system

Abstract

We provide the system. [Solution] A means of receiving search conditions from a communication terminal, Means of collecting information from websites and communication platforms, A means for analyzing information collected using natural language processing and generating a summary, A means for providing the generated summary to a communication terminal, A means of receiving purchase instructions from users and carrying out purchase procedures via an e-commerce system, A means of notifying the user of purchase completion information, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes 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] Modern consumers need to check word-of-mouth information on numerous websites and communication platforms when making a purchase decision for a product. However, this process is time-consuming and laborious and not efficient. Also, because the information is scattered, it is difficult for consumers to comprehensively and objectively grasp the situation. Furthermore, in the process of the purchasing procedure, there is a problem that input operations and information confirmation on multiple platforms are required, complicating the user experience.

Means for Solving the Problems

[0005] This invention provides a means for receiving search criteria from a communication terminal and collecting information from multiple websites and communication platforms based on those criteria. The collected information is analyzed using natural language processing to classify positive and negative opinions and generate summaries. These summaries are provided to the communication terminal for user review. If the user wishes to make a purchase, the purchase procedure is carried out via an e-commerce system, and the user is notified of the completion of the purchase, thereby streamlining the process from information collection to purchase and improving the user experience.

[0006] A "communication terminal" is a device that allows a user to input and transmit digital information, and includes smartphones, computers, and other similar devices.

[0007] A "website" is an information page accessible via the internet, an online space where product information and customer reviews are posted.

[0008] A "communication platform" refers to online services or applications that enable users to exchange information, and includes social networking services (SNS) and messaging services.

[0009] "Means of information gathering" refers to the process or method of obtaining useful data from various digital resources based on specified search criteria.

[0010] "Natural language processing" is a technology that enables computers to understand human language, and it processes text data by performing grammatical analysis, semantic analysis, and other similar processes.

[0011] "Means for generating summaries" refers to methods or techniques for extracting key points from collected information and summarizing them concisely.

[0012] An "electronic commerce system" is an online platform that facilitates the buying and selling of goods and services via the internet, and typically serves to connect buyers and sellers.

[0013] "Means of completing the purchase process" refers to the series of processes and methods that allow a user to complete a transaction after selecting a product, such as making payment and setting the shipping address.

[0014] "Means of notifying purchase completion information" refers to methods and technologies used to inform users that a transaction has been successfully completed, and these are typically done via email or in-app notifications. [Brief explanation of the drawing]

[0015] [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] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 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 the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple 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.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] 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.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] The AI ​​agent system for summarizing word-of-mouth information according to the present invention is characterized in that, based on search conditions received from the user's communication terminal, the server automatically collects relevant word-of-mouth information from various sources such as websites, social networking services, and video sharing platforms. The server structures the acquired information and generates a summary of the information by analyzing the text using natural language processing (NLP) technology. In this process, positive and negative opinions are identified and a summary is constructed. The generated summary is then sent back to the communication terminal and provided to the user.

[0037] Users can easily view summarized information on their devices and proceed with purchasing items they are interested in. Once a user has made their purchase selection, they send a purchase instruction to the server using their device. Based on this instruction, the server accesses the e-commerce site for the selected items and automatically adds the items to the cart, manages payment information, and sets up shipping information.

[0038] As a concrete example, consider a scenario where a user uses their smartphone to gather information about "wireless headphones." In this case, the user enters search criteria on their device and submits them. The server then collects reviews and user feedback on wireless headphones from sources such as Amazon, iHerb, and YouTube® reviews. The collected data is analyzed, summarized, and presented to the user's device, highlighting aspects such as positive feedback on sound quality and issues with battery life. When the user selects a product they like and presses the purchase button, the server completes the purchase process on the relevant platform and finally displays a purchase completion notification on the device.

[0039] This system allows users to easily overview a vast amount of word-of-mouth information from diverse sources, enabling them to complete purchase procedures quickly and conveniently.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user uses their device to enter the category or specific product name they are looking for and submits a search request. The device then sends the user's needs to the server.

[0043] Step 2:

[0044] The server receives search requests from terminals and analyzes their content. Based on the necessary keywords and category information, it decides which information sources to collect review data from.

[0045] Step 3:

[0046] The server collects relevant user reviews using APIs and scraping techniques from websites, social media, and video sharing platforms. It executes search queries against each information source to retrieve the data.

[0047] Step 4:

[0048] The server organizes the collected data and performs text analysis using natural language processing techniques. This analysis extracts important key phrases from the information and classifies the reviews into positive and negative evaluations.

[0049] Step 5:

[0050] Based on the analysis results, the server summarizes multiple reviews and reconstructs the information in a way that is easy for users to understand. The summary includes information about the product's features, advantages, disadvantages, and user experience.

[0051] Step 6:

[0052] The server sends the generated summary to the terminal. This allows the terminal to display the summary information to the user, enabling the user to evaluate the product in detail.

[0053] Step 7:

[0054] The user reviews the summarized information through their device and selects the products they like. Once they have made their selection, the user sends a purchase instruction from their device to the server to proceed with the purchase.

[0055] Step 8:

[0056] The server receives a purchase instruction from the user and initiates the purchase process on the relevant e-commerce site. It adds items to the cart, processes payment, verifies shipping information, and completes the transaction.

[0057] Step 9:

[0058] After the purchase process is complete, the server sends information to the device indicating that the purchase has been confirmed. The device then displays this notification to the user, providing them with order confirmation.

[0059] (Example 1)

[0060] 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."

[0061] While a vast amount of user reviews exist online, it is extremely difficult for users to efficiently gather this information, summarize it, and understand only the necessary details. Furthermore, with the current situation where the reliability of information and the judgment of positive / negative opinions are left to individual users, it is difficult to obtain the objective information necessary for purchasing decisions. Therefore, there is a need for a system that allows users to easily obtain user reviews from diverse sources, quickly summarize them, and use them to inform their decision-making.

[0062] 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.

[0063] In this invention, the server includes means for receiving search criteria from a communication device, means for collecting data from information provision services and information exchange media, and means for analyzing the collected data using natural language processing technology and generating a summary. This enables users to effectively obtain word-of-mouth information from a wide range of sources and make objective and rapid decisions.

[0064] A "communication device" is a device that allows a user to connect to the internet and send and receive information, and includes smartphones, personal computers, and other similar devices.

[0065] "Search criteria" refer to the conditions and keywords that users enter to specify the information they are looking for, and serve as guidelines for data collection.

[0066] "Information provision services" is a general term for websites and platforms that provide various data and information over the internet.

[0067] An "information exchange medium" refers to a platform where people share information, such as social networking services (SNS) or online forums.

[0068] A "data interface" is a means of connection that enables data communication between a specific web service and an external system, and refers to APIs, etc.

[0069] "Natural language processing technology" is a technology that analyzes human language on a computer and understands its structure and meaning.

[0070] A "summary" is a document that extracts the main points from a large amount of information and presents them concisely.

[0071] An "artificial intelligence model" is a program that uses machine learning and deep learning technologies to think and make decisions like a human.

[0072] An "electronic transaction system" is a system for buying and selling goods via the internet, and includes online shopping platforms, etc.

[0073] The AI ​​agent system for summarizing word-of-mouth information, according to the present invention, operates collaboratively with a user, a terminal, and a server. The user inputs search criteria using a communication device and sends them to the server via the terminal. For example, a specific prompt sentence such as "reputation of sound quality and battery life of wireless headphones" can be sent.

[0074] Based on these search criteria, the server collects data from information provision services and information exchange media. Data collection utilizes the data interfaces provided by each service, such as APIs. The server structures the collected data and analyzes it using natural language processing techniques. Specifically, it uses software such as SpaCy and NLTK to perform morphological analysis and topic extraction of text. It also uses the sentiment analysis tool VADER to identify positive and negative opinions. The analysis results are converted into a summary using a generative AI model. OpenAI® language models and other tools are used to summarize the information in the format desired by the user.

[0075] Next, the server sends the generated summary to the communication device, making it immediately available for the user to view. Based on the presented summary, the user selects products they are interested in. If they find a product they like, the user sends a purchase instruction to the server via their terminal. Based on this instruction, the server automates the purchase process through the electronic transaction system. For example, it adds the product to the cart, enters payment information, and sets up delivery. Once the transaction is complete, the server notifies the user of this information, providing a smooth purchasing experience.

[0076] Thus, the present invention makes it possible to efficiently and quickly acquire and summarize the information that users desire, and to easily guide them toward purchasing products.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The user uses a communication device to enter specific search criteria and send them to the server. These search criteria are expressed as a prompt. For example, the text "Wireless headphone sound quality and battery reputation" is used as input and sent to the server. Specifically, the user enters the prompt in the search bar of their device and presses the "Search" button.

[0080] Step 2:

[0081] The server analyzes the search criteria received from the user and identifies information provision services and information exchange media. The server uses the necessary data interfaces (such as APIs) to access these platforms and collect relevant data. Using the received prompts as input, the server retrieves reviews and testimonials from sources such as Amazon and review sites as output. Specifically, the server sends queries to each platform and stores the returned data.

[0082] Step 3:

[0083] The server structures the collected data and performs text analysis using natural language processing techniques. It uses the collected raw text data as input and generates tagged data identifying positive, negative, and neutral opinions as output. Specifically, the server performs morphological analysis using the SpaCy library and analyzes sentiment using VADER.

[0084] Step 4:

[0085] The server uses a generative AI model to generate summaries from analyzed data. Using tagged, analyzed data as input, it generates easily understandable summary text for the user as output. Specifically, the server uses an OpenAI language model to create the desired summary.

[0086] Step 5:

[0087] The server sends the generated summary to the user's terminal. This is an output process that allows the user to easily access the information. Specifically, the server sends the summary data to the communication device's application, which then displays it on the screen.

[0088] Step 6:

[0089] The user reviews the provided summary on their device and decides to purchase the items they like. The user presses the purchase button to send the purchase instruction to the server. The user's selections and purchase request information are used as input and transmitted to the server. Specifically, the user checks the details of the selected items and clicks the "Purchase" button.

[0090] Step 7:

[0091] The server receives purchase instructions from the user and automates the purchase process through the electronic trading system. The server receives the user's purchase information as input, adds items to the cart, enters payment information, and completes shipping settings. It then sends a purchase completion notification to the user as output. Specifically, the server accesses the API of the relevant trading site, enters the necessary data, and confirms the order.

[0092] (Application Example 1)

[0093] 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."

[0094] On current e-commerce platforms, it is difficult for users to efficiently collect and analyze product reviews in a short amount of time. Furthermore, users often have to go through the entire purchase process from scratch, which is cumbersome and time-consuming. In addition, when making a purchase decision, users need to be presented with reliable and summarized evaluations gathered from various sources.

[0095] 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.

[0096] In this invention, the server includes means for receiving search criteria from a communication device, means for obtaining information from information sources, means for analyzing the obtained information using natural language processing and creating a summary, and means for executing an automated payment procedure using the summary information. This makes it possible to easily aggregate a large amount of word-of-mouth information across diverse information sources and to implement an efficient purchase procedure.

[0097] A "communication device" is an electronic device used by users to search for, receive, and transmit information.

[0098] "Search criteria" refer to the conditions or items that users specify when gathering information.

[0099] An "information source" refers to the place or medium through which information is disseminated, such as a website or a communication platform.

[0100] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language.

[0101] A "summary" is a text that concisely organizes a vast amount of information and extracts the most important points.

[0102] "Payment procedures" refer to the series of operations and processes necessary to pay for purchased goods.

[0103] "Summary information" refers to a summary of information generated through natural language processing.

[0104] "Automated payment processing" refers to a process where the payment procedures required for a purchase are automatically handled by the system.

[0105] This invention relates to a word-of-mouth summary AI agent system that enables users to collect information and efficiently carry out purchase procedures. This system is implemented via the user's communication terminal and a server.

[0106] Users use a communication device to input search criteria for specific products or services. This information is sent to a server. The server executes a Python program to collect reviews and testimonials from various information sources. The application program interface of each information source is used to access it.

[0107] The collected data is analyzed using natural language processing. Specifically, the Hugging Face Transformers library is used, and a generative AI model summarizes the reviews. This summarization process classifies the positive and negative evaluations within the information. The generated summary information is then sent back to the user's communication device and presented in a format that is easily accessible to the user.

[0108] After reviewing ratings and summaries, users select the items they wish to purchase and submit a purchase order through the system. The server then handles the automated payment process via the e-commerce platform. This process allows users to easily complete complex purchase procedures.

[0109] As a concrete example, suppose a user is considering making a reservation at a new cafe. In this case, the user uses their smartphone to search for reviews of cafes and enters a prompt such as, "Please tell me the reviews of recently opened cafes." The server analyzes and summarizes the prompt, ultimately helping the user quickly make a reservation or purchase a coupon for a cafe they are interested in.

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The user uses a communication terminal to enter search criteria for a specific product or service and sends them to the server. The entered search criteria might be something like "reviews of the latest wireless headphones." The server receives these search criteria and proceeds to the next processing step based on them.

[0113] Step 2:

[0114] The server executes a program for accessing information sources and retrieves information that matches the specified criteria. Specifically, it uses the application program interface of the information source to collect relevant reviews and comments from review sites and video sharing platforms. The input for this step is the search criteria, and the output is a dataset of the collected information.

[0115] Step 3:

[0116] The server applies natural language processing to analyze the collected data. Using the Hugging Face Transformers library, a generative AI model generates summaries of the reviews. The data is organized based on positive and negative ratings. The input for this step is the collected information dataset, and the output is the summarized information.

[0117] Step 4:

[0118] The server transmits the generated summary information to the communication terminal and presents it to the user. The user reviews the information and makes a selection of products or services. This step is the phase in which the user scrutinizes the displayed information and makes a purchase decision. The input is the summarized information, and the output is the user's selection.

[0119] Step 5:

[0120] After the user selects the items they wish to purchase, they send this information from their communication terminal to the server. The server receives this information and executes an automated payment process through the e-commerce platform. During this process, the necessary payment information is set up by the system, and the transaction is completed. The input for this step is the user's selection information, and the output is a notification that the purchase process is complete.

[0121] Step 6:

[0122] After the server confirms the purchase is complete, it returns that information to the communication terminal and notifies the user. This allows the user to confirm in real time that the purchase was successfully completed. The input is the purchase completion status information, and the output is the notification to the user.

[0123] 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.

[0124] The AI ​​agent system for summarizing user reviews of the present invention, in addition to its basic function of collecting, summarizing, and providing relevant user review information based on search criteria received from the user's communication terminal, incorporates an emotion engine that analyzes the user's emotions, thereby achieving more personalized information delivery. The server first receives search criteria from the terminal and collects information from specified websites and communication platforms. The collected data is analyzed using natural language processing technology, and positive and negative opinions are classified and summarized.

[0125] The emotion engine monitors user operation data, input behavior, operation time, and operation frequency on the user's device to evaluate the user's emotional state in real time. Based on this emotional data, the server adjusts the presentation order of collected word-of-mouth information and has the function of providing optimal information in line with the user's emotions.

[0126] As a concrete example, consider a scenario where a user gathers information about fitness equipment. When the user searches for "treadmill" on their device, the server collects user reviews from Amazon, health information sites, and YouTube. As the user spends more time browsing reviews and moves between pages frequently, the sentiment engine detects positive emotions indicating the user's interest. The server then changes its settings to prioritize displaying positive reviews, personalizing the information gathering experience to make it more enjoyable for the user.

[0127] Furthermore, when a user selects a product, the purchase process in the e-commerce system is expedited, and a notification is displayed on the device upon completion of the purchase. The introduction of an emotion engine allows users to enjoy a more comfortable and effective information gathering and purchasing experience tailored to their individual emotional state.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The user operates the device, enters a category of product they are interested in or a specific product name, and sends a search request. The device forwards this request to the server.

[0131] Step 2:

[0132] The server receives requests from users and analyzes the search criteria. Based on this analysis, it decides which websites and communication platforms to collect user reviews from.

[0133] Step 3:

[0134] The server accesses the specified information source and collects relevant user reviews using APIs and scraping techniques. It executes queries using search keywords to retrieve data.

[0135] Step 4:

[0136] The server structures the collected data and analyzes the text using natural language processing (NLP) techniques. This process includes extracting key phrases and classifying positive and negative opinions.

[0137] Step 5:

[0138] Based on the analyzed data, the server generates a summary. This summary is structured to include key features, strengths, weaknesses, and the overall user experience.

[0139] Step 6:

[0140] The emotion engine monitors user activity data on the user's device and evaluates the user's emotional state in real time. This evaluation includes user activity time, frequency of page transitions, and input procedures.

[0141] Step 7:

[0142] The server dynamically adjusts the order in which information is presented based on feedback from the emotion engine. Information in which the user has expressed positive emotions is displayed preferentially.

[0143] Step 8:

[0144] The terminal displays summary information received from the server to the user. The user views this information and evaluates the product based on the details.

[0145] Step 9:

[0146] When a user decides to make a purchase, they send a purchase instruction to the server via their device. This instruction is intended to complete the purchase of a specific product or service.

[0147] Step 10:

[0148] The server receives a purchase instruction from the user and initiates the purchase process within the e-commerce system. This includes adding items to the shopping cart, entering payment information, and setting shipping information.

[0149] Step 11:

[0150] Once the purchase process is complete, the server sends a confirmation of the purchase to the device. The device then displays a notification to the user that includes this confirmation.

[0151] (Example 2)

[0152] 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".

[0153] Gathering a large amount of word-of-mouth information from diverse sources and providing information that responds to users' emotional states is technically very complex. Furthermore, systems that provide personalized information based on user emotions have not been effectively implemented with existing technologies. In addition to the sheer volume and variability in quality of information, there are challenges in how to provide information that takes user emotions into account.

[0154] 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.

[0155] In this invention, the server includes means for receiving search conditions, means for collecting information, means for analyzing the information and generating a summary using natural language processing technology, and means for adjusting the order in which information is presented using an emotion engine that evaluates the user's emotional state. This enables the rapid and accurate presentation of information of interest to the user, resulting in a personalized information acquisition experience.

[0156] "Means for receiving search conditions" refers to technical measures that enable the system's server to obtain specific keywords or conditions entered by the user via a communication terminal.

[0157] "Means of information gathering" refers to functions and protocols for collecting data from multiple specified sources and aggregating it on a server.

[0158] "Natural language processing technology" refers to computer processing techniques used to analyze and understand text data, and to classify or summarize information as needed.

[0159] An "emotion engine" is a system component that analyzes user behavior and operation history to detect and evaluate the user's emotional state in real time.

[0160] "Means for adjusting the order in which information is presented" refers to technical measures that have the functionality to arrange and present information to the user in an optimal order based on the user's emotional state and interests.

[0161] "A means of conducting purchase procedures via a transaction system" refers to a mechanism that connects with an e-commerce platform to automatically perform the necessary purchase procedures for the goods or services selected by the user and complete the transaction.

[0162] The system for implementing this invention has functions to analyze text data collected from multiple sources using natural language processing technology, create positive and negative summaries, and optimize information delivery based on the user's emotions.

[0163] First, the user uses a communication device to enter search criteria for a specific product or service. The server immediately receives these search criteria and collects relevant data from multiple sources (e.g., websites and review sites). Web scraping and APIs can be used to efficiently collect diverse data.

[0164] Next, the server performs natural language processing on the collected data. Specifically, it analyzes the information and generates a summary using advanced natural language processing technologies such as Python's NLTK library and Google's BERT model. In this process, it classifies the information into positive and negative evaluations and extracts the key points.

[0165] Furthermore, the user's device is equipped with an emotion engine. This engine monitors user interaction data (click patterns, page dwell time, etc.) and evaluates the user's emotional state in real time. Based on the emotion engine's evaluation, the server adjusts the order in which information is presented, prioritizing information that the user is interested in.

[0166] As a concrete example, consider a scenario where a user is researching fitness equipment. When the user searches for "high-performance treadmill," the server collects and analyzes relevant user reviews and provides a summary tailored to the user's emotional state. For users who spend a long time viewing reviews, the sentiment engine determines that they are interested, and the server prioritizes displaying information with positive reviews.

[0167] The input to the generative AI model will use a specific prompt such as, "Summarize reviews suitable for users considering purchasing fitness equipment, and present them with a priority given to positive reviews."

[0168] In this way, the system enables the provision of information that responds to the user's emotions and can meet diverse needs.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] The server receives search criteria entered by the user via a communication terminal. It receives the user-specified keyword (e.g., "treadmill") as input data and functions as a trigger to proceed to the next step. Based on these search criteria, data collection begins from appropriate sources.

[0172] Step 2:

[0173] The server collects data from specified sources. The input is the search criteria received in step 1, and based on this, it retrieves relevant information from websites and databases via crawling or APIs. The output is a collection of raw, collected user reviews. This data collection process utilizes technology to retrieve regularly updated information in real time.

[0174] Step 3:

[0175] The server applies natural language processing to the collected data. It receives the word-of-mouth information obtained in step 2 as input, analyzes the data using Python's NLTK library and Google's BERT model, and generates summaries including positive and negative evaluations. The output is the analyzed summary data, which is then organized into the content presented to the user.

[0176] Step 4:

[0177] The emotion engine, located on the device, monitors user interaction data. Inputs include behavioral data such as user click patterns and page dwell time. The engine analyzes this data and infers the user's emotional state in real time. The output is evaluation data regarding the user's emotional state.

[0178] Step 5:

[0179] The server uses evaluation data from the emotion engine to adjust the order in which information is presented. The inputs here are the summary data from step 3 and the emotion evaluation data from step 4. The server rearranges the information and optimizes it to align with the user's emotions. The output is a set of feedback information to be displayed to the user, which is then sent to the terminal.

[0180] Step 6:

[0181] When a user selects an item, the terminal sends a purchase instruction to the server. The input is the purchase information that the user has confirmed and selected. Based on this, the server calls the transaction system and quickly completes the purchase process. The output is the confirmed purchase information and a purchase completion notification. The server immediately sends this to the terminal to inform the user that the transaction is complete.

[0182] (Application Example 2)

[0183] 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".

[0184] When users gather information or make purchases through communication devices, it is difficult to efficiently obtain relevant information, and in particular, it is difficult to grasp a large amount of word-of-mouth information at once. Furthermore, there is a challenge in providing personalized information because the customization of information based on the user's emotional state is insufficient.

[0185] 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.

[0186] In this invention, the server includes means for receiving search conditions from a communication terminal, means for collecting information from websites and information exchange platforms, means for analyzing the collected information using natural language processing and generating a summary, and means for analyzing the user's emotions and adjusting the order in which the collected information is presented. This enables users to have an efficient and personalized information gathering and purchasing experience that is tailored to their emotional state.

[0187] A "communication terminal" is a device used by a user to perform information processing, and includes smartphones, tablets, and other similar devices.

[0188] "Search criteria" refer to keywords and filtering requirements specified by the user, and relevant information is collected based on these criteria.

[0189] A "website" is a collection of online pages that exist on the internet and provide information.

[0190] An "information exchange platform" is an online service that allows users to exchange information with each other, and includes social networks and messaging applications.

[0191] "Natural language processing" is a technology that enables computers to understand and process human language, making it possible to analyze text and generate summaries.

[0192] A "summary" is a concise explanation that extracts the key points from a large amount of information, enabling users to understand the information efficiently.

[0193] "User emotions" refer to information that indicates the user's psychological state, and are inferred from behavioral data and biosignals.

[0194] "Adjusting the presentation order" refers to changing the display order of information to take into account the user's emotional state and providing personalized information.

[0195] An "electronic commerce system" is a system for buying and selling goods and services online, where the purchase process is automated.

[0196] A "purchase instruction" is an action in which a user expresses their intention to purchase a specific product or service.

[0197] This invention is a system that operates based on data communication between a communication terminal and a server. The user enters search criteria using the communication terminal. These search criteria are sent to the server, which then collects relevant information from specified websites and information exchange platforms. By using multiple data acquisition interfaces, efficient and comprehensive data collection can be achieved.

[0198] The server also uses natural language processing techniques to analyze the collected information and generate a summary. This summary includes positive and negative evaluations, allowing users to concisely understand the overall picture of the information.

[0199] Furthermore, the server analyzes user interaction data to evaluate user emotions in real time. Based on the results of the emotion analysis, it adjusts the presentation order to prioritize information that the user is interested in. This process utilizes machine learning models and is optimized to provide the most relevant information to the user.

[0200] In the purchase flow, when a user indicates a purchase instruction for a product, the server quickly processes the purchase via the e-commerce system. After the purchase is complete, a completion notification is displayed on the communication terminal. This allows users to enjoy a seamless and efficient purchasing experience. Furthermore, it is possible to learn which information the user showed the most interest in and use that information to provide information in the future.

[0201] For example, when a user searches for "treadmill," the server collects reviews from fitness-related review sites and video platforms and generates a summary. If the user's browsing behavior indicates positive emotions, the system is configured to prioritize displaying reviews that have received particularly high ratings. This allows the user to enjoy a more comfortable information gathering experience. Further analysis and customization are possible by utilizing prompts to the generative AI model, such as, "If a user has been browsing treadmill reviews for a long time, they are likely to have positive emotions. Suggest how we can customize the information to encourage purchase based on those emotions."

[0202] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0203] Step 1:

[0204] The user uses a communication terminal to enter search criteria. The entered search criteria are in keyword format and are sent as a request to the server. The server receives this input, parses the search criteria, and prepares for the next step.

[0205] Step 2:

[0206] The server collects information based on the received search criteria through data acquisition interfaces of multiple websites and information exchange platforms. During this process, it uses APIs to gather relevant reviews and testimonials from specified platforms and stores them as text data. This collected text data serves as input for analysis in the next step.

[0207] Step 3:

[0208] The server uses natural language processing technology to analyze the collected text data and generate a summary. This process utilizes a generative AI model to extract key points from the text and classify them into positive and negative opinions. This generates a summary, which is then transformed into a user-friendly format. The generated summary is then used to prepare for presentation in the next step.

[0209] Step 4:

[0210] User operation data from their communication device is sent to the server, where sentiment analysis is performed. The server analyzes the user's operation time, click count, etc., and evaluates the user's emotional state. Based on this evaluation, the server adjusts the order in which it presents information. The results of the sentiment analysis are used to personalize the information presentation and serve as input for setting the priority of the content to be provided next.

[0211] Step 5:

[0212] The server provides the communication terminal with a summary generated in a coordinated order. The user can view and review the information on the communication terminal. This includes priority information that reflects sentiment analysis, providing information tailored to the user. If the user shows interest in a particular product among the displayed information, the system prepares to proceed to the next step.

[0213] Step 6:

[0214] When a user places a purchase order for a product on their device, the order is sent to the server. The server then proceeds with the purchase process via the e-commerce system. During the purchase process, transaction details are processed, a completion notification is generated, and sent to the device. This confirms to the user that the purchase has been completed.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] [Second Embodiment]

[0219] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0220] 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.

[0221] 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).

[0222] 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.

[0223] 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.

[0224] 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).

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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.

[0230] 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".

[0231] The AI ​​agent system for summarizing word-of-mouth information according to the present invention is characterized in that, based on search conditions received from the user's communication terminal, the server automatically collects relevant word-of-mouth information from various sources such as websites, social networking services, and video sharing platforms. The server structures the acquired information and generates a summary of the information by analyzing the text using natural language processing (NLP) technology. In this process, positive and negative opinions are identified and a summary is constructed. The generated summary is then sent back to the communication terminal and provided to the user.

[0232] Users can easily view summarized information on their devices and proceed with purchasing items they are interested in. Once a user has made their purchase selection, they send a purchase instruction to the server using their device. Based on this instruction, the server accesses the e-commerce site for the selected items and automatically adds the items to the cart, manages payment information, and sets up shipping information.

[0233] As a concrete example, consider a scenario where a user uses their smartphone to gather information about "wireless headphones." In this case, the user enters search criteria on their device and submits them. The server then collects reviews and user feedback on wireless headphones from sources such as Amazon, iHerb, and YouTube. The collected data is analyzed, summarized, and presented to the user's device, highlighting aspects such as positive reviews regarding sound quality and issues with battery life. When the user selects a product they like and presses the purchase button, the server completes the purchase process on the relevant platform and finally displays a purchase completion notification on the device.

[0234] This system allows users to easily overview a vast amount of word-of-mouth information from diverse sources, enabling them to complete purchase procedures quickly and conveniently.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] The user uses their device to enter the category or specific product name they are looking for and submits a search request. The device then sends the user's needs to the server.

[0238] Step 2:

[0239] The server receives search requests from terminals and analyzes their content. Based on the necessary keywords and category information, it decides which information sources to collect review data from.

[0240] Step 3:

[0241] The server collects relevant user reviews using APIs and scraping techniques from websites, social media, and video sharing platforms. It executes search queries against each information source to retrieve the data.

[0242] Step 4:

[0243] The server organizes the collected data and performs text analysis using natural language processing techniques. This analysis extracts important key phrases from the information and classifies the reviews into positive and negative evaluations.

[0244] Step 5:

[0245] Based on the analysis results, the server summarizes multiple reviews and reconstructs the information in a way that is easy for users to understand. The summary includes information about the product's features, advantages, disadvantages, and user experience.

[0246] Step 6:

[0247] The server sends the generated summary to the terminal. This allows the terminal to display the summary information to the user, enabling the user to evaluate the product in detail.

[0248] Step 7:

[0249] The user reviews the summarized information through their device and selects the products they like. Once they have made their selection, the user sends a purchase instruction from their device to the server to proceed with the purchase.

[0250] Step 8:

[0251] The server receives a purchase instruction from the user and initiates the purchase process on the relevant e-commerce site. It adds items to the cart, processes payment, verifies shipping information, and completes the transaction.

[0252] Step 9:

[0253] After the purchase process is complete, the server sends information to the device indicating that the purchase has been confirmed. The device then displays this notification to the user, providing them with order confirmation.

[0254] (Example 1)

[0255] 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."

[0256] While a vast amount of user reviews exist online, it is extremely difficult for users to efficiently gather this information, summarize it, and understand only the necessary details. Furthermore, with the current situation where the reliability of information and the judgment of positive / negative opinions are left to individual users, it is difficult to obtain the objective information necessary for purchasing decisions. Therefore, there is a need for a system that allows users to easily obtain user reviews from diverse sources, quickly summarize them, and use them to inform their decision-making.

[0257] 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.

[0258] In this invention, the server includes means for receiving search criteria from a communication device, means for collecting data from information provision services and information exchange media, and means for analyzing the collected data using natural language processing technology and generating a summary. This enables users to effectively obtain word-of-mouth information from a wide range of sources and make objective and rapid decisions.

[0259] A "communication device" is a device that allows a user to connect to the internet and send and receive information, and includes smartphones, personal computers, and other similar devices.

[0260] "Search criteria" refer to the conditions and keywords that users enter to specify the information they are looking for, and serve as guidelines for data collection.

[0261] "Information provision services" is a general term for websites and platforms that provide various data and information over the internet.

[0262] An "information exchange medium" refers to a platform where people share information, such as social networking services (SNS) or online forums.

[0263] A "data interface" is a means of connection that enables data communication between a specific web service and an external system, and refers to APIs, etc.

[0264] "Natural language processing technology" is a technology that analyzes human language on a computer and understands its structure and meaning.

[0265] A "summary" is a document that extracts the main points from a large amount of information and presents them concisely.

[0266] An "artificial intelligence model" is a program that uses machine learning and deep learning technologies to think and make decisions like a human.

[0267] An "electronic transaction system" is a system for buying and selling goods via the internet, and includes online shopping platforms, etc.

[0268] The AI ​​agent system for summarizing word-of-mouth information, according to the present invention, operates collaboratively with a user, a terminal, and a server. The user inputs search criteria using a communication device and sends them to the server via the terminal. For example, a specific prompt sentence such as "reputation of sound quality and battery life of wireless headphones" can be sent.

[0269] Based on these search criteria, the server collects data from information provision services and information exchange media. Data collection utilizes the data interfaces provided by each service, such as APIs. The server structures the collected data and analyzes it using natural language processing techniques. Specifically, it uses software such as SpaCy and NLTK to perform morphological analysis and topic extraction of text. It also uses the sentiment analysis tool VADER to identify positive and negative opinions. The analysis results are converted into a summary using a generative AI model. OpenAI's language models and other tools are used to summarize the information in the format desired by the user.

[0270] Next, the server sends the generated summary to the communication device, making it immediately available for the user to view. Based on the presented summary, the user selects products they are interested in. If they find a product they like, the user sends a purchase instruction to the server via their terminal. Based on this instruction, the server automates the purchase process through the electronic transaction system. For example, it adds the product to the cart, enters payment information, and sets up delivery. Once the transaction is complete, the server notifies the user of this information, providing a smooth purchasing experience.

[0271] Thus, the present invention makes it possible to efficiently and quickly acquire and summarize the information that users desire, and to easily guide them toward purchasing products.

[0272] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0273] Step 1:

[0274] The user uses a communication device to enter specific search criteria and send them to the server. These search criteria are expressed as a prompt. For example, the text "Wireless headphone sound quality and battery reputation" is used as input and sent to the server. Specifically, the user enters the prompt in the search bar of their device and presses the "Search" button.

[0275] Step 2:

[0276] The server analyzes the search criteria received from the user and identifies information provision services and information exchange media. The server uses the necessary data interfaces (such as APIs) to access these platforms and collect relevant data. Using the received prompts as input, the server retrieves reviews and testimonials from sources such as Amazon and review sites as output. Specifically, the server sends queries to each platform and stores the returned data.

[0277] Step 3:

[0278] The server structures the collected data and performs text analysis using natural language processing techniques. It uses the collected raw text data as input and generates tagged data identifying positive, negative, and neutral opinions as output. Specifically, the server performs morphological analysis using the SpaCy library and analyzes sentiment using VADER.

[0279] Step 4:

[0280] The server uses a generative AI model to generate summaries from analyzed data. Using tagged, analyzed data as input, it generates easily understandable summary text for the user as output. Specifically, the server uses an OpenAI language model to create the desired summary.

[0281] Step 5:

[0282] The server sends the generated summary to the user's terminal. This is an output process that allows the user to easily access the information. Specifically, the server sends the summary data to the communication device's application, which then displays it on the screen.

[0283] Step 6:

[0284] The user checks the provided summary on the terminal and decides to purchase the products they like. The user presses the purchase button to send a purchase instruction to the server. The user's selection and purchase intention information are used as input and transmitted to the server. As a specific operation, the user checks the details of the selected product and clicks the "Purchase" button.

[0285] Step 7:

[0286] The server receives the purchase instruction from the user and conducts the purchase procedure in an automated manner through the electronic trading system. The server receives the user's purchase information as input, adds the product to the cart, enters the payment information, and completes the delivery settings. As output, a notification of the completion of the purchase procedure is sent to the user. As a specific operation, the server accesses the API of the corresponding trading site, enters the necessary data, and finalizes the order.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0289] In the current e-commerce trading platform, it is difficult for users to efficiently collect and analyze product review information in a short time. Also, users need to conduct the purchase procedure of the products they are interested in from scratch, which is often cumbersome and time-consuming. Furthermore, when making a purchase decision, it is necessary to present the evaluations collected from various information sources in a reliable and summarized form.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0291] In this invention, the server includes means for receiving search criteria from a communication device, means for obtaining information from information sources, means for analyzing the obtained information using natural language processing and creating a summary, and means for executing an automated payment procedure using the summary information. This makes it possible to easily aggregate a large amount of word-of-mouth information across diverse information sources and to implement an efficient purchase procedure.

[0292] A "communication device" is an electronic device used by users to search for, receive, and transmit information.

[0293] "Search criteria" refer to the conditions or items that users specify when gathering information.

[0294] An "information source" refers to the place or medium through which information is disseminated, such as a website or a communication platform.

[0295] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language.

[0296] A "summary" is a text that concisely organizes a vast amount of information and extracts the most important points.

[0297] "Payment procedures" refer to the series of operations and processes necessary to pay for purchased goods.

[0298] "Summary information" refers to a summary of information generated through natural language processing.

[0299] "Automated payment processing" refers to a process where the payment procedures required for a purchase are automatically handled by the system.

[0300] This invention relates to a word-of-mouth summary AI agent system that enables users to collect information and efficiently carry out purchase procedures. This system is implemented via the user's communication terminal and a server.

[0301] Users use a communication device to input search criteria for specific products or services. This information is sent to a server. The server executes a Python program to collect reviews and testimonials from various information sources. The application program interface of each information source is used to access it.

[0302] The collected data is analyzed using natural language processing. Specifically, the Hugging Face Transformers library is used, and a generative AI model summarizes the reviews. This summarization process classifies the positive and negative evaluations within the information. The generated summary information is then sent back to the user's communication device and presented in a format that is easily accessible to the user.

[0303] After reviewing ratings and summaries, users select the items they wish to purchase and submit a purchase order through the system. The server then handles the automated payment process via the e-commerce platform. This process allows users to easily complete complex purchase procedures.

[0304] As a concrete example, suppose a user is considering making a reservation at a new cafe. In this case, the user uses their smartphone to search for reviews of cafes and enters a prompt such as, "Please tell me the reviews of recently opened cafes." The server analyzes and summarizes the prompt, ultimately helping the user quickly make a reservation or purchase a coupon for a cafe they are interested in.

[0305] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0306] Step 1:

[0307] The user uses a communication terminal to input search criteria for specific products or services and send them to the server. The input search criteria are, for example, "reviews of the latest wireless headphones". The server receives this search criteria and proceeds to the next processing step based on it.

[0308] Step 2:

[0309] The server executes a program for accessing information sources and obtains information that meets the specified criteria. Specifically, using the application program interface of the information source, relevant reviews and comments are collected from review sites and video sharing platforms. The input for this step is the search criteria, and the output is a dataset of the collected information.

[0310] Step 3:

[0311] The server applies natural language processing to analyze the collected data. Using the Transformers library of Hugging Face, a generative AI model is used to generate a summary of the comments. The data is sorted based on positive and negative evaluations. The input for this step is the collected information dataset, and the output is the summarized information.

[0312] Step 4:

[0313] The server sends the generated summary information to the communication terminal and presents it to the user. The user checks the information and makes a selection of products or services. This step is the phase where the user examines the displayed information and makes a purchasing decision. The input is the summarized information, and the output is the user's selection.

[0314] Step 5:

[0315] After the user selects the items they wish to purchase, they send this information from their communication terminal to the server. The server receives this information and executes an automated payment process through the e-commerce platform. During this process, the necessary payment information is set up by the system, and the transaction is completed. The input for this step is the user's selection information, and the output is a notification that the purchase process is complete.

[0316] Step 6:

[0317] After the server confirms the purchase is complete, it returns that information to the communication terminal and notifies the user. This allows the user to confirm in real time that the purchase was successfully completed. The input is the purchase completion status information, and the output is the notification to the user.

[0318] 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.

[0319] The AI ​​agent system for summarizing user reviews of the present invention, in addition to its basic function of collecting, summarizing, and providing relevant user review information based on search criteria received from the user's communication terminal, incorporates an emotion engine that analyzes the user's emotions, thereby achieving more personalized information delivery. The server first receives search criteria from the terminal and collects information from specified websites and communication platforms. The collected data is analyzed using natural language processing technology, and positive and negative opinions are classified and summarized.

[0320] The emotion engine monitors user operation data, input behavior, operation time, and operation frequency on the user's device to evaluate the user's emotional state in real time. Based on this emotional data, the server adjusts the presentation order of collected word-of-mouth information and has the function of providing optimal information in line with the user's emotions.

[0321] As a concrete example, consider a scenario where a user gathers information about fitness equipment. When the user searches for "treadmill" on their device, the server collects user reviews from Amazon, health information sites, and YouTube. As the user spends more time browsing reviews and moves between pages frequently, the sentiment engine detects positive emotions indicating the user's interest. The server then changes its settings to prioritize displaying positive reviews, personalizing the information gathering experience to make it more enjoyable for the user.

[0322] Furthermore, when a user selects a product, the purchase process in the e-commerce system is expedited, and a notification is displayed on the device upon completion of the purchase. The introduction of an emotion engine allows users to enjoy a more comfortable and effective information gathering and purchasing experience tailored to their individual emotional state.

[0323] The following describes the processing flow.

[0324] Step 1:

[0325] The user operates the device, enters a category of product they are interested in or a specific product name, and sends a search request. The device forwards this request to the server.

[0326] Step 2:

[0327] The server receives requests from users and analyzes the search criteria. Based on this analysis, it decides which websites and communication platforms to collect user reviews from.

[0328] Step 3:

[0329] The server accesses the specified information source and collects relevant user reviews using APIs and scraping techniques. It executes queries using search keywords to retrieve data.

[0330] Step 4:

[0331] The server structures the collected data and analyzes the text using natural language processing (NLP) techniques. This process includes extracting key phrases and classifying positive and negative opinions.

[0332] Step 5:

[0333] Based on the analyzed data, the server generates a summary. This summary is structured to include key features, strengths, weaknesses, and the overall user experience.

[0334] Step 6:

[0335] The emotion engine monitors user activity data on the user's device and evaluates the user's emotional state in real time. This evaluation includes user activity time, frequency of page transitions, and input procedures.

[0336] Step 7:

[0337] The server dynamically adjusts the order in which information is presented based on feedback from the emotion engine. Information in which the user has expressed positive emotions is displayed preferentially.

[0338] Step 8:

[0339] The terminal displays summary information received from the server to the user. The user views this information and evaluates the product based on the details.

[0340] Step 9:

[0341] When a user decides to make a purchase, they send a purchase instruction to the server via their device. This instruction is intended to complete the purchase of a specific product or service.

[0342] Step 10:

[0343] The server receives a purchase instruction from the user and initiates the purchase process within the e-commerce system. This includes adding items to the shopping cart, entering payment information, and setting shipping information.

[0344] Step 11:

[0345] Once the purchase process is complete, the server sends a confirmation of the purchase to the device. The device then displays a notification to the user that includes this confirmation.

[0346] (Example 2)

[0347] 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".

[0348] Gathering a large amount of word-of-mouth information from diverse sources and providing information that responds to users' emotional states is technically very complex. Furthermore, systems that provide personalized information based on user emotions have not been effectively implemented with existing technologies. In addition to the sheer volume and variability in quality of information, there are challenges in how to provide information that takes user emotions into account.

[0349] 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.

[0350] In this invention, the server includes means for receiving search conditions, means for collecting information, means for analyzing the information and generating a summary using natural language processing technology, and means for adjusting the order in which information is presented using an emotion engine that evaluates the user's emotional state. This enables the rapid and accurate presentation of information of interest to the user, resulting in a personalized information acquisition experience.

[0351] "Means for receiving search conditions" refers to technical measures that enable the system's server to obtain specific keywords or conditions entered by the user via a communication terminal.

[0352] "Means of information gathering" refers to functions and protocols for collecting data from multiple specified sources and aggregating it on a server.

[0353] "Natural language processing technology" refers to computer processing techniques used to analyze and understand text data, and to classify or summarize information as needed.

[0354] An "emotion engine" is a system component that analyzes user behavior and operation history to detect and evaluate the user's emotional state in real time.

[0355] "Means for adjusting the order in which information is presented" refers to technical measures that have the functionality to arrange and present information to the user in an optimal order based on the user's emotional state and interests.

[0356] "A means of conducting purchase procedures via a transaction system" refers to a mechanism that connects with an e-commerce platform to automatically perform the necessary purchase procedures for the goods or services selected by the user and complete the transaction.

[0357] The system for implementing this invention has functions to analyze text data collected from multiple sources using natural language processing technology, create positive and negative summaries, and optimize information delivery based on the user's emotions.

[0358] First, the user uses a communication device to enter search criteria for a specific product or service. The server immediately receives these search criteria and collects relevant data from multiple sources (e.g., websites and review sites). Web scraping and APIs can be used to efficiently collect diverse data.

[0359] Next, the server performs natural language processing on the collected data. Specifically, it analyzes the information and generates summaries using advanced natural language processing technologies such as Python's NLTK library and Google's BERT model. In this process, it classifies the information into positive and negative evaluations and extracts the key points.

[0360] Furthermore, the user's device is equipped with an emotion engine. This engine monitors user interaction data (click patterns, page dwell time, etc.) and evaluates the user's emotional state in real time. Based on the emotion engine's evaluation, the server adjusts the order in which information is presented, prioritizing information that the user is interested in.

[0361] As a concrete example, consider a scenario where a user is researching fitness equipment. When the user searches for "high-performance treadmill," the server collects and analyzes relevant user reviews and provides a summary tailored to the user's emotional state. For users who spend a long time viewing reviews, the sentiment engine determines that they are interested, and the server prioritizes displaying information with positive reviews.

[0362] The input to the generative AI model will use a specific prompt such as, "Summarize reviews suitable for users considering purchasing fitness equipment, and present them with a priority given to positive reviews."

[0363] In this way, the system enables the provision of information that responds to the user's emotions and can meet diverse needs.

[0364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0365] Step 1:

[0366] The server receives search criteria entered by the user via a communication terminal. It receives the user-specified keyword (e.g., "treadmill") as input data and functions as a trigger to proceed to the next step. Based on these search criteria, data collection begins from appropriate sources.

[0367] Step 2:

[0368] The server collects data from specified sources. The input is the search criteria received in step 1, and based on this, it retrieves relevant information from websites and databases via crawling or APIs. The output is a collection of raw, collected user reviews. This data collection process utilizes technology to retrieve regularly updated information in real time.

[0369] Step 3:

[0370] The server applies natural language processing to the collected data. It receives the word-of-mouth information obtained in step 2 as input, analyzes the data using Python's NLTK library and Google's BERT model, and generates summaries including positive and negative evaluations. The output is the analyzed summary data, which is then organized into the content presented to the user.

[0371] Step 4:

[0372] The emotion engine, located on the device, monitors user interaction data. Inputs include behavioral data such as user click patterns and page dwell time. The engine analyzes this data and infers the user's emotional state in real time. The output is evaluation data regarding the user's emotional state.

[0373] Step 5:

[0374] The server uses evaluation data from the emotion engine to adjust the order in which information is presented. The inputs here are the summary data from step 3 and the emotion evaluation data from step 4. The server rearranges the information and optimizes it to align with the user's emotions. The output is a set of feedback information to be displayed to the user, which is then sent to the terminal.

[0375] Step 6:

[0376] When a user selects an item, the terminal sends a purchase instruction to the server. The input is the purchase information that the user has confirmed and selected. Based on this, the server calls the transaction system and quickly completes the purchase process. The output is the confirmed purchase information and a purchase completion notification. The server immediately sends this to the terminal to inform the user that the transaction is complete.

[0377] (Application Example 2)

[0378] 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."

[0379] When users gather information or make purchases through communication devices, it is difficult to efficiently obtain relevant information, and in particular, it is difficult to grasp a large amount of word-of-mouth information at once. Furthermore, there is a challenge in providing personalized information because the customization of information based on the user's emotional state is insufficient.

[0380] 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.

[0381] In this invention, the server includes means for receiving search conditions from a communication terminal, means for collecting information from websites and information exchange platforms, means for analyzing the collected information using natural language processing and generating a summary, and means for analyzing the user's emotions and adjusting the order in which the collected information is presented. This enables users to have an efficient and personalized information gathering and purchasing experience that is tailored to their emotional state.

[0382] A "communication terminal" is a device used by a user to perform information processing, and includes smartphones, tablets, and other similar devices.

[0383] "Search criteria" refer to keywords and filtering requirements specified by the user, and relevant information is collected based on these criteria.

[0384] A "website" is a collection of online pages that exist on the internet and provide information.

[0385] An "information exchange platform" is an online service that allows users to exchange information with each other, and includes social networks and messaging applications.

[0386] "Natural language processing" is a technology that enables computers to understand and process human language, making it possible to analyze text and generate summaries.

[0387] A "summary" is a concise explanation that extracts the key points from a large amount of information, enabling users to understand the information efficiently.

[0388] "User emotions" refer to information that indicates the user's psychological state, and are inferred from behavioral data and biosignals.

[0389] "Adjusting the presentation order" refers to changing the display order of information to take into account the user's emotional state and providing personalized information.

[0390] An "electronic commerce system" is a system for buying and selling goods and services online, where the purchase process is automated.

[0391] A "purchase instruction" is an action in which a user expresses their intention to purchase a specific product or service.

[0392] This invention is a system that operates based on data communication between a communication terminal and a server. The user enters search criteria using the communication terminal. These search criteria are sent to the server, which then collects relevant information from specified websites and information exchange platforms. By using multiple data acquisition interfaces, efficient and comprehensive data collection can be achieved.

[0393] The server also uses natural language processing techniques to analyze the collected information and generate a summary. This summary includes positive and negative evaluations, allowing users to concisely understand the overall picture of the information.

[0394] Furthermore, the server analyzes user interaction data to evaluate user emotions in real time. Based on the results of the emotion analysis, it adjusts the presentation order to prioritize information that the user is interested in. This process utilizes machine learning models and is optimized to provide the most relevant information to the user.

[0395] In the purchase flow, when a user indicates a purchase instruction for a product, the server quickly processes the purchase via the e-commerce system. After the purchase is complete, a completion notification is displayed on the communication terminal. This allows users to enjoy a seamless and efficient purchasing experience. Furthermore, it is possible to learn which information the user showed the most interest in and use that information to provide information in the future.

[0396] For example, when a user searches for "treadmill," the server collects reviews from fitness-related review sites and video platforms and generates a summary. If the user's browsing behavior indicates positive emotions, the system is configured to prioritize displaying reviews that have received particularly high ratings. This allows the user to enjoy a more comfortable information gathering experience. Further analysis and customization are possible by utilizing prompts to the generative AI model, such as, "If a user has been browsing treadmill reviews for a long time, they are likely to have positive emotions. Suggest how we can customize the information to encourage purchase based on those emotions."

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

[0398] Step 1:

[0399] The user uses a communication terminal to enter search criteria. The entered search criteria are in keyword format and are sent as a request to the server. The server receives this input, parses the search criteria, and prepares for the next step.

[0400] Step 2:

[0401] The server collects information based on the received search criteria through data acquisition interfaces of multiple websites and information exchange platforms. During this process, it uses APIs to gather relevant reviews and testimonials from specified platforms and stores them as text data. This collected text data serves as input for analysis in the next step.

[0402] Step 3:

[0403] The server uses natural language processing technology to analyze the collected text data and generate a summary. This process utilizes a generative AI model to extract key points from the text and classify them into positive and negative opinions. This generates a summary, which is then transformed into a user-friendly format. The generated summary is then used to prepare for presentation in the next step.

[0404] Step 4:

[0405] User operation data from their communication device is sent to the server, where sentiment analysis is performed. The server analyzes the user's operation time, click count, etc., and evaluates the user's emotional state. Based on this evaluation, the server adjusts the order in which it presents information. The results of the sentiment analysis are used to personalize the information presentation and serve as input for setting the priority of the content to be provided next.

[0406] Step 5:

[0407] The server provides the communication terminal with a summary generated in a coordinated order. The user can view and review the information on the communication terminal. This includes priority information that reflects sentiment analysis, providing information tailored to the user. If the user shows interest in a particular product among the displayed information, the system prepares to proceed to the next step.

[0408] Step 6:

[0409] When a user places a purchase order for a product on their device, the order is sent to the server. The server then proceeds with the purchase process via the e-commerce system. During the purchase process, transaction details are processed, a completion notification is generated, and sent to the device. This confirms to the user that the purchase has been completed.

[0410] 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.

[0411] 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.

[0412] 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.

[0413] [Third Embodiment]

[0414] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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).

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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".

[0426] The AI ​​agent system for summarizing word-of-mouth information according to the present invention is characterized in that, based on search conditions received from the user's communication terminal, the server automatically collects relevant word-of-mouth information from various sources such as websites, social networking services, and video sharing platforms. The server structures the acquired information and generates a summary of the information by analyzing the text using natural language processing (NLP) technology. In this process, positive and negative opinions are identified and a summary is constructed. The generated summary is then sent back to the communication terminal and provided to the user.

[0427] Users can easily view summarized information on their devices and proceed with purchasing items they are interested in. Once a user has made their purchase selection, they send a purchase instruction to the server using their device. Based on this instruction, the server accesses the e-commerce site for the selected items and automatically adds the items to the cart, manages payment information, and sets up shipping information.

[0428] As a concrete example, consider a scenario where a user uses their smartphone to gather information about "wireless headphones." In this case, the user enters search criteria on their device and submits them. The server then collects reviews and user feedback on wireless headphones from sources such as Amazon, iHerb, and YouTube. The collected data is analyzed, summarized, and presented to the user's device, highlighting aspects such as positive reviews regarding sound quality and issues with battery life. When the user selects a product they like and presses the purchase button, the server completes the purchase process on the relevant platform and finally displays a purchase completion notification on the device.

[0429] This system allows users to easily overview a vast amount of word-of-mouth information from diverse sources, enabling them to complete purchase procedures quickly and conveniently.

[0430] The following describes the processing flow.

[0431] Step 1:

[0432] The user uses their device to enter the category or specific product name they are looking for and submits a search request. The device then sends the user's needs to the server.

[0433] Step 2:

[0434] The server receives search requests from terminals and analyzes their content. Based on the necessary keywords and category information, it decides which information sources to collect review data from.

[0435] Step 3:

[0436] The server collects relevant user reviews using APIs and scraping techniques from websites, social media, and video sharing platforms. It executes search queries against each information source to retrieve the data.

[0437] Step 4:

[0438] The server organizes the collected data and performs text analysis using natural language processing techniques. This analysis extracts important key phrases from the information and classifies the reviews into positive and negative evaluations.

[0439] Step 5:

[0440] Based on the analysis results, the server summarizes multiple reviews and reconstructs the information in a way that is easy for users to understand. The summary includes information about the product's features, advantages, disadvantages, and user experience.

[0441] Step 6:

[0442] The server sends the generated summary to the terminal. This allows the terminal to display the summary information to the user, enabling the user to evaluate the product in detail.

[0443] Step 7:

[0444] The user reviews the summarized information through their device and selects the products they like. Once they have made their selection, the user sends a purchase instruction from their device to the server to proceed with the purchase.

[0445] Step 8:

[0446] The server receives a purchase instruction from the user and initiates the purchase process on the relevant e-commerce site. It adds items to the cart, processes payment, verifies shipping information, and completes the transaction.

[0447] Step 9:

[0448] After the purchase process is complete, the server sends information to the device indicating that the purchase has been confirmed. The device then displays this notification to the user, providing them with order confirmation.

[0449] (Example 1)

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

[0451] While a vast amount of user reviews exist online, it is extremely difficult for users to efficiently gather this information, summarize it, and understand only the necessary details. Furthermore, with the current situation where the reliability of information and the judgment of positive / negative opinions are left to individual users, it is difficult to obtain the objective information necessary for purchasing decisions. Therefore, there is a need for a system that allows users to easily obtain user reviews from diverse sources, quickly summarize them, and use them to inform their decision-making.

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

[0453] In this invention, the server includes means for receiving search criteria from a communication device, means for collecting data from information provision services and information exchange media, and means for analyzing the collected data using natural language processing technology and generating a summary. This enables users to effectively obtain word-of-mouth information from a wide range of sources and make objective and rapid decisions.

[0454] A "communication device" is a device that allows a user to connect to the internet and send and receive information, and includes smartphones, personal computers, and other similar devices.

[0455] "Search criteria" refer to the conditions and keywords that users enter to specify the information they are looking for, and serve as guidelines for data collection.

[0456] "Information provision services" is a general term for websites and platforms that provide various data and information over the internet.

[0457] An "information exchange medium" refers to a platform where people share information, such as social networking services (SNS) or online forums.

[0458] A "data interface" is a means of connection that enables data communication between a specific web service and an external system, and refers to APIs, etc.

[0459] "Natural language processing technology" is a technology that analyzes human language on a computer and understands its structure and meaning.

[0460] A "summary" is a document that extracts the main points from a large amount of information and presents them concisely.

[0461] An "artificial intelligence model" is a program that uses machine learning and deep learning technologies to think and make decisions like a human.

[0462] An "electronic transaction system" is a system for buying and selling goods via the internet, and includes online shopping platforms, etc.

[0463] The AI ​​agent system for summarizing word-of-mouth information, according to the present invention, operates collaboratively with a user, a terminal, and a server. The user inputs search criteria using a communication device and sends them to the server via the terminal. For example, a specific prompt sentence such as "reputation of sound quality and battery life of wireless headphones" can be sent.

[0464] Based on these search criteria, the server collects data from information provision services and information exchange media. Data collection utilizes the data interfaces provided by each service, such as APIs. The server structures the collected data and analyzes it using natural language processing techniques. Specifically, it uses software such as SpaCy and NLTK to perform morphological analysis and topic extraction of text. It also uses the sentiment analysis tool VADER to identify positive and negative opinions. The analysis results are converted into a summary using a generative AI model. OpenAI's language models and other tools are used to summarize the information in the format desired by the user.

[0465] Next, the server sends the generated summary to the communication device, making it immediately available for the user to view. Based on the presented summary, the user selects products they are interested in. If they find a product they like, the user sends a purchase instruction to the server via their terminal. Based on this instruction, the server automates the purchase process through the electronic transaction system. For example, it adds the product to the cart, enters payment information, and sets up delivery. Once the transaction is complete, the server notifies the user of this information, providing a smooth purchasing experience.

[0466] Thus, the present invention makes it possible to efficiently and quickly acquire and summarize the information that users desire, and to easily guide them toward purchasing products.

[0467] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0468] Step 1:

[0469] The user uses a communication device to enter specific search criteria and send them to the server. These search criteria are expressed as a prompt. For example, the text "Wireless headphone sound quality and battery reputation" is used as input and sent to the server. Specifically, the user enters the prompt in the search bar of their device and presses the "Search" button.

[0470] Step 2:

[0471] The server analyzes the search criteria received from the user and identifies information provision services and information exchange media. The server uses the necessary data interfaces (such as APIs) to access these platforms and collect relevant data. Using the received prompts as input, the server retrieves reviews and testimonials from sources such as Amazon and review sites as output. Specifically, the server sends queries to each platform and stores the returned data.

[0472] Step 3:

[0473] The server structures the collected data and performs text analysis using natural language processing techniques. It uses the collected raw text data as input and generates tagged data identifying positive, negative, and neutral opinions as output. Specifically, the server performs morphological analysis using the SpaCy library and analyzes sentiment using VADER.

[0474] Step 4:

[0475] The server uses a generative AI model to generate summaries from analyzed data. Using tagged, analyzed data as input, it generates easily understandable summary text for the user as output. Specifically, the server uses an OpenAI language model to create the desired summary.

[0476] Step 5:

[0477] The server sends the generated summary to the user's terminal. This is an output process that allows the user to easily access the information. Specifically, the server sends the summary data to the communication device's application, which then displays it on the screen.

[0478] Step 6:

[0479] The user reviews the provided summary on their device and decides to purchase the items they like. The user presses the purchase button to send the purchase instruction to the server. The user's selections and purchase request information are used as input and transmitted to the server. Specifically, the user checks the details of the selected items and clicks the "Purchase" button.

[0480] Step 7:

[0481] The server receives purchase instructions from the user and automates the purchase process through the electronic trading system. The server receives the user's purchase information as input, adds items to the cart, enters payment information, and completes shipping settings. It then sends a purchase completion notification to the user as output. Specifically, the server accesses the API of the relevant trading site, enters the necessary data, and confirms the order.

[0482] (Application Example 1)

[0483] 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."

[0484] On current e-commerce platforms, it is difficult for users to efficiently collect and analyze product reviews in a short amount of time. Furthermore, users often have to go through the entire purchase process from scratch, which is cumbersome and time-consuming. In addition, when making a purchase decision, users need to be presented with reliable and summarized evaluations gathered from various sources.

[0485] 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.

[0486] In this invention, the server includes means for receiving search criteria from a communication device, means for obtaining information from information sources, means for analyzing the obtained information using natural language processing and creating a summary, and means for executing an automated payment procedure using the summary information. This makes it possible to easily aggregate a large amount of word-of-mouth information across diverse information sources and to implement an efficient purchase procedure.

[0487] A "communication device" is an electronic device used by users to search for, receive, and transmit information.

[0488] "Search criteria" refer to the conditions or items that users specify when gathering information.

[0489] An "information source" refers to the place or medium through which information is disseminated, such as a website or a communication platform.

[0490] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language.

[0491] A "summary" is a text that concisely organizes a vast amount of information and extracts the most important points.

[0492] "Payment procedures" refer to the series of operations and processes necessary to pay for purchased goods.

[0493] "Summary information" refers to a summary of information generated through natural language processing.

[0494] "Automated payment processing" refers to a process where the payment procedures required for a purchase are automatically handled by the system.

[0495] This invention relates to a word-of-mouth summary AI agent system that enables users to collect information and efficiently carry out purchase procedures. This system is implemented via the user's communication terminal and a server.

[0496] Users use a communication device to input search criteria for specific products or services. This information is sent to a server. The server executes a Python program to collect reviews and testimonials from various information sources. The application program interface of each information source is used to access it.

[0497] The collected data is analyzed using natural language processing. Specifically, the Hugging Face Transformers library is used, and a generative AI model summarizes the reviews. This summarization process classifies the positive and negative evaluations within the information. The generated summary information is then sent back to the user's communication device and presented in a format that is easily accessible to the user.

[0498] After reviewing ratings and summaries, users select the items they wish to purchase and submit a purchase order through the system. The server then handles the automated payment process via the e-commerce platform. This process allows users to easily complete complex purchase procedures.

[0499] As a concrete example, suppose a user is considering making a reservation at a new cafe. In this case, the user uses their smartphone to search for reviews of cafes and enters a prompt such as, "Please tell me the reviews of recently opened cafes." The server analyzes and summarizes the prompt, ultimately helping the user quickly make a reservation or purchase a coupon for a cafe they are interested in.

[0500] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0501] Step 1:

[0502] The user uses a communication terminal to enter search criteria for a specific product or service and sends them to the server. The entered search criteria might be something like "reviews of the latest wireless headphones." The server receives these search criteria and proceeds to the next processing step based on them.

[0503] Step 2:

[0504] The server executes a program for accessing information sources and retrieves information that matches the specified criteria. Specifically, it uses the application program interface of the information source to collect relevant reviews and comments from review sites and video sharing platforms. The input for this step is the search criteria, and the output is a dataset of the collected information.

[0505] Step 3:

[0506] The server applies natural language processing to analyze the collected data. Using the Hugging Face Transformers library, a generative AI model generates summaries of the reviews. The data is organized based on positive and negative ratings. The input for this step is the collected information dataset, and the output is the summarized information.

[0507] Step 4:

[0508] The server transmits the generated summary information to the communication terminal and presents it to the user. The user reviews the information and makes a selection of products or services. This step is the phase in which the user scrutinizes the displayed information and makes a purchase decision. The input is the summarized information, and the output is the user's selection.

[0509] Step 5:

[0510] After the user selects the items they wish to purchase, they send this information from their communication terminal to the server. The server receives this information and executes an automated payment process through the e-commerce platform. During this process, the necessary payment information is set up by the system, and the transaction is completed. The input for this step is the user's selection information, and the output is a notification that the purchase process is complete.

[0511] Step 6:

[0512] After the server confirms the purchase is complete, it returns that information to the communication terminal and notifies the user. This allows the user to confirm in real time that the purchase was successfully completed. The input is the purchase completion status information, and the output is the notification to the user.

[0513] 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.

[0514] The AI ​​agent system for summarizing user reviews of the present invention, in addition to its basic function of collecting, summarizing, and providing relevant user review information based on search criteria received from the user's communication terminal, incorporates an emotion engine that analyzes the user's emotions, thereby achieving more personalized information delivery. The server first receives search criteria from the terminal and collects information from specified websites and communication platforms. The collected data is analyzed using natural language processing technology, and positive and negative opinions are classified and summarized.

[0515] The emotion engine monitors user operation data, input behavior, operation time, and operation frequency on the user's device to evaluate the user's emotional state in real time. Based on this emotional data, the server adjusts the presentation order of collected word-of-mouth information and has the function of providing optimal information in line with the user's emotions.

[0516] As a concrete example, consider a scenario where a user gathers information about fitness equipment. When the user searches for "treadmill" on their device, the server collects user reviews from Amazon, health information sites, and YouTube. As the user spends more time browsing reviews and moves between pages frequently, the sentiment engine detects positive emotions indicating the user's interest. The server then changes its settings to prioritize displaying positive reviews, personalizing the information gathering experience to make it more enjoyable for the user.

[0517] Furthermore, when a user selects a product, the purchase process in the e-commerce system is expedited, and a notification is displayed on the device upon completion of the purchase. The introduction of an emotion engine allows users to enjoy a more comfortable and effective information gathering and purchasing experience tailored to their individual emotional state.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] The user operates the device, enters a category of product they are interested in or a specific product name, and sends a search request. The device forwards this request to the server.

[0521] Step 2:

[0522] The server receives requests from users and analyzes the search criteria. Based on this analysis, it decides which websites and communication platforms to collect user reviews from.

[0523] Step 3:

[0524] The server accesses the specified information source and collects relevant user reviews using APIs and scraping techniques. It executes queries using search keywords to retrieve data.

[0525] Step 4:

[0526] The server structures the collected data and analyzes the text using natural language processing (NLP) techniques. This process includes extracting key phrases and classifying positive and negative opinions.

[0527] Step 5:

[0528] Based on the analyzed data, the server generates a summary. This summary is structured to include key features, strengths, weaknesses, and the overall user experience.

[0529] Step 6:

[0530] The emotion engine monitors user activity data on the user's device and evaluates the user's emotional state in real time. This evaluation includes user activity time, frequency of page transitions, and input procedures.

[0531] Step 7:

[0532] The server dynamically adjusts the order in which information is presented based on feedback from the emotion engine. Information in which the user has expressed positive emotions is displayed preferentially.

[0533] Step 8:

[0534] The terminal displays summary information received from the server to the user. The user views this information and evaluates the product based on the details.

[0535] Step 9:

[0536] When a user decides to make a purchase, they send a purchase instruction to the server via their device. This instruction is intended to complete the purchase of a specific product or service.

[0537] Step 10:

[0538] The server receives a purchase instruction from the user and initiates the purchase process within the e-commerce system. This includes adding items to the shopping cart, entering payment information, and setting shipping information.

[0539] Step 11:

[0540] Once the purchase process is complete, the server sends a confirmation of the purchase to the device. The device then displays a notification to the user that includes this confirmation.

[0541] (Example 2)

[0542] 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."

[0543] Gathering a large amount of word-of-mouth information from diverse sources and providing information that responds to users' emotional states is technically very complex. Furthermore, systems that provide personalized information based on user emotions have not been effectively implemented with existing technologies. In addition to the sheer volume and variability in quality of information, there are challenges in how to provide information that takes user emotions into account.

[0544] 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.

[0545] In this invention, the server includes means for receiving search conditions, means for collecting information, means for analyzing the information and generating a summary using natural language processing technology, and means for adjusting the order in which information is presented using an emotion engine that evaluates the user's emotional state. This enables the rapid and accurate presentation of information of interest to the user, resulting in a personalized information acquisition experience.

[0546] "Means for receiving search conditions" refers to technical measures that enable the system's server to obtain specific keywords or conditions entered by the user via a communication terminal.

[0547] "Means of information gathering" refers to functions and protocols for collecting data from multiple specified sources and aggregating it on a server.

[0548] "Natural language processing technology" refers to computer processing techniques used to analyze and understand text data, and to classify or summarize information as needed.

[0549] An "emotion engine" is a system component that analyzes user behavior and operation history to detect and evaluate the user's emotional state in real time.

[0550] "Means for adjusting the order in which information is presented" refers to technical measures that have the functionality to arrange and present information to the user in an optimal order based on the user's emotional state and interests.

[0551] "A means of conducting purchase procedures via a transaction system" refers to a mechanism that connects with an e-commerce platform to automatically perform the necessary purchase procedures for the goods or services selected by the user and complete the transaction.

[0552] The system for implementing this invention has functions to analyze text data collected from multiple sources using natural language processing technology, create positive and negative summaries, and optimize information delivery based on the user's emotions.

[0553] First, the user uses a communication device to enter search criteria for a specific product or service. The server immediately receives these search criteria and collects relevant data from multiple sources (e.g., websites and review sites). Web scraping and APIs can be used to efficiently collect diverse data.

[0554] Next, the server performs natural language processing on the collected data. Specifically, it analyzes the information and generates summaries using advanced natural language processing technologies such as Python's NLTK library and Google's BERT model. In this process, it classifies the information into positive and negative evaluations and extracts the key points.

[0555] Furthermore, the user's device is equipped with an emotion engine. This engine monitors user interaction data (click patterns, page dwell time, etc.) and evaluates the user's emotional state in real time. Based on the emotion engine's evaluation, the server adjusts the order in which information is presented, prioritizing information that the user is interested in.

[0556] As a concrete example, consider a scenario where a user is researching fitness equipment. When the user searches for "high-performance treadmill," the server collects and analyzes relevant user reviews and provides a summary tailored to the user's emotional state. For users who spend a long time viewing reviews, the sentiment engine determines that they are interested, and the server prioritizes displaying information with positive reviews.

[0557] The input to the generative AI model will use a specific prompt such as, "Summarize reviews suitable for users considering purchasing fitness equipment, and present them with a priority given to positive reviews."

[0558] In this way, the system enables the provision of information that responds to the user's emotions and can meet diverse needs.

[0559] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0560] Step 1:

[0561] The server receives search criteria entered by the user via a communication terminal. It receives the user-specified keyword (e.g., "treadmill") as input data and functions as a trigger to proceed to the next step. Based on these search criteria, data collection begins from appropriate sources.

[0562] Step 2:

[0563] The server collects data from specified sources. The input is the search criteria received in step 1, and based on this, it retrieves relevant information from websites and databases via crawling or APIs. The output is a collection of raw, collected user reviews. This data collection process utilizes technology to retrieve regularly updated information in real time.

[0564] Step 3:

[0565] The server applies natural language processing to the collected data. It receives the word-of-mouth information obtained in step 2 as input, analyzes the data using Python's NLTK library and Google's BERT model, and generates summaries including positive and negative evaluations. The output is the analyzed summary data, which is then organized into the content presented to the user.

[0566] Step 4:

[0567] The emotion engine, located on the device, monitors user interaction data. Inputs include behavioral data such as user click patterns and page dwell time. The engine analyzes this data and infers the user's emotional state in real time. The output is evaluation data regarding the user's emotional state.

[0568] Step 5:

[0569] The server uses evaluation data from the emotion engine to adjust the order in which information is presented. The inputs here are the summary data from step 3 and the emotion evaluation data from step 4. The server rearranges the information and optimizes it to align with the user's emotions. The output is a set of feedback information to be displayed to the user, which is then sent to the terminal.

[0570] Step 6:

[0571] When a user selects an item, the terminal sends a purchase instruction to the server. The input is the purchase information that the user has confirmed and selected. Based on this, the server calls the transaction system and quickly completes the purchase process. The output is the confirmed purchase information and a purchase completion notification. The server immediately sends this to the terminal to inform the user that the transaction is complete.

[0572] (Application Example 2)

[0573] 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."

[0574] When users gather information or make purchases through communication devices, it is difficult to efficiently obtain relevant information, and in particular, it is difficult to grasp a large amount of word-of-mouth information at once. Furthermore, there is a challenge in providing personalized information because the customization of information based on the user's emotional state is insufficient.

[0575] 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.

[0576] In this invention, the server includes means for receiving search conditions from a communication terminal, means for collecting information from websites and information exchange platforms, means for analyzing the collected information using natural language processing and generating a summary, and means for analyzing the user's emotions and adjusting the order in which the collected information is presented. This enables users to have an efficient and personalized information gathering and purchasing experience that is tailored to their emotional state.

[0577] A "communication terminal" is a device used by a user to perform information processing, and includes smartphones, tablets, and other similar devices.

[0578] "Search criteria" refer to keywords and filtering requirements specified by the user, and relevant information is collected based on these criteria.

[0579] A "website" is a collection of online pages that exist on the internet and provide information.

[0580] An "information exchange platform" is an online service that allows users to exchange information with each other, and includes social networks and messaging applications.

[0581] "Natural language processing" is a technology that enables computers to understand and process human language, making it possible to analyze text and generate summaries.

[0582] A "summary" is a concise explanation that extracts the key points from a large amount of information, enabling users to understand the information efficiently.

[0583] "User emotions" refer to information that indicates the user's psychological state, and are inferred from behavioral data and biosignals.

[0584] "Adjusting the presentation order" refers to changing the display order of information to take into account the user's emotional state and providing personalized information.

[0585] An "electronic commerce system" is a system for buying and selling goods and services online, where the purchase process is automated.

[0586] A "purchase instruction" is an action in which a user expresses their intention to purchase a specific product or service.

[0587] This invention is a system that operates based on data communication between a communication terminal and a server. The user enters search criteria using the communication terminal. These search criteria are sent to the server, which then collects relevant information from specified websites and information exchange platforms. By using multiple data acquisition interfaces, efficient and comprehensive data collection can be achieved.

[0588] The server also uses natural language processing techniques to analyze the collected information and generate a summary. This summary includes positive and negative evaluations, allowing users to concisely understand the overall picture of the information.

[0589] Furthermore, the server analyzes user interaction data to evaluate user emotions in real time. Based on the results of the emotion analysis, it adjusts the presentation order to prioritize information that the user is interested in. This process utilizes machine learning models and is optimized to provide the most relevant information to the user.

[0590] In the purchase flow, when a user indicates a purchase instruction for a product, the server quickly processes the purchase via the e-commerce system. After the purchase is complete, a completion notification is displayed on the communication terminal. This allows users to enjoy a seamless and efficient purchasing experience. Furthermore, it is possible to learn which information the user showed the most interest in and use that information to provide information in the future.

[0591] For example, when a user searches for "treadmill," the server collects reviews from fitness-related review sites and video platforms and generates a summary. If the user's browsing behavior indicates positive emotions, the system is configured to prioritize displaying reviews that have received particularly high ratings. This allows the user to enjoy a more comfortable information gathering experience. Further analysis and customization are possible by utilizing prompts to the generative AI model, such as, "If a user has been browsing treadmill reviews for a long time, they are likely to have positive emotions. Suggest how we can customize the information to encourage purchase based on those emotions."

[0592] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0593] Step 1:

[0594] The user uses a communication terminal to enter search criteria. The entered search criteria are in keyword format and are sent as a request to the server. The server receives this input, parses the search criteria, and prepares for the next step.

[0595] Step 2:

[0596] The server collects information based on the received search criteria through data acquisition interfaces of multiple websites and information exchange platforms. During this process, it uses APIs to gather relevant reviews and testimonials from specified platforms and stores them as text data. This collected text data serves as input for analysis in the next step.

[0597] Step 3:

[0598] The server uses natural language processing technology to analyze the collected text data and generate a summary. This process utilizes a generative AI model to extract key points from the text and classify them into positive and negative opinions. This generates a summary, which is then transformed into a user-friendly format. The generated summary is then used to prepare for presentation in the next step.

[0599] Step 4:

[0600] User operation data from their communication device is sent to the server, where sentiment analysis is performed. The server analyzes the user's operation time, click count, etc., and evaluates the user's emotional state. Based on this evaluation, the server adjusts the order in which it presents information. The results of the sentiment analysis are used to personalize the information presentation and serve as input for setting the priority of the content to be provided next.

[0601] Step 5:

[0602] The server provides the communication terminal with a summary generated in a coordinated order. The user can view and review the information on the communication terminal. This includes priority information that reflects sentiment analysis, providing information tailored to the user. If the user shows interest in a particular product among the displayed information, the system prepares to proceed to the next step.

[0603] Step 6:

[0604] When a user places a purchase order for a product on their device, the order is sent to the server. The server then proceeds with the purchase process via the e-commerce system. During the purchase process, transaction details are processed, a completion notification is generated, and sent to the device. This confirms to the user that the purchase has been completed.

[0605] 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.

[0606] 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.

[0607] 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.

[0608] [Fourth Embodiment]

[0609] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0610] 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.

[0611] 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).

[0612] 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.

[0613] 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.

[0614] 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).

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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.

[0621] 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".

[0622] The AI ​​agent system for summarizing word-of-mouth information according to the present invention is characterized in that, based on search conditions received from the user's communication terminal, the server automatically collects relevant word-of-mouth information from various sources such as websites, social networking services, and video sharing platforms. The server structures the acquired information and generates a summary of the information by analyzing the text using natural language processing (NLP) technology. In this process, positive and negative opinions are identified and a summary is constructed. The generated summary is then sent back to the communication terminal and provided to the user.

[0623] Users can easily view summarized information on their devices and proceed with purchasing items they are interested in. Once a user has made their purchase selection, they send a purchase instruction to the server using their device. Based on this instruction, the server accesses the e-commerce site for the selected items and automatically adds the items to the cart, manages payment information, and sets up shipping information.

[0624] As a concrete example, consider a scenario where a user uses their smartphone to gather information about "wireless headphones." In this case, the user enters search criteria on their device and submits them. The server then collects reviews and user feedback on wireless headphones from sources such as Amazon, iHerb, and YouTube. The collected data is analyzed, summarized, and presented to the user's device, highlighting aspects such as positive reviews regarding sound quality and issues with battery life. When the user selects a product they like and presses the purchase button, the server completes the purchase process on the relevant platform and finally displays a purchase completion notification on the device.

[0625] This system allows users to easily overview a vast amount of word-of-mouth information from diverse sources, enabling them to complete purchase procedures quickly and conveniently.

[0626] The following describes the processing flow.

[0627] Step 1:

[0628] The user uses their device to enter the category or specific product name they are looking for and submits a search request. The device then sends the user's needs to the server.

[0629] Step 2:

[0630] The server receives search requests from terminals and analyzes their content. Based on the necessary keywords and category information, it decides which information sources to collect review data from.

[0631] Step 3:

[0632] The server collects relevant user reviews using APIs and scraping techniques from websites, social media, and video sharing platforms. It executes search queries against each information source to retrieve the data.

[0633] Step 4:

[0634] The server organizes the collected data and performs text analysis using natural language processing techniques. This analysis extracts important key phrases from the information and classifies the reviews into positive and negative evaluations.

[0635] Step 5:

[0636] Based on the analysis results, the server summarizes multiple reviews and reconstructs the information in a way that is easy for users to understand. The summary includes information about the product's features, advantages, disadvantages, and user experience.

[0637] Step 6:

[0638] The server sends the generated summary to the terminal. This allows the terminal to display the summary information to the user, enabling the user to evaluate the product in detail.

[0639] Step 7:

[0640] The user reviews the summarized information through their device and selects the products they like. Once they have made their selection, the user sends a purchase instruction from their device to the server to proceed with the purchase.

[0641] Step 8:

[0642] The server receives a purchase instruction from the user and initiates the purchase process on the relevant e-commerce site. It adds items to the cart, processes payment, verifies shipping information, and completes the transaction.

[0643] Step 9:

[0644] After the purchase process is complete, the server sends information to the device indicating that the purchase has been confirmed. The device then displays this notification to the user, providing them with order confirmation.

[0645] (Example 1)

[0646] 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".

[0647] While a vast amount of user reviews exist online, it is extremely difficult for users to efficiently gather this information, summarize it, and understand only the necessary details. Furthermore, with the current situation where the reliability of information and the judgment of positive / negative opinions are left to individual users, it is difficult to obtain the objective information necessary for purchasing decisions. Therefore, there is a need for a system that allows users to easily obtain user reviews from diverse sources, quickly summarize them, and use them to inform their decision-making.

[0648] 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.

[0649] In this invention, the server includes means for receiving search criteria from a communication device, means for collecting data from information provision services and information exchange media, and means for analyzing the collected data using natural language processing technology and generating a summary. This enables users to effectively obtain word-of-mouth information from a wide range of sources and make objective and rapid decisions.

[0650] A "communication device" is a device that allows a user to connect to the internet and send and receive information, and includes smartphones, personal computers, and other similar devices.

[0651] "Search criteria" refer to the conditions and keywords that users enter to specify the information they are looking for, and serve as guidelines for data collection.

[0652] "Information provision services" is a general term for websites and platforms that provide various data and information over the internet.

[0653] An "information exchange medium" refers to a platform where people share information, such as social networking services (SNS) or online forums.

[0654] A "data interface" is a means of connection that enables data communication between a specific web service and an external system, and refers to APIs, etc.

[0655] "Natural language processing technology" is a technology that analyzes human language on a computer and understands its structure and meaning.

[0656] A "summary" is a document that extracts the main points from a large amount of information and presents them concisely.

[0657] An "artificial intelligence model" is a program that uses machine learning and deep learning technologies to think and make decisions like a human.

[0658] An "electronic transaction system" is a system for buying and selling goods via the internet, and includes online shopping platforms, etc.

[0659] The AI ​​agent system for summarizing word-of-mouth information, according to the present invention, operates collaboratively with a user, a terminal, and a server. The user inputs search criteria using a communication device and sends them to the server via the terminal. For example, a specific prompt sentence such as "reputation of sound quality and battery life of wireless headphones" can be sent.

[0660] Based on these search criteria, the server collects data from information provision services and information exchange media. Data collection utilizes the data interfaces provided by each service, such as APIs. The server structures the collected data and analyzes it using natural language processing techniques. Specifically, it uses software such as SpaCy and NLTK to perform morphological analysis and topic extraction of text. It also uses the sentiment analysis tool VADER to identify positive and negative opinions. The analysis results are converted into a summary using a generative AI model. OpenAI's language models and other tools are used to summarize the information in the format desired by the user.

[0661] Next, the server sends the generated summary to the communication device, making it immediately available for the user to view. Based on the presented summary, the user selects products they are interested in. If they find a product they like, the user sends a purchase instruction to the server via their terminal. Based on this instruction, the server automates the purchase process through the electronic transaction system. For example, it adds the product to the cart, enters payment information, and sets up delivery. Once the transaction is complete, the server notifies the user of this information, providing a smooth purchasing experience.

[0662] Thus, the present invention makes it possible to efficiently and quickly acquire and summarize the information that users desire, and to easily guide them toward purchasing products.

[0663] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0664] Step 1:

[0665] The user uses a communication device to enter specific search criteria and send them to the server. These search criteria are expressed as a prompt. For example, the text "Wireless headphone sound quality and battery reputation" is used as input and sent to the server. Specifically, the user enters the prompt in the search bar of their device and presses the "Search" button.

[0666] Step 2:

[0667] The server analyzes the search criteria received from the user and identifies information provision services and information exchange media. The server uses the necessary data interfaces (such as APIs) to access these platforms and collect relevant data. Using the received prompts as input, the server retrieves reviews and testimonials from sources such as Amazon and review sites as output. Specifically, the server sends queries to each platform and stores the returned data.

[0668] Step 3:

[0669] The server structures the collected data and performs text analysis using natural language processing techniques. It uses the collected raw text data as input and generates tagged data identifying positive, negative, and neutral opinions as output. Specifically, the server performs morphological analysis using the SpaCy library and analyzes sentiment using VADER.

[0670] Step 4:

[0671] The server uses a generative AI model to generate summaries from analyzed data. Using tagged, analyzed data as input, it generates easily understandable summary text for the user as output. Specifically, the server uses an OpenAI language model to create the desired summary.

[0672] Step 5:

[0673] The server sends the generated summary to the user's terminal. This is an output process that allows the user to easily access the information. Specifically, the server sends the summary data to the communication device's application, which then displays it on the screen.

[0674] Step 6:

[0675] The user reviews the provided summary on their device and decides to purchase the items they like. The user presses the purchase button to send the purchase instruction to the server. The user's selections and purchase request information are used as input and transmitted to the server. Specifically, the user checks the details of the selected items and clicks the "Purchase" button.

[0676] Step 7:

[0677] The server receives purchase instructions from the user and automates the purchase process through the electronic trading system. The server receives the user's purchase information as input, adds items to the cart, enters payment information, and completes shipping settings. It then sends a purchase completion notification to the user as output. Specifically, the server accesses the API of the relevant trading site, enters the necessary data, and confirms the order.

[0678] (Application Example 1)

[0679] 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".

[0680] On current e-commerce platforms, it is difficult for users to efficiently collect and analyze product reviews in a short amount of time. Furthermore, users often have to go through the entire purchase process from scratch, which is cumbersome and time-consuming. In addition, when making a purchase decision, users need to be presented with reliable and summarized evaluations gathered from various sources.

[0681] 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.

[0682] In this invention, the server includes means for receiving search criteria from a communication device, means for obtaining information from information sources, means for analyzing the obtained information using natural language processing and creating a summary, and means for executing an automated payment procedure using the summary information. This makes it possible to easily aggregate a large amount of word-of-mouth information across diverse information sources and to implement an efficient purchase procedure.

[0683] A "communication device" is an electronic device used by users to search for, receive, and transmit information.

[0684] "Search criteria" refer to the conditions or items that users specify when gathering information.

[0685] An "information source" refers to the place or medium through which information is disseminated, such as a website or a communication platform.

[0686] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language.

[0687] A "summary" is a text that concisely organizes a vast amount of information and extracts the most important points.

[0688] "Payment procedures" refer to the series of operations and processes necessary to pay for purchased goods.

[0689] "Summary information" refers to a summary of information generated through natural language processing.

[0690] "Automated payment processing" refers to a process where the payment procedures required for a purchase are automatically handled by the system.

[0691] This invention relates to a word-of-mouth summary AI agent system that enables users to collect information and efficiently carry out purchase procedures. This system is implemented via the user's communication terminal and a server.

[0692] Users use a communication device to input search criteria for specific products or services. This information is sent to a server. The server executes a Python program to collect reviews and testimonials from various information sources. The application program interface of each information source is used to access it.

[0693] The collected data is analyzed using natural language processing. Specifically, the Hugging Face Transformers library is used, and a generative AI model summarizes the reviews. This summarization process classifies the positive and negative evaluations within the information. The generated summary information is then sent back to the user's communication device and presented in a format that is easily accessible to the user.

[0694] After reviewing ratings and summaries, users select the items they wish to purchase and submit a purchase order through the system. The server then handles the automated payment process via the e-commerce platform. This process allows users to easily complete complex purchase procedures.

[0695] As a concrete example, suppose a user is considering making a reservation at a new cafe. In this case, the user uses their smartphone to search for reviews of cafes and enters a prompt such as, "Please tell me the reviews of recently opened cafes." The server analyzes and summarizes the prompt, ultimately helping the user quickly make a reservation or purchase a coupon for a cafe they are interested in.

[0696] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0697] Step 1:

[0698] The user uses a communication terminal to enter search criteria for a specific product or service and sends them to the server. The entered search criteria might be something like "reviews of the latest wireless headphones." The server receives these search criteria and proceeds to the next processing step based on them.

[0699] Step 2:

[0700] The server executes a program for accessing information sources and retrieves information that matches the specified criteria. Specifically, it uses the application program interface of the information source to collect relevant reviews and comments from review sites and video sharing platforms. The input for this step is the search criteria, and the output is a dataset of the collected information.

[0701] Step 3:

[0702] The server applies natural language processing to analyze the collected data. Using the Hugging Face Transformers library, a generative AI model generates summaries of the reviews. The data is organized based on positive and negative ratings. The input for this step is the collected information dataset, and the output is the summarized information.

[0703] Step 4:

[0704] The server transmits the generated summary information to the communication terminal and presents it to the user. The user reviews the information and makes a selection of products or services. This step is the phase in which the user scrutinizes the displayed information and makes a purchase decision. The input is the summarized information, and the output is the user's selection.

[0705] Step 5:

[0706] After the user selects the items they wish to purchase, they send this information from their communication terminal to the server. The server receives this information and executes an automated payment process through the e-commerce platform. During this process, the necessary payment information is set up by the system, and the transaction is completed. The input for this step is the user's selection information, and the output is a notification that the purchase process is complete.

[0707] Step 6:

[0708] After the server confirms the purchase is complete, it returns that information to the communication terminal and notifies the user. This allows the user to confirm in real time that the purchase was successfully completed. The input is the purchase completion status information, and the output is the notification to the user.

[0709] 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.

[0710] The AI ​​agent system for summarizing user reviews of the present invention, in addition to its basic function of collecting, summarizing, and providing relevant user review information based on search criteria received from the user's communication terminal, incorporates an emotion engine that analyzes the user's emotions, thereby achieving more personalized information delivery. The server first receives search criteria from the terminal and collects information from specified websites and communication platforms. The collected data is analyzed using natural language processing technology, and positive and negative opinions are classified and summarized.

[0711] The emotion engine monitors user operation data, input behavior, operation time, and operation frequency on the user's device to evaluate the user's emotional state in real time. Based on this emotional data, the server adjusts the presentation order of collected word-of-mouth information and has the function of providing optimal information in line with the user's emotions.

[0712] As a concrete example, consider a scenario where a user gathers information about fitness equipment. When the user searches for "treadmill" on their device, the server collects user reviews from Amazon, health information sites, and YouTube. As the user spends more time browsing reviews and moves between pages frequently, the sentiment engine detects positive emotions indicating the user's interest. The server then changes its settings to prioritize displaying positive reviews, personalizing the information gathering experience to make it more enjoyable for the user.

[0713] Furthermore, when a user selects a product, the purchase process in the e-commerce system is expedited, and a notification is displayed on the device upon completion of the purchase. The introduction of an emotion engine allows users to enjoy a more comfortable and effective information gathering and purchasing experience tailored to their individual emotional state.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] The user operates the device, enters a category of product they are interested in or a specific product name, and sends a search request. The device forwards this request to the server.

[0717] Step 2:

[0718] The server receives requests from users and analyzes the search criteria. Based on this analysis, it decides which websites and communication platforms to collect user reviews from.

[0719] Step 3:

[0720] The server accesses the specified information source and collects relevant user reviews using APIs and scraping techniques. It executes queries using search keywords to retrieve data.

[0721] Step 4:

[0722] The server structures the collected data and analyzes the text using natural language processing (NLP) techniques. This process includes extracting key phrases and classifying positive and negative opinions.

[0723] Step 5:

[0724] Based on the analyzed data, the server generates a summary. This summary is structured to include key features, strengths, weaknesses, and the overall user experience.

[0725] Step 6:

[0726] The emotion engine monitors user activity data on the user's device and evaluates the user's emotional state in real time. This evaluation includes user activity time, frequency of page transitions, and input procedures.

[0727] Step 7:

[0728] The server dynamically adjusts the order in which information is presented based on feedback from the emotion engine. Information in which the user has expressed positive emotions is displayed preferentially.

[0729] Step 8:

[0730] The terminal displays summary information received from the server to the user. The user views this information and evaluates the product based on the details.

[0731] Step 9:

[0732] When a user decides to make a purchase, they send a purchase instruction to the server via their device. This instruction is intended to complete the purchase of a specific product or service.

[0733] Step 10:

