] Once the user confirms their selection, the device sends the service purchase information to the server.

[0247] Step 8:

[0248] The server receives the purchase information and notifies the selected service provider of the transaction. Furthermore, it initiates a profit-sharing process within the system and distributes the revenue according to the set percentage.

[0249] (Example 1)

[0250] 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."

[0251] In modern society, it is difficult for users to quickly and accurately select the services they desire from a vast amount of information. Furthermore, there is a need to effectively utilize location information and past behavioral history when finding the optimal service that matches the user's needs. In addition, it is necessary to streamline the purchase process of the selected service and ensure fair profit sharing between the user and the service provider.

[0252] 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.

[0253] In this invention, the server includes means for receiving and analyzing input data, location information, and usage history transmitted from the information processing terminal; means including generation technology for obtaining relevant options from a data storage device based on the analysis results and selecting an optimized option based on evaluation, distance, and price; and profit sharing means for receiving specific selections and service purchase information by the user and sharing profits with the provider. This enables the provision of optimal services that meet the user's wishes, as well as the streamlining of the purchase process and smooth profit sharing with businesses.

[0254] An "information processing terminal" is a device that allows users to input information in natural language and send the desired content or data to a server.

[0255] A "central processing unit" is a computer system that receives data transmitted from information processing terminals and analyzes its contents.

[0256] "Generative technology" refers to a wide range of techniques used to derive the optimal choice based on the results of data analysis.

[0257] A "data storage device" is a storage medium that stores services and related information and accesses them as needed.

[0258] A "profit-sharing mechanism" is a system for appropriately distributing profits between service providers and users based on service purchase information from users.

[0259] "Natural language processing techniques" are technologies that enable computers to understand, analyze, and process content expressed by users in natural language.

[0260] This invention describes a specific embodiment of a system that allows users to efficiently select and purchase services.

[0261] The user inputs their desired service into an information processing terminal using natural language. The terminal transmits the input text data, location information, and past usage history to a server. This provides the basic data needed to realize the user's wishes. The terminal used is expected to be a smartphone or personal computer.

[0262] The server uses a generative AI model to analyze the received data. This model applies natural language processing techniques to analyze user requests and extract relevant keywords. The software used includes natural language processing libraries and cloud-based AI services. Using the results of this analysis, the server retrieves service information from data storage and narrows down the options to those with high ratings and that meet the distance and price criteria.

[0263] The selected service information is transmitted to the information processing terminal in a visually easy-to-understand format. The terminal presents this information to the user, supporting them in making the optimal choice. Once the user completes the purchase of the specified service, the information necessary for profit sharing is returned to the server, ensuring that profits are distributed reliably with the relevant businesses.

[0264] As a concrete example, consider a case where a user inputs, "I want to go to a highly-rated Italian restaurant in Tokyo." This input is sent to the server, which then considers location information, ratings, price, etc., to list suitable Italian restaurants.

[0265] An example of a prompt message might be, "The user is looking for a highly-rated Italian restaurant in Tokyo. Please suggest available services." This system allows users to quickly and efficiently select and use the desired service from a vast amount of information.

[0266] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0267] Step 1:

[0268] The user inputs their desired service into an information processing terminal using natural language. The input is stored as text data on the terminal. At the same time, the user's location information is obtained using the terminal's location information system, and past usage history is retrieved from the terminal's storage. This data is prepared as basic information necessary for service selection.

[0269] Step 2:

[0270] The device sends text data, location information, and usage history to the server. The transmitted data is received by the server and stored in preparation for the next analysis step. This gives the server a foundation to comprehensively understand the user's requests and their background information.

[0271] Step 3:

[0272] The server inputs the received text data into a generating AI model. This model uses natural language processing techniques to analyze the meaning of the input natural language and extract relevant keywords. For example, it identifies keywords such as "Tokyo," "Italian food," and "highly rated," and passes that data to the next processing step.

[0273] Step 4:

[0274] The server searches a data storage device based on the extracted keywords. This data storage device contains a lot of service information. The server filters the options to find the one that best matches the user's requirements in terms of rating, distance, and price. In this process, a database search algorithm is used to quickly retrieve results that match the user's criteria.

[0275] Step 5:

[0276] The server sends filtered options to the terminal. The terminal receives these options and prepares to present them to the user in a visually easy-to-understand format. The user can then browse and compare the options presented in a list format to select the best service.

[0277] Step 6:

[0278] The user makes a reservation or purchase for a service selected through their device. The purchase information obtained as a result of this operation is then sent back to the server, which receives the information.

[0279] Step 7:

[0280] The server distributes revenue appropriately between the service provider and the user based on the received purchase information. This profit-sharing process is handled by an automated calculation program, including the transfer of funds to the service provider. This ensures a smooth service experience for users and strengthens cooperation between service providers and server operators.

[0281] (Application Example 1)

[0282] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0283] In modern times when there is an overflow of a lot of information, it is not easy for users to quickly and accurately find the services or products they want. Especially when using physical stores, it is difficult to choose the optimal store from a huge number of options, and it is also required that reservations and purchases are made smoothly. A system for solving such problems is necessary.

[0284] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0285] In this invention, the server includes means for a user to input what they want in natural language, means for selecting an optimal candidate in consideration of location information and past history, and means for displaying candidates that are visually related. Thereby, users can efficiently find the services or stores they want and smoothly complete transactions.

[0286] An "information processing device" is a terminal for a user to input what they want in natural language.

[0287] A "central processing unit" is a processing unit for receiving input data transmitted from the information processing device and performing analysis.

[0288] A "generation model" is a component having a function of acquiring related service information from a database based on the analysis result and selecting an optimal option.

[0289] "Visual display" is a method of presenting information in a form that is easy for users to understand.

[0290] A "profit-sharing mechanism" is a system that allows users to share profits with businesses based on the transactions they have conducted.

[0291] "Natural language processing technology" is a technology used to understand and analyze user input.

[0292] "Location information" refers to data about the user's current location.

[0293] "History" refers to past usage records.

[0294] This invention is an information processing system for efficiently finding the services and products that users desire. To implement this system, an information processing device is provided, which allows users to input their desired information in natural language. This information processing device may include common computing devices such as smartphones and tablets.

[0295] The input data is transmitted to the central processing unit (CCU) via the internet. The CCU is a server that uses natural language processing techniques to analyze the input. Specifically, existing natural language processing libraries such as "Google Cloud Natural Language" and "Microsoft Text Analytics" are available. The CCU analyzes the input and identifies relevant keywords and phrases.

[0296] The analyzed data is used to retrieve relevant service information from the database using a generative model. A generative model is a computational model that suggests the optimal option based on the analysis results. The selected information is returned to the information processing device in a visually easy-to-understand format. Users can then select the most suitable service based on this information.

[0297] The system has the ability to provide optimal suggestions by considering the user's location information and past usage history. Location information is obtained using the smartphone's GPS function. Past history is recorded in a database linked to the user account and can be individually customized.

[0298] As a concrete example, consider a scenario where a user inputs "I want to eat delicious pasta this weekend" into an information processing device. The server analyzes this input and visually displays a list of the most suitable Italian restaurants. Based on the displayed information, the user can select a restaurant and make a reservation. Furthermore, once the transaction is complete, profit sharing is automatically handled between the user and the restaurant.

[0299] An example of a prompt statement is as follows:

[0300] "Based on the user's input: 'I want to eat delicious pasta this weekend,' please list the top 5 Italian restaurants using the user's current location and past history."

[0301] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0302] Step 1:

[0303] The terminal receives the user's request, entered in natural language. This request may include, for example, "I want to eat delicious pasta on the weekend." At this point, the input data is the user's text instruction. The terminal prepares to send this input to the server.

[0304] Step 2:

[0305] The server receives the input data sent from the terminal. Based on the received data, natural language processing is performed to analyze the user's desired content. For example, keywords such as "pasta" and "weekend" are extracted. Technologies such as Google Cloud Natural Language are used for this data processing. As a result of the analysis, relevant keywords are output.

[0306] Step 3:

[0307] The server uses the generative AI model to search for service information based on the analysis result. The server queries the database with the keyword as an argument and obtains the optimal store information. The input at this point is the keyword list based on the analysis result, and the output is the list of related store information. The content of the database includes the location, evaluation, price range, vacancy status, etc. of the store.

[0308] Step 4:

[0309] The server formats the acquired store information for visual display on the terminal. Here, the information is visually arranged in the form of a map or a list so that the user can easily compare. The terminal receives the assembled display data and displays the result on the user's screen.

[0310] Step 5:

[0311] The terminal accepts the user's selection. The user selects a service of interest from the presented ones and performs operations such as reservation or purchase. This operation is sent from the terminal to the server, where the processing continues. The input is the user's selection information, and the output is the reservation / purchase information of the selected service.

[0312] Step 6:

[0313] The server receives and processes the selected reservation or purchase information. This processing includes reservation confirmation and purchase procedures with the selected service provider. The system automatically calculates profit sharing and notifies relevant parties as needed. Finally, the user receives feedback on the transaction completion status and confirmation information.

[0314] 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.

[0315] This invention relates to an information processing system that allows users to efficiently select the services they desire, and more particularly to a system that incorporates an emotion engine that recognizes user emotions and optimizes suggested services. Specific embodiments of the invention will be described below.

[0316] This system consists of an information processing terminal, a central processing unit (server), a generative model, and an emotion engine. Users use the information processing terminal to input their desired services in natural language. The terminal transmits the input information to the server, simultaneously sending the user's location information and past usage history.

[0317] The server analyzes the received data and uses generative models and natural language processing techniques to pinpoint the specific services the user desires. The emotion engine then analyzes the user's emotional state from the input language data. This analysis determines how the user is feeling and optimizes the services suggested by the generative model.

[0318] Relevant service information retrieved from the database is presented to the user as the best option, taking into account the user's current emotional state and past emotional history. This allows the user to select a service that resonates with their emotions.

[0319] For example, if a user enters "I'm tired and want to find a spa where I can relax," the server analyzes this information to select spa facilities, and the emotion engine detects "fatigue." Based on this, it emphasizes and suggests services that are particularly relaxing. The user reviews the suggested list on their device, selects a suitable facility, and makes a reservation. Once the selection is complete, the server initiates the profit-sharing process, ensuring a smooth transaction.

[0320] In this way, the present invention provides optimal services that meet the psychological needs of users, improves user satisfaction, and enables efficient market transactions.

[0321] The following describes the processing flow.

[0322] Step 1:

[0323] The user activates the information processing terminal and inputs the desired service in natural language. The terminal creates a data packet that includes the input text data, as well as the user's location information and past usage history.

[0324] Step 2:

[0325] The terminal sends the created data packet to the server. At this time, the data is encrypted using a communication protocol.

[0326] Step 3:

[0327] The server analyzes the received data packets. Using natural language processing techniques, it analyzes the input text data to identify the service the user desires.

[0328] Step 4:

[0329] The server activates the emotion engine based on the analysis results. The emotion engine uses information extracted from the user's input to analyze the user's emotional state and determine what psychological state they are in.

[0330] Step 5:

[0331] The server considers the analysis results of the emotion engine and retrieves relevant service information from the database. A generative model is used to combine the best options to match the user's emotional state and adjust the suggestions accordingly.

[0332] Step 6:

[0333] The server lists the selected service information and sends it to the terminal in a visual format. The terminal receives this information and displays it in a way that is easy for the user to understand.

[0334] Step 7:

[0335] The user reviews the service options presented through the device and selects the one that best suits their needs. Once the user confirms their selection, the device sends the purchase information to the server.

[0336] Step 8:

[0337] The server receives purchase information and notifies the relevant service providers of the transaction. Simultaneously, it automatically initiates the profit-sharing process and distributes the revenue according to the established arrangements.

[0338] (Example 2)

[0339] 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".

[0340] The problem that this invention aims to solve is to improve the user experience by enabling service selection according to the user's emotions and realizing information provision optimized for their emotional state. Conventional systems provide information without considering the user's emotional state, which could lead to decreased user satisfaction.

[0341] 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.

[0342] In this invention, the server includes means for inputting information desired by the user in natural language, a central computer for receiving and analyzing the input information transmitted from the means, and means including a generation algorithm for analyzing the user's emotional state, retrieving relevant information from a data warehouse based on the analysis results, and selecting the optimal choice. This enables the provision of optimal choices based on the user's emotions, thereby improving the user experience.

[0343] "A means of inputting information desired by the user in natural language" refers to an input device or interface for users to input the information or service details they require in natural language format.

[0344] A "central computer" is an information processing device that receives input from users, analyzes it, and processes it.

[0345] The phrase "analyzing the user's emotional state" refers to a technology that has an analytical function to analyze the language data entered by the user and determine their emotions and psychological state.

[0346] "Means including a generation algorithm" refers to an apparatus or system that includes an algorithm or model for generating relevant information based on analysis results.

[0347] A "data warehouse" is a database system that centrally manages diverse data and enables high-speed searching and retrieval of necessary information.

[0348] This invention relates to an information processing system that enables users to efficiently select the services they desire, and more particularly to a system that recognizes user emotions and optimizes suggested services. The system's basic components consist of an information processing terminal, a central computer (server), a generation algorithm, and emotion analysis technology.

[0349] Users use an information processing terminal to input their desired service in natural language. An example input might be, "I want to find a place where I can relax." The terminal sends this input information to a server, which simultaneously provides the user's location information and past usage history.

[0350] The server uses natural language processing techniques to analyze the received data and a generative AI model to identify the services the user desires. During this analysis, an emotion engine is used to analyze the user's emotional state from the text they input. For example, it can detect fatigue from the input "tired."

[0351] The generation algorithm retrieves relevant service information from a data repository based on the user's context and emotions, providing the most appropriate service selection. For example, if a user enters "I want to find a yoga class," the server highlights and presents potential yoga classes that can help reduce stress to the user's information processing terminal. This process allows the user to make a choice that suits their emotional state.

[0352] An example of a prompt to input into the generating AI model is as follows: "Assuming the user intends to relax, please suggest the most suitable spa facility."

[0353] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0354] Step 1:

[0355] The user uses an information processing terminal to input their desired service details in natural language. This input is text data that expresses the user's requests and desires. For example, it might say, "I want to find a relaxing cafe." The entered data is temporarily stored on the terminal.

[0356] Step 2:

[0357] The terminal sends input text data to the server. During this process, sub-data, including the user's location information and past usage history, is sent to the server as packets along with the input natural language data. This information serves as initial data necessary for service selection.

[0358] Step 3:

[0359] The server analyzes the received text data and subdata. Natural language processing techniques are used here, leveraging generative AI models to gain a detailed understanding of the user's requests. This analysis clarifies the services the user desires and their content. The output at this point is the identified service request.

[0360] Step 4:

[0361] The server uses sentiment analysis technology to analyze the user's emotional state from their input text. The sentiment engine processes the text and identifies emotions such as "fatigue" and "stress." This analysis is used in the optimization process for selecting service candidates. The output here is data about the user's emotional state.

[0362] Step 5:

[0363] The server uses a generation algorithm to retrieve relevant service information from the data repository. The retrieved data is filtered based on the user's emotional state, location, and past usage history, and ranked to determine the most appropriate and useful service options. The output of this process is an optimized list of service candidates.

[0364] Step 6:

[0365] The terminal presents the user with an optimized list of service candidates sent from the server. The user can review the presented information and make a selection that suits their needs. The input in this step is the list of service candidates from the server, and the output is the user's final selection.

[0366] (Application Example 2)

[0367] 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."

[0368] In modern information processing systems, there is a lack of appropriate suggestions that take into account the psychological state and emotions of users when they select the services they desire. Furthermore, while there is a desire for appropriate environmental adjustments based on emotions within the home, there is a problem in the lack of sufficient efficient mechanisms to achieve this.

[0369] 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.

[0370] In this invention, the server includes means for analyzing data transmitted from an information processing device, means for acquiring relevant service information from a storage unit using a generative model and selecting the optimal option, and means for determining the user's emotional state using an emotion engine and adjusting the environment accordingly. This enables the provision of optimal services and environments based on the user's emotions, thereby improving the user experience.

[0371] An "information processing device" is a device that allows users to input desired information using natural language.

[0372] A "central control unit" is a device that receives and analyzes data transmitted from an information processing unit.

[0373] A "generative model" includes an algorithm that acquires service information based on analysis results and selects the optimal option.

[0374] The term "storage unit" refers to the database where information about related services is stored.

[0375] An "emotion engine" is a technology that identifies and analyzes emotional states from user input data.

[0376] "Means for optimally adjusting the environment" refers to functions that allow users to manipulate environmental settings such as lighting, music, and scent according to their emotional state.

[0377] A "vendor" refers to a business that provides services and is the entity that shares profits based on purchase information from users.

[0378] The server receives natural language input data from the user via an information processing terminal, and this data is analyzed by a central control unit. Using the results of the analysis, the generative model retrieves relevant service information from the storage unit and selects the optimal option. Natural language processing technology is used in this process, making it possible to accurately identify what the user desires.

[0379] Furthermore, the emotion engine analyzes the user's emotional state and issues instructions to the environment control system to provide the optimal environment based on the user's emotions. Specifically, various smart devices respond to this, dynamically adjusting settings such as lighting, music, and scent. For example, if the user says, "I want to relax," the emotion engine analyzes that intention and issues instructions to change the lighting to a warm color while simultaneously playing relaxing music.

[0380] The terminal displays optimal options and adjusted settings sent from the server to the user, who can then enjoy the service by confirming them. Furthermore, once the user ultimately purchases or selects a service, the server receives that information and processes the transaction to arrange profit sharing with the service provider. This entire process allows users to seamlessly receive emotionally resonant services.

[0381] An example of a prompt statement using a generative AI model might be an instruction such as, "Write a program that suggests interior design that will help the user relax." This prompt statement is an important element in conveying the user's intent to the system.

[0382] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0383] Step 1:

[0384] The user inputs their desired information into the information processing terminal using natural language. The input data is then sent directly to the server. In this process, input is either the user's spoken words or text input, and output is the user's request data sent to the server.

[0385] Step 2:

[0386] The server analyzes the data received by the central control unit. Natural language processing techniques are used for the analysis to clarify the user's intent. Through this process, the services and conditions requested by the user are identified from the input data, and the analysis results are sent as output to the generative model.

[0387] Step 3:

[0388] The generative model retrieves service information from the storage unit based on the analysis results. It selects the optimal option by considering data from related services, past usage history, and location information. The inputs here are the analysis results and data from the storage unit, and the output is optimized service information to be presented to the user.

[0389] Step 4:

[0390] The emotion engine analyzes the user's emotional state based on their input data. The analyzed emotions form the basis for environmental adjustments, and the user's emotional state is sent to the environmental control system as output.

[0391] Step 5:

[0392] The environmental control system adjusts the environment via smart devices based on the results of the emotion engine. Specific actions include adjusting the color temperature of the lighting, selecting music, and activating an aroma diffuser. The input is the result of the emotion engine, and the output is the adjusted environmental settings.

[0393] Step 6:

[0394] The server sends the final selection and configuration information to the terminal and displays it to the user. This allows the user to review the suggested services and optimized environment. Optimization information is used as input, and the output is the information displayed on the user's device.

[0395] Step 7:

[0396] The user confirms the selected service on their device and ultimately purchases or selects the service. This information is sent to the server, which provides the user's selection information as input and generates instructions for profit distribution to the service provider as output.

[0397] 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.

[0398] 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.

[0399] 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.

[0400] [Third Embodiment]

[0401] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0402] 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.

[0403] 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).

[0404] 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.

[0405] 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.

[0406] 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).

[0407] 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.

[0408] 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.

[0409] 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.

[0410] 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.

[0411] 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.

[0412] 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".

[0413] This invention relates to an information processing system for enabling users to quickly and appropriately select services. Specific embodiments of the invention are described below.

[0414] This system's basic components are an information processing terminal where users input their desired actions and services in natural language, and a central processing unit (server) that processes the input data and selects services that meet the user's needs. When a user searches for services using the information processing terminal, location information and past usage history are transmitted from the terminal to the server during the input stage.

[0415] The server analyzes the received data based on a generative model and identifies relevant keywords. This lays the foundation for concretizing user preferences and proposing the most suitable services. Based on the keywords obtained as a result of the analysis, the server retrieves highly relevant services from the database and narrows down the options.

[0416] The selected service information is transmitted from the server to the information processing terminal and presented to the user by the terminal. The information is displayed in a visually easy-to-understand format, allowing the user to easily compare options. Once the user selects a specific service and decides to purchase it, the purchase information is sent to the server, completing the transaction.

[0417] Furthermore, this system incorporates a profit-sharing mechanism between the user and the service provider. Once a user's purchase of a service is confirmed, the system is designed to automatically share revenue with the service provider. As a result, users can smoothly enjoy the desired services, and service providers and operators can cooperate to conduct business efficiently.

[0418] For example, if a user enters "I want to go to a highly-rated Italian restaurant in Tokyo" into an information processing terminal, that request is sent to the server. Based on the location information, the server extracts Italian restaurants near the user's current location from its database and presents the best option based on rating, distance, and price. When the user makes a reservation at the selected restaurant, that information is transmitted to the service provider, and the revenue-sharing system is activated.

[0419] This invention enables users to quickly find appropriate services from a vast amount of information and to conduct transactions efficiently.

[0420] The following describes the processing flow.

[0421] Step 1:

[0422] The user activates the information processing terminal and inputs the desired service in natural language. The terminal receives the input text data and combines it with the user's location information and past usage history to create a data packet.

[0423] Step 2:

[0424] The terminal sends the created data packet to the server. During this process, the data is securely encrypted according to the communication protocol.

[0425] Step 3:

[0426] The server decodes the received data packets and analyzes the input text data using natural language processing techniques. This allows it to identify the service the user desires.

[0427] Step 4:

[0428] Based on the analysis results, the server searches the database for information on relevant services. A generative model is used to select the appropriate service, taking into account factors such as past user preferences, review ratings, distance, and price.

[0429] Step 5:

[0430] The server creates a list of selected service information and sends it to the terminal in a visually easy-to-understand format.

[0431] Step 6:

[0432] The terminal displays a list of received services to the user. The user reviews this list and selects the desired service from the presented options.

[0433] Step 7:

[0434] Once the user confirms their selection, the device sends the service purchase information to the server.

[0435] Step 8:

[0436] The server receives the purchase information and notifies the selected service provider of the transaction. Furthermore, it initiates a profit-sharing process within the system and distributes the revenue according to the set percentage.

[0437] (Example 1)

[0438] 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."

[0439] In modern society, it is difficult for users to quickly and accurately select the services they desire from a vast amount of information. Furthermore, there is a need to effectively utilize location information and past behavioral history when finding the optimal service that matches the user's needs. In addition, it is necessary to streamline the purchase process of the selected service and ensure fair profit sharing between the user and the service provider.

[0440] 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.

[0441] In this invention, the server includes means for receiving and analyzing input data, location information, and usage history transmitted from the information processing terminal; means including generation technology for obtaining relevant options from a data storage device based on the analysis results and selecting an optimized option based on evaluation, distance, and price; and profit sharing means for receiving specific selections and service purchase information by the user and sharing profits with the provider. This enables the provision of optimal services that meet the user's wishes, as well as the streamlining of the purchase process and smooth profit sharing with businesses.

[0442] An "information processing terminal" is a device that allows users to input information in natural language and send the desired content or data to a server.

[0443] A "central processing unit" is a computer system that receives data transmitted from information processing terminals and analyzes its contents.

[0444] "Generative technology" refers to a wide range of techniques used to derive the optimal choice based on the results of data analysis.

[0445] A "data storage device" is a storage medium that stores services and related information and accesses them as needed.

[0446] A "profit-sharing mechanism" is a system for appropriately distributing profits between service providers and users based on service purchase information from users.

[0447] "Natural language processing techniques" are technologies that enable computers to understand, analyze, and process content expressed by users in natural language.

[0448] This invention describes a specific embodiment of a system that allows users to efficiently select and purchase services.

[0449] The user inputs their desired service into an information processing terminal using natural language. The terminal transmits the input text data, location information, and past usage history to a server. This provides the basic data needed to realize the user's wishes. The terminal used is expected to be a smartphone or personal computer.

[0450] The server uses a generative AI model to analyze the received data. This model applies natural language processing techniques to analyze user requests and extract relevant keywords. The software used includes natural language processing libraries and cloud-based AI services. Using the results of this analysis, the server retrieves service information from data storage and narrows down the options to those with high ratings and that meet the distance and price criteria.

[0451] The selected service information is transmitted to the information processing terminal in a visually easy-to-understand format. The terminal presents this information to the user, supporting them in making the optimal choice. Once the user completes the purchase of the specified service, the information necessary for profit sharing is returned to the server, ensuring that profits are distributed reliably with the relevant businesses.

[0452] As a concrete example, consider a case where a user inputs, "I want to go to a highly-rated Italian restaurant in Tokyo." This input is sent to the server, which then considers location information, ratings, price, etc., to list suitable Italian restaurants.

[0453] An example of a prompt message might be, "The user is looking for a highly-rated Italian restaurant in Tokyo. Please suggest available services." This system allows users to quickly and efficiently select and use the desired service from a vast amount of information.

[0454] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0455] Step 1:

[0456] The user inputs their desired service into an information processing terminal using natural language. The input is stored as text data on the terminal. At the same time, the user's location information is obtained using the terminal's location information system, and past usage history is retrieved from the terminal's storage. This data is prepared as basic information necessary for service selection.

[0457] Step 2:

[0458] The device sends text data, location information, and usage history to the server. The transmitted data is received by the server and stored in preparation for the next analysis step. This gives the server a foundation to comprehensively understand the user's requests and their background information.

[0459] Step 3:

[0460] The server inputs the received text data into a generating AI model. This model uses natural language processing techniques to analyze the meaning of the input natural language and extract relevant keywords. For example, it identifies keywords such as "Tokyo," "Italian food," and "highly rated," and passes that data to the next processing step.

[0461] Step 4:

[0462] The server searches a data storage device based on the extracted keywords. This data storage device contains a lot of service information. The server filters the options to find the one that best matches the user's requirements in terms of rating, distance, and price. In this process, a database search algorithm is used to quickly retrieve results that match the user's criteria.

[0463] Step 5:

[0464] The server sends filtered options to the terminal. The terminal receives these options and prepares to present them to the user in a visually easy-to-understand format. The user can then browse and compare the options presented in a list format to select the best service.

[0465] Step 6:

[0466] The user makes a reservation or purchase for a service selected through their device. The purchase information obtained as a result of this operation is then sent back to the server, which receives the information.

[0467] Step 7:

[0468] The server distributes revenue appropriately between the service provider and the user based on the received purchase information. This profit-sharing process is handled by an automated calculation program, including the transfer of funds to the service provider. This ensures a smooth service experience for users and strengthens cooperation between service providers and server operators.

[0469] (Application Example 1)

[0470] 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."

[0471] In today's information-saturated world, it's not easy for users to quickly and accurately find the services and products they desire. This is especially true when using physical stores; choosing the best store from a vast array of options is difficult, and smooth reservations and purchases are essential. A system is needed to address these challenges.

[0472] 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.

[0473] In this invention, the server includes means for receiving user requests in natural language, means for selecting the most suitable candidates considering location information and past history, and means for visually displaying relevant candidates. This enables users to efficiently find their desired services or stores and complete transactions smoothly.

[0474] An "information processing device" is a terminal that allows users to input their desired information in natural language.

[0475] A "central processing unit" is a processing unit that receives input data transmitted from information processing units and performs analysis on it.

[0476] A "generative model" is a component that has the function of retrieving relevant service information from a database based on the analysis results and selecting the optimal option.

[0477] "Visual presentation" refers to a method of presenting information in a format that is easy for users to understand.

[0478] A "profit-sharing mechanism" is a system that allows users to share profits with businesses based on the transactions they have conducted.

[0479] "Natural language processing technology" is a technology used to understand and analyze user input.

[0480] "Location information" refers to data about the user's current location.

[0481] "History" refers to past usage records.

[0482] This invention is an information processing system for efficiently finding the services and products that users desire. To implement this system, an information processing device is provided, which allows users to input their desired information in natural language. This information processing device may include common computing devices such as smartphones and tablets.

[0483] The input data is transmitted to the central processing unit (CCU) via the internet. The CCU is a server that uses natural language processing techniques to analyze the input. Specifically, existing natural language processing libraries such as "Google Cloud Natural Language" and "Microsoft Text Analytics" are available. The CCU analyzes the input and identifies relevant keywords and phrases.

[0484] The analyzed data is used to retrieve relevant service information from the database using a generative model. A generative model is a computational model that suggests the optimal option based on the analysis results. The selected information is returned to the information processing device in a visually easy-to-understand format. Users can then select the most suitable service based on this information.

[0485] The system has the ability to provide optimal suggestions by considering the user's location information and past usage history. Location information is obtained using the smartphone's GPS function. Past history is recorded in a database linked to the user account and can be individually customized.

[0486] As a concrete example, consider a scenario where a user inputs "I want to eat delicious pasta this weekend" into an information processing device. The server analyzes this input and visually displays a list of the most suitable Italian restaurants. Based on the displayed information, the user can select a restaurant and make a reservation. Furthermore, once the transaction is complete, profit sharing is automatically handled between the user and the restaurant.

[0487] An example of a prompt statement is as follows:

[0488] "Based on the user's input: 'I want to eat delicious pasta this weekend,' please list the top 5 Italian restaurants using the user's current location and past history."

[0489] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0490] Step 1:

[0491] The terminal receives the user's request, entered in natural language. This request may include, for example, "I want to eat delicious pasta on the weekend." At this point, the input data is the user's text instruction. The terminal prepares to send this input to the server.

[0492] Step 2:

[0493] The server receives input data sent from the terminal. Based on the received data, it performs natural language processing to analyze the user's preferences. For example, it extracts keywords such as "pasta" and "weekend." Technologies such as Google Cloud Natural Language are used for this data processing. As a result of the analysis, relevant keywords are output.

[0494] Step 3:

[0495] The server uses a generative AI model to perform service information retrieval based on the analysis results. The server queries the database using keywords as arguments to obtain the most relevant store information. At this point, the input is a list of keywords based on the analysis results, and the output is a list of relevant store information. The database contains store locations, ratings, price ranges, availability, etc.

[0496] Step 4:

[0497] The server formats the acquired store information for visual display on the terminal. Here, the information is visually organized in map or list format so that users can easily compare it. The terminal receives the assembled display data and displays the results on the user's screen.

[0498] Step 5:

[0499] The terminal accepts the user's selection. The user selects a service of interest from the presented options and performs a reservation or purchase operation. This operation is sent from the terminal to the server, where processing continues. The input is the user's selection information, and the output is the reservation / purchase information for the selected service.

[0500] Step 6:

[0501] The server receives and processes the selected reservation or purchase information. This processing includes reservation confirmation and purchase procedures with the selected service provider. The system automatically calculates profit sharing and notifies relevant parties as needed. Finally, the user receives feedback on the transaction completion status and confirmation information.

[0502] 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.

[0503] This invention relates to an information processing system that allows users to efficiently select the services they desire, and more particularly to a system that incorporates an emotion engine that recognizes user emotions and optimizes suggested services. Specific embodiments of the invention will be described below.

[0504] This system consists of an information processing terminal, a central processing unit (server), a generative model, and an emotion engine. Users use the information processing terminal to input their desired services in natural language. The terminal transmits the input information to the server, simultaneously sending the user's location information and past usage history.

[0505] The server analyzes the received data and uses generative models and natural language processing techniques to pinpoint the specific services the user desires. The emotion engine then analyzes the user's emotional state from the input language data. This analysis determines how the user is feeling and optimizes the services suggested by the generative model.

[0506] Relevant service information retrieved from the database is presented to the user as the best option, taking into account the user's current emotional state and past emotional history. This allows the user to select a service that resonates with their emotions.

[0507] For example, if a user enters "I'm tired and want to find a spa where I can relax," the server analyzes this information to select spa facilities, and the emotion engine detects "fatigue." Based on this, it emphasizes and suggests services that are particularly relaxing. The user reviews the suggested list on their device, selects a suitable facility, and makes a reservation. Once the selection is complete, the server initiates the profit-sharing process, ensuring a smooth transaction.

[0508] In this way, the present invention provides optimal services that meet the psychological needs of users, improves user satisfaction, and enables efficient market transactions.

[0509] The following describes the processing flow.

[0510] Step 1:

[0511] The user activates the information processing terminal and inputs the desired service in natural language. The terminal creates a data packet that includes the input text data, as well as the user's location information and past usage history.

[0512] Step 2:

[0513] The terminal sends the created data packet to the server. At this time, the data is encrypted using a communication protocol.

[0514] Step 3:

[0515] The server analyzes the received data packets. Using natural language processing techniques, it analyzes the input text data to identify the service the user desires.

[0516] Step 4:

[0517] The server activates the emotion engine based on the analysis results. The emotion engine uses information extracted from the user's input to analyze the user's emotional state and determine what psychological state they are in.

[0518] Step 5:

[0519] The server considers the analysis results of the emotion engine and retrieves relevant service information from the database. A generative model is used to combine the best options to match the user's emotional state and adjust the suggestions accordingly.

[0520] Step 6:

[0521] The server lists the selected service information and sends it to the terminal in a visual format. The terminal receives this information and displays it in a way that is easy for the user to understand.

[0522] Step 7:

[0523] The user reviews the service options presented through the device and selects the one that best suits their needs. Once the user confirms their selection, the device sends the purchase information to the server.

[0524] Step 8:

[0525] The server receives purchase information and notifies the relevant service providers of the transaction. Simultaneously, it automatically initiates the profit-sharing process and distributes the revenue according to the established arrangements.

[0526] (Example 2)

[0527] 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."

[0528] The problem that this invention aims to solve is to improve the user experience by enabling service selection according to the user's emotions and realizing information provision optimized for their emotional state. Conventional systems provide information without considering the user's emotional state, which could lead to decreased user satisfaction.

[0529] 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.

[0530] In this invention, the server includes means for inputting information desired by the user in natural language, a central computer for receiving and analyzing the input information transmitted from the means, and means including a generation algorithm for analyzing the user's emotional state, retrieving relevant information from a data warehouse based on the analysis results, and selecting the optimal choice. This enables the provision of optimal choices based on the user's emotions, thereby improving the user experience.

[0531] "A means of inputting information desired by the user in natural language" refers to an input device or interface for users to input the information or service details they require in natural language format.

[0532] A "central computer" is an information processing device that receives input from users, analyzes it, and processes it.

[0533] The phrase "analyzing the user's emotional state" refers to a technology that has an analytical function to analyze the language data entered by the user and determine their emotions and psychological state.

[0534] "Means including a generation algorithm" refers to an apparatus or system that includes an algorithm or model for generating relevant information based on analysis results.

[0535] A "data warehouse" is a database system that centrally manages diverse data and enables high-speed searching and retrieval of necessary information.

[0536] This invention relates to an information processing system that enables users to efficiently select the services they desire, and more particularly to a system that recognizes user emotions and optimizes suggested services. The system's basic components consist of an information processing terminal, a central computer (server), a generation algorithm, and emotion analysis technology.

[0537] Users use an information processing terminal to input their desired service in natural language. An example input might be, "I want to find a place where I can relax." The terminal sends this input information to a server, which simultaneously provides the user's location information and past usage history.

[0538] The server uses natural language processing techniques to analyze the received data and a generative AI model to identify the services the user desires. During this analysis, an emotion engine is used to analyze the user's emotional state from the text they input. For example, it can detect fatigue from the input "tired."

[0539] The generation algorithm retrieves relevant service information from a data repository based on the user's context and emotions, providing the most appropriate service selection. For example, if a user enters "I want to find a yoga class," the server highlights and presents potential yoga classes that can help reduce stress to the user's information processing terminal. This process allows the user to make a choice that suits their emotional state.

[0540] An example of a prompt to input into the generating AI model is as follows: "Assuming the user intends to relax, please suggest the most suitable spa facility."

[0541] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0542] Step 1:

[0543] The user uses an information processing terminal to input their desired service details in natural language. This input is text data that expresses the user's requests and desires. For example, it might say, "I want to find a relaxing cafe." The entered data is temporarily stored on the terminal.

[0544] Step 2:

[0545] The terminal sends input text data to the server. During this process, sub-data, including the user's location information and past usage history, is sent to the server as packets along with the input natural language data. This information serves as initial data necessary for service selection.

[0546] Step 3:

[0547] The server analyzes the received text data and subdata. Natural language processing techniques are used here, leveraging generative AI models to gain a detailed understanding of the user's requests. This analysis clarifies the services the user desires and their content. The output at this point is the identified service request.

[0548] Step 4:

[0549] The server uses sentiment analysis technology to analyze the user's emotional state from their input text. The sentiment engine processes the text and identifies emotions such as "fatigue" and "stress." This analysis is used in the optimization process for selecting service candidates. The output here is data about the user's emotional state.

[0550] Step 5:

[0551] The server uses a generation algorithm to retrieve relevant service information from the data repository. The retrieved data is filtered based on the user's emotional state, location, and past usage history, and ranked to determine the most appropriate and useful service options. The output of this process is an optimized list of service candidates.

[0552] Step 6:

[0553] The terminal presents the user with an optimized list of service candidates sent from the server. The user can review the presented information and make a selection that suits their needs. The input in this step is the list of service candidates from the server, and the output is the user's final selection.

[0554] (Application Example 2)

[0555] 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."

[0556] In modern information processing systems, there is a lack of appropriate suggestions that take into account the psychological state and emotions of users when they select the services they desire. Furthermore, while there is a desire for appropriate environmental adjustments based on emotions within the home, there is a problem in the lack of sufficient efficient mechanisms to achieve this.

[0557] 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.

[0558] In this invention, the server includes means for analyzing data transmitted from an information processing device, means for acquiring relevant service information from a storage unit using a generative model and selecting the optimal option, and means for determining the user's emotional state using an emotion engine and adjusting the environment accordingly. This enables the provision of optimal services and environments based on the user's emotions, thereby improving the user experience.

[0559] An "information processing device" is a device that allows users to input desired information using natural language.

[0560] A "central control unit" is a device that receives and analyzes data transmitted from an information processing unit.

[0561] A "generative model" includes an algorithm that acquires service information based on analysis results and selects the optimal option.

[0562] The term "storage unit" refers to the database where information about related services is stored.

[0563] An "emotion engine" is a technology that identifies and analyzes emotional states from user input data.

[0564] "Means for optimally adjusting the environment" refers to functions that allow users to manipulate environmental settings such as lighting, music, and scent according to their emotional state.

[0565] A "vendor" refers to a business that provides services and is the entity that shares profits based on purchase information from users.

[0566] The server receives natural language input data from the user via an information processing terminal, and this data is analyzed by a central control unit. Using the results of the analysis, the generative model retrieves relevant service information from the storage unit and selects the optimal option. Natural language processing technology is used in this process, making it possible to accurately identify what the user desires.

[0567] Furthermore, the emotion engine analyzes the user's emotional state and issues instructions to the environment control system to provide the optimal environment based on the user's emotions. Specifically, various smart devices respond to this, dynamically adjusting settings such as lighting, music, and scent. For example, if the user says, "I want to relax," the emotion engine analyzes that intention and issues instructions to change the lighting to a warm color while simultaneously playing relaxing music.

[0568] The terminal displays optimal options and adjusted settings sent from the server to the user, who can then enjoy the service by confirming them. Furthermore, once the user ultimately purchases or selects a service, the server receives that information and processes the transaction to arrange profit sharing with the service provider. This entire process allows users to seamlessly receive emotionally resonant services.

[0569] An example of a prompt statement using a generative AI model might be an instruction such as, "Write a program that suggests interior design that will help the user relax." This prompt statement is an important element in conveying the user's intent to the system.

[0570] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0571] Step 1:

[0572] The user inputs their desired information into the information processing terminal using natural language. The input data is then sent directly to the server. In this process, input is either the user's spoken words or text input, and output is the user's request data sent to the server.

[0573] Step 2:

[0574] The server analyzes the data received by the central control unit. Natural language processing techniques are used for the analysis to clarify the user's intent. Through this process, the services and conditions requested by the user are identified from the input data, and the analysis results are sent as output to the generative model.

[0575] Step 3:

[0576] The generative model retrieves service information from the storage unit based on the analysis results. It selects the optimal option by considering data from related services, past usage history, and location information. The inputs here are the analysis results and data from the storage unit, and the output is optimized service information to be presented to the user.

[0577] Step 4:

[0578] The emotion engine analyzes the user's emotional state based on their input data. The analyzed emotions form the basis for environmental adjustments, and the user's emotional state is sent to the environmental control system as output.

[0579] Step 5:

[0580] The environmental control system adjusts the environment via smart devices based on the results of the emotion engine. Specific actions include adjusting the color temperature of the lighting, selecting music, and activating an aroma diffuser. The input is the result of the emotion engine, and the output is the adjusted environmental settings.

[0581] Step 6:

[0582] The server sends the final selection and configuration information to the terminal and displays it to the user. This allows the user to review the suggested services and optimized environment. Optimization information is used as input, and the output is the information displayed on the user's device.

[0583] Step 7:

[0584] The user confirms the selected service on their device and ultimately purchases or selects the service. This information is sent to the server, which provides the user's selection information as input and generates instructions for profit distribution to the service provider as output.

[0585] 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.

[0586] 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.

[0587] 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.

[0588] [Fourth Embodiment]

[0589] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0590] 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.

[0591] 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).

[0592] 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.

[0593] 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.

[0594] 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).

[0595] 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.

[0596] 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.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] 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.

[0601] 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".

[0602] This invention relates to an information processing system for enabling users to quickly and appropriately select services. Specific embodiments of the invention are described below.

[0603] This system's basic components are an information processing terminal where users input their desired actions and services in natural language, and a central processing unit (server) that processes the input data and selects services that meet the user's needs. When a user searches for services using the information processing terminal, location information and past usage history are transmitted from the terminal to the server during the input stage.

[0604] The server analyzes the received data based on a generative model and identifies relevant keywords. This lays the foundation for concretizing user preferences and proposing the most suitable services. Based on the keywords obtained as a result of the analysis, the server retrieves highly relevant services from the database and narrows down the options.

[0605] The selected service information is transmitted from the server to the information processing terminal and presented to the user by the terminal. The information is displayed in a visually easy-to-understand format, allowing the user to easily compare options. Once the user selects a specific service and decides to purchase it, the purchase information is sent to the server, completing the transaction.

[0606] Furthermore, this system incorporates a profit-sharing mechanism between the user and the service provider. Once a user's purchase of a service is confirmed, the system is designed to automatically share revenue with the service provider. As a result, users can smoothly enjoy the desired services, and service providers and operators can cooperate to conduct business efficiently.

[0607] For example, if a user enters "I want to go to a highly-rated Italian restaurant in Tokyo" into an information processing terminal, that request is sent to the server. Based on the location information, the server extracts Italian restaurants near the user's current location from its database and presents the best option based on rating, distance, and price. When the user makes a reservation at the selected restaurant, that information is transmitted to the service provider, and the revenue-sharing system is activated.

[0608] This invention enables users to quickly find appropriate services from a vast amount of information and to conduct transactions efficiently.

[0609] The following describes the processing flow.

[0610] Step 1:

[0611] The user activates the information processing terminal and inputs the desired service in natural language. The terminal receives the input text data and combines it with the user's location information and past usage history to create a data packet.

[0612] Step 2:

[0613] The terminal sends the created data packet to the server. During this process, the data is securely encrypted according to the communication protocol.

[0614] Step 3:

[0615] The server decodes the received data packets and analyzes the input text data using natural language processing techniques. This allows it to identify the service the user desires.

[0616] Step 4:

[0617] Based on the analysis results, the server searches the database for information on relevant services. A generative model is used to select the appropriate service, taking into account factors such as past user preferences, review ratings, distance, and price.

[0618] Step 5:

[0619] The server creates a list of selected service information and sends it to the terminal in a visually easy-to-understand format.

[0620] Step 6:

[0621] The terminal displays a list of received services to the user. The user reviews this list and selects the desired service from the presented options.

[0622] Step 7:

[0623] Once the user confirms their selection, the device sends the service purchase information to the server.

[0624] Step 8:

[0625] The server receives the purchase information and notifies the selected service provider of the transaction. Furthermore, it initiates a profit-sharing process within the system and distributes the revenue according to the set percentage.

[0626] (Example 1)

[0627] 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".

[0628] In modern society, it is difficult for users to quickly and accurately select the services they desire from a vast amount of information. Furthermore, there is a need to effectively utilize location information and past behavioral history when finding the optimal service that matches the user's needs. In addition, it is necessary to streamline the purchase process of the selected service and ensure fair profit sharing between the user and the service provider.

[0629] 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.

[0630] In this invention, the server includes means for receiving and analyzing input data, location information, and usage history transmitted from the information processing terminal; means including generation technology for obtaining relevant options from a data storage device based on the analysis results and selecting an optimized option based on evaluation, distance, and price; and profit sharing means for receiving specific selections and service purchase information by the user and sharing profits with the provider. This enables the provision of optimal services that meet the user's wishes, as well as the streamlining of the purchase process and smooth profit sharing with businesses.

[0631] An "information processing terminal" is a device that allows users to input information in natural language and send the desired content or data to a server.

[0632] A "central processing unit" is a computer system that receives data transmitted from information processing terminals and analyzes its contents.

[0633] "Generative technology" refers to a wide range of techniques used to derive the optimal choice based on the results of data analysis.

[0634] A "data storage device" is a storage medium that stores services and related information and accesses them as needed.

[0635] A "profit-sharing mechanism" is a system for appropriately distributing profits between service providers and users based on service purchase information from users.

[0636] "Natural language processing techniques" are technologies that enable computers to understand, analyze, and process content expressed by users in natural language.

[0637] This invention describes a specific embodiment of a system that allows users to efficiently select and purchase services.

[0638] The user inputs their desired service into an information processing terminal using natural language. The terminal transmits the input text data, location information, and past usage history to a server. This provides the basic data needed to realize the user's wishes. The terminal used is expected to be a smartphone or personal computer.

[0639] The server uses a generative AI model to analyze the received data. This model applies natural language processing techniques to analyze user requests and extract relevant keywords. The software used includes natural language processing libraries and cloud-based AI services. Using the results of this analysis, the server retrieves service information from data storage and narrows down the options to those with high ratings and that meet the distance and price criteria.

[0640] The selected service information is transmitted to the information processing terminal in a visually easy-to-understand format. The terminal presents this information to the user, supporting them in making the optimal choice. Once the user completes the purchase of the specified service, the information necessary for profit sharing is returned to the server, ensuring that profits are distributed reliably with the relevant businesses.

[0641] As a concrete example, consider a case where a user inputs, "I want to go to a highly-rated Italian restaurant in Tokyo." This input is sent to the server, which then considers location information, ratings, price, etc., to list suitable Italian restaurants.

[0642] An example of a prompt message might be, "The user is looking for a highly-rated Italian restaurant in Tokyo. Please suggest available services." This system allows users to quickly and efficiently select and use the desired service from a vast amount of information.

[0643] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0644] Step 1:

[0645] The user inputs their desired service into an information processing terminal using natural language. The input is stored as text data on the terminal. At the same time, the user's location information is obtained using the terminal's location information system, and past usage history is retrieved from the terminal's storage. This data is prepared as basic information necessary for service selection.

[0646] Step 2:

[0647] The device sends text data, location information, and usage history to the server. The transmitted data is received by the server and stored in preparation for the next analysis step. This gives the server a foundation to comprehensively understand the user's requests and their background information.

[0648] Step 3:

[0649] The server inputs the received text data into a generating AI model. This model uses natural language processing techniques to analyze the meaning of the input natural language and extract relevant keywords. For example, it identifies keywords such as "Tokyo," "Italian food," and "highly rated," and passes that data to the next processing step.

[0650] Step 4:

[0651] The server searches a data storage device based on the extracted keywords. This data storage device contains a lot of service information. The server filters the options to find the one that best matches the user's requirements in terms of rating, distance, and price. In this process, a database search algorithm is used to quickly retrieve results that match the user's criteria.

[0652] Step 5:

[0653] The server sends filtered options to the terminal. The terminal receives these options and prepares to present them to the user in a visually easy-to-understand format. The user can then browse and compare the options presented in a list format to select the best service.

[0654] Step 6:

[0655] The user makes a reservation or purchase for a service selected through their device. The purchase information obtained as a result of this operation is then sent back to the server, which receives the information.

[0656] Step 7:

[0657] The server distributes revenue appropriately between the service provider and the user based on the received purchase information. This profit-sharing process is handled by an automated calculation program, including the transfer of funds to the service provider. This ensures a smooth service experience for users and strengthens cooperation between service providers and server operators.

[0658] (Application Example 1)

[0659] 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".

[0660] In today's information-saturated world, it's not easy for users to quickly and accurately find the services and products they desire. This is especially true when using physical stores; choosing the best store from a vast array of options is difficult, and smooth reservations and purchases are essential. A system is needed to address these challenges.

[0661] 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.

[0662] In this invention, the server includes means for receiving user requests in natural language, means for selecting the most suitable candidates considering location information and past history, and means for visually displaying relevant candidates. This enables users to efficiently find their desired services or stores and complete transactions smoothly.

[0663] An "information processing device" is a terminal that allows users to input their desired information in natural language.

[0664] A "central processing unit" is a processing unit that receives input data transmitted from information processing units and performs analysis on it.

[0665] A "generative model" is a component that has the function of retrieving relevant service information from a database based on the analysis results and selecting the optimal option.

[0666] "Visual presentation" refers to a method of presenting information in a format that is easy for users to understand.

[0667] A "profit-sharing mechanism" is a system that allows users to share profits with businesses based on the transactions they have conducted.

[0668] "Natural language processing technology" is a technology used to understand and analyze user input.

[0669] "Location information" refers to data about the user's current location.

[0670] "History" refers to past usage records.

[0671] This invention is an information processing system for efficiently finding the services and products that users desire. To implement this system, an information processing device is provided, which allows users to input their desired information in natural language. This information processing device may include common computing devices such as smartphones and tablets.

[0672] The input data is transmitted to the central processing unit (CCU) via the internet. The CCU is a server that uses natural language processing techniques to analyze the input. Specifically, existing natural language processing libraries such as "Google Cloud Natural Language" and "Microsoft Text Analytics" are available. The CCU analyzes the input and identifies relevant keywords and phrases.

[0673] The analyzed data is used to retrieve relevant service information from the database using a generative model. A generative model is a computational model that suggests the optimal option based on the analysis results. The selected information is returned to the information processing device in a visually easy-to-understand format. Users can then select the most suitable service based on this information.

[0674] The system has the ability to provide optimal suggestions by considering the user's location information and past usage history. Location information is obtained using the smartphone's GPS function. Past history is recorded in a database linked to the user account and can be individually customized.

[0675] As a concrete example, consider a scenario where a user inputs "I want to eat delicious pasta this weekend" into an information processing device. The server analyzes this input and visually displays a list of the most suitable Italian restaurants. Based on the displayed information, the user can select a restaurant and make a reservation. Furthermore, once the transaction is complete, profit sharing is automatically handled between the user and the restaurant.

[0676] An example of a prompt statement is as follows:

[0677] "Based on the user's input: 'I want to eat delicious pasta this weekend,' please list the top 5 Italian restaurants using the user's current location and past history."

[0678] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0679] Step 1:

[0680] The terminal receives the user's request, entered in natural language. This request may include, for example, "I want to eat delicious pasta on the weekend." At this point, the input data is the user's text instruction. The terminal prepares to send this input to the server.

[0681] Step 2:

[0682] The server receives input data sent from the terminal. Based on the received data, it performs natural language processing to analyze the user's preferences. For example, it extracts keywords such as "pasta" and "weekend." Technologies such as Google Cloud Natural Language are used for this data processing. As a result of the analysis, relevant keywords are output.

[0683] Step 3:

[0684] The server uses a generative AI model to perform service information retrieval based on the analysis results. The server queries the database using keywords as arguments to obtain the most relevant store information. At this point, the input is a list of keywords based on the analysis results, and the output is a list of relevant store information. The database contains store locations, ratings, price ranges, availability, etc.

[0685] Step 4:

[0686] The server formats the acquired store information for visual display on the terminal. Here, the information is visually organized in map or list format so that users can easily compare it. The terminal receives the assembled display data and displays the results on the user's screen.

[0687] Step 5:

[0688] The terminal accepts the user's selection. The user selects a service of interest from the presented options and performs a reservation or purchase operation. This operation is sent from the terminal to the server, where processing continues. The input is the user's selection information, and the output is the reservation / purchase information for the selected service.

[0689] Step 6:

[0690] The server receives and processes the selected reservation or purchase information. This processing includes reservation confirmation and purchase procedures with the selected service provider. The system automatically calculates profit sharing and notifies relevant parties as needed. Finally, the user receives feedback on the transaction completion status and confirmation information.

[0691] 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.

[0692] This invention relates to an information processing system that allows users to efficiently select the services they desire, and more particularly to a system that incorporates an emotion engine that recognizes user emotions and optimizes suggested services. Specific embodiments of the invention will be described below.

[0693] This system consists of an information processing terminal, a central processing unit (server), a generative model, and an emotion engine. Users use the information processing terminal to input their desired services in natural language. The terminal transmits the input information to the server, simultaneously sending the user's location information and past usage history.

[0694] The server analyzes the received data and uses generative models and natural language processing techniques to pinpoint the specific services the user desires. The emotion engine then analyzes the user's emotional state from the input language data. This analysis determines how the user is feeling and optimizes the services suggested by the generative model.

[0695] Relevant service information retrieved from the database is presented to the user as the best option, taking into account the user's current emotional state and past emotional history. This allows the user to select a service that resonates with their emotions.

[0696] For example, if a user enters "I'm tired and want to find a spa where I can relax," the server analyzes this information to select spa facilities, and the emotion engine detects "fatigue." Based on this, it emphasizes and suggests services that are particularly relaxing. The user reviews the suggested list on their device, selects a suitable facility, and makes a reservation. Once the selection is complete, the server initiates the profit-sharing process, ensuring a smooth transaction.

[0697] In this way, the present invention provides optimal services that meet the psychological needs of users, improves user satisfaction, and enables efficient market transactions.

[0698] The following describes the processing flow.

[0699] Step 1:

[0700] The user activates the information processing terminal and inputs the desired service in natural language. The terminal creates a data packet that includes the input text data, as well as the user's location information and past usage history.

[0701] Step 2:

[0702] The terminal sends the created data packet to the server. At this time, the data is encrypted using a communication protocol.

[0703] Step 3:

[0704] The server analyzes the received data packets. Using natural language processing techniques, it analyzes the input text data to identify the service the user desires.

[0705] Step 4:

[0706] The server activates the emotion engine based on the analysis results. The emotion engine uses information extracted from the user's input to analyze the user's emotional state and determine what psychological state they are in.

[0707] Step 5:

[0708] The server considers the analysis results of the emotion engine and retrieves relevant service information from the database. A generative model is used to combine the best options to match the user's emotional state and adjust the suggestions accordingly.

[0709] Step 6:

[0710] The server lists the selected service information and sends it to the terminal in a visual format. The terminal receives this information and displays it in a way that is easy for the user to understand.

[0711] Step 7:

[0712] The user reviews the service options presented through the device and selects the one that best suits their needs. Once the user confirms their selection, the device sends the purchase information to the server.

[0713] Step 8:

[0714] The server receives purchase information and notifies the relevant service providers of the transaction. Simultaneously, it automatically initiates the profit-sharing process and distributes the revenue according to the established arrangements.

[0715] (Example 2)

[0716] 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".

[0717] The problem that this invention aims to solve is to improve the user experience by enabling service selection according to the user's emotions and realizing information provision optimized for their emotional state. Conventional systems provide information without considering the user's emotional state, which could lead to decreased user satisfaction.

[0718] 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.

[0719] In this invention, the server includes means for inputting information desired by the user in natural language, a central computer for receiving and analyzing the input information transmitted from the means, and means including a generation algorithm for analyzing the user's emotional state, retrieving relevant information from a data warehouse based on the analysis results, and selecting the optimal choice. This enables the provision of optimal choices based on the user's emotions, thereby improving the user experience.

[0720] "A means of inputting information desired by the user in natural language" refers to an input device or interface for users to input the information or service details they require in natural language format.

[0721] A "central computer" is an information processing device that receives input from users, analyzes it, and processes it.

[0722] The phrase "analyzing the user's emotional state" refers to a technology that has an analytical function to analyze the language data entered by the user and determine their emotions and psychological state.

[0723] "Means including a generation algorithm" refers to an apparatus or system that includes an algorithm or model for generating relevant information based on analysis results.

[0724] A "data warehouse" is a database system that centrally manages diverse data and enables high-speed searching and retrieval of necessary information.

[0725] This invention relates to an information processing system that enables users to efficiently select the services they desire, and more particularly to a system that recognizes user emotions and optimizes suggested services. The system's basic components consist of an information processing terminal, a central computer (server), a generation algorithm, and emotion analysis technology.

[0726] Users use an information processing terminal to input their desired service in natural language. An example input might be, "I want to find a place where I can relax." The terminal sends this input information to a server, which simultaneously provides the user's location information and past usage history.

[0727] The server uses natural language processing techniques to analyze the received data and a generative AI model to identify the services the user desires. During this analysis, an emotion engine is used to analyze the user's emotional state from the text they input. For example, it can detect fatigue from the input "tired."

[0728] The generation algorithm retrieves relevant service information from a data repository based on the user's context and emotions, providing the most appropriate service selection. For example, if a user enters "I want to find a yoga class," the server highlights and presents potential yoga classes that can help reduce stress to the user's information processing terminal. This process allows the user to make a choice that suits their emotional state.

[0729] An example of a prompt to input into the generating AI model is as follows: "Assuming the user intends to relax, please suggest the most suitable spa facility."

[0730] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0731] Step 1:

[0732] The user uses an information processing terminal to input their desired service details in natural language. This input is text data that expresses the user's requests and desires. For example, it might say, "I want to find a relaxing cafe." The entered data is temporarily stored on the terminal.

[0733] Step 2:

[0734] The terminal sends input text data to the server. During this process, sub-data, including the user's location information and past usage history, is sent to the server as packets along with the input natural language data. This information serves as initial data necessary for service selection.

[0735] Step 3:

[0736] The server analyzes the received text data and subdata. Natural language processing techniques are used here, leveraging generative AI models to gain a detailed understanding of the user's requests. This analysis clarifies the services the user desires and their content. The output at this point is the identified service request.

[0737] Step 4:

[0738] The server uses sentiment analysis technology to analyze the user's emotional state from their input text. The sentiment engine processes the text and identifies emotions such as "fatigue" and "stress." This analysis is used in the optimization process for selecting service candidates. The output here is data about the user's emotional state.

[0739] Step 5:

[0740] The server uses a generation algorithm to retrieve relevant service information from the data repository. The retrieved data is filtered based on the user's emotional state, location, and past usage history, and ranked to determine the most appropriate and useful service options. The output of this process is an optimized list of service candidates.

[0741] Step 6:

[0742] The terminal presents the user with an optimized list of service candidates sent from the server. The user can review the presented information and make a selection that suits their needs. The input in this step is the list of service candidates from the server, and the output is the user's final selection.

[0743] (Application Example 2)

[0744] 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".

[0745] In modern information processing systems, there is a lack of appropriate suggestions that take into account the psychological state and emotions of users when they select the services they desire. Furthermore, while there is a desire for appropriate environmental adjustments based on emotions within the home, there is a problem in the lack of sufficient efficient mechanisms to achieve this.

[0746] 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.

[0747] In this invention, the server includes means for analyzing data transmitted from an information processing device, means for acquiring relevant service information from a storage unit using a generative model and selecting the optimal option, and means for determining the user's emotional state using an emotion engine and adjusting the environment accordingly. This enables the provision of optimal services and environments based on the user's emotions, thereby improving the user experience.

[0748] An "information processing device" is a device that allows users to input desired information using natural language.

[0749] A "central control unit" is a device that receives and analyzes data transmitted from an information processing unit.

[0750] A "generative model" includes an algorithm that acquires service information based on analysis results and selects the optimal option.

[0751] The term "storage unit" refers to the database where information about related services is stored.

[0752] An "emotion engine" is a technology that identifies and analyzes emotional states from user input data.

[0753] "Means for optimally adjusting the environment" refers to functions that allow users to manipulate environmental settings such as lighting, music, and scent according to their emotional state.

[0754] A "vendor" refers to a business that provides services and is the entity that shares profits based on purchase information from users.

[0755] The server receives natural language input data from the user via an information processing terminal, and this data is analyzed by a central control unit. Using the results of the analysis, the generative model retrieves relevant service information from the storage unit and selects the optimal option. Natural language processing technology is used in this process, making it possible to accurately identify what the user desires.

[0756] Furthermore, the emotion engine analyzes the user's emotional state and issues instructions to the environment control system to provide the optimal environment based on the user's emotions. Specifically, various smart devices respond to this, dynamically adjusting settings such as lighting, music, and scent. For example, if the user says, "I want to relax," the emotion engine analyzes that intention and issues instructions to change the lighting to a warm color while simultaneously playing relaxing music.

[0757] The terminal displays optimal options and adjusted settings sent from the server to the user, who can then enjoy the service by confirming them. Furthermore, once the user ultimately purchases or selects a service, the server receives that information and processes the transaction to arrange profit sharing with the service provider. This entire process allows users to seamlessly receive emotionally resonant services.

[0758] An example of a prompt statement using a generative AI model might be an instruction such as, "Write a program that suggests interior design that will help the user relax." This prompt statement is an important element in conveying the user's intent to the system.

[0759] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0760] Step 1:

[0761] The user inputs their desired information into the information processing terminal using natural language. The input data is then sent directly to the server. In this process, input is either the user's spoken words or text input, and output is the user's request data sent to the server.

[0762] Step 2:

[0763] The server analyzes the data received by the central control unit. Natural language processing techniques are used for the analysis to clarify the user's intent. Through this process, the services and conditions requested by the user are identified from the input data, and the analysis results are sent as output to the generative model.

[0764] Step 3:

[0765] The generative model retrieves service information from the storage unit based on the analysis results. It selects the optimal option by considering data from related services, past usage history, and location information. The inputs here are the analysis results and data from the storage unit, and the output is optimized service information to be presented to the user.

[0766] Step 4:

[0767] The emotion engine analyzes the user's emotional state based on their input data. The analyzed emotions form the basis for environmental adjustments, and the user's emotional state is sent to the environmental control system as output.

[0768] Step 5:

[0769] The environmental control system adjusts the environment via smart devices based on the results of the emotion engine. Specific actions include adjusting the color temperature of the lighting, selecting music, and activating an aroma diffuser. The input is the result of the emotion engine, and the output is the adjusted environmental settings.

[0770] Step 6:

[0771] The server sends the final selection and configuration information to the terminal and displays it to the user. This allows the user to review the suggested services and optimized environment. Optimization information is used as input, and the output is the information displayed on the user's device.

[0772] Step 7:

[0773] The user confirms the selected service on their device and ultimately purchases or selects the service. This information is sent to the server, which provides the user's selection information as input and generates instructions for profit distribution to the service provider as output.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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."

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] The following is further disclosed regarding the embodiments described above.

[0796] (Claim 1)

[0797] A means for the user to input desired content in natural language on an information processing terminal,

[0798] A central processing unit that receives and analyzes input data transmitted from the aforementioned information processing terminal,

[0799] A means including a generative model that retrieves relevant service information from a database based on the aforementioned analysis results and selects the optimal option,

[0800] means for transmitting and displaying the aforementioned optimal choice to the information processing terminal,

[0801] A means of receiving user purchase information for services and sharing profits with the service provider,

[0802] A system that includes this.

[0803] (Claim 2)

[0804] The system according to claim 1, which selects the optimal option considering the user's location information and past usage history.

[0805] (Claim 3)

[0806] The system according to claim 1, wherein a generative model uses natural language processing technology to identify the content desired by the user.

[0807] "Example 1"

[0808] (Claim 1)

[0809] A means for the user to input desired content in natural language on an information processing terminal,

[0810] A central processing unit that receives and analyzes input data, location information, and usage history transmitted from the aforementioned information processing terminal,

[0811] Means including a generation technique for obtaining relevant options from a data storage device based on the analysis results and selecting an optimized option based on evaluation, distance, and price,

[0812] A means for transmitting the optimized options to the information processing terminal and displaying them in a visually easy-to-understand format,

[0813] A profit-sharing mechanism that receives specific user selections and service purchase information and distributes profits with the provider,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, which selects highly relevant options based on the user's location information and past usage history.

[0817] (Claim 3)

[0818] The system according to claim 1, wherein the generation technology uses natural language processing techniques to analyze and identify the content desired by the user.

[0819] "Application Example 1"

[0820] (Claim 1)

[0821] In an information processing device, a means for the user to input desired content in natural language,

[0822] A central processing unit that receives and analyzes input data transmitted from the aforementioned information processing device,

[0823] A means including a generative model that retrieves relevant service information from a database based on the aforementioned analysis results and selects the optimal option,

[0824] A means for transmitting the aforementioned optimal choice to the information processing device and displaying it visually,

[0825] A means of receiving transaction information from users and sharing profits with the business,

[0826] A means of presenting relevant candidates based on content entered by the user in natural language,

[0827] A system that includes this.

[0828] (Claim 2)

[0829] The system according to claim 1, which selects the optimal candidate by taking into account the user's location information and past history.

[0830] (Claim 3)

[0831] The system according to claim 1, wherein a generative model utilizes natural language processing technology to identify the content desired by the user.

[0832] "Example 2 of combining an emotion engine"

[0833] (Claim 1)

[0834] A means for users to input the information they want in natural language,

[0835] A central computer that receives and analyzes input information transmitted from the aforementioned means,

[0836] A means including a generation algorithm that analyzes the user's emotional state, retrieves relevant information from a data warehouse based on the analysis results, and selects the optimal option,

[0837] A means for transmitting and displaying the aforementioned optimal choice to the means,

[0838] A means of receiving user purchase information and sharing profits with business partners,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, which selects the optimal option considering the user's current location and past usage history.

[0842] (Claim 3)

[0843] The system according to claim 1, wherein the generation algorithm uses natural language processing techniques to identify user requests, analyzes their emotional state, and adjusts the choices accordingly.

[0844] "Application example 2 when combining with an emotional engine"

[0845] (Claim 1)

[0846] In an information processing device, a means for inputting the content desired by the user in natural language,

[0847] A central control unit that receives and analyzes input data transmitted from the aforementioned information processing device,

[0848] A means including a generation model that obtains relevant service information from a storage unit based on the aforementioned analysis results and selects the optimal option,

[0849] means for transmitting and displaying the aforementioned optimal choice to the information processing device,

[0850] A means of receiving information on service purchases made by users and sharing profits with the service provider,

[0851] A means of judging the emotional state of users and optimally adjusting the environment,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, which selects the optimal option considering the user's location information and past usage history.

[0855] (Claim 3)

[0856] The system according to claim 1, wherein a generative model uses natural language processing technology to identify what the user wants, and an emotion engine is used to analyze the emotional state. [Explanation of symbols]

[0857] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for the user to input desired content in natural language on an information processing terminal, A central processing unit that receives and analyzes input data transmitted from the aforementioned information processing terminal, A means including a generative model that retrieves relevant service information from a database based on the aforementioned analysis results and selects the optimal option, means for transmitting and displaying the aforementioned optimal choice to the information processing terminal, A means of receiving user purchase information for services and sharing profits with the service provider, A system that includes this.

2. The system according to claim 1, which selects the optimal option considering the user's location information and past usage history.

3. The system according to claim 1, wherein a generative model uses natural language processing technology to identify content desired by the user.

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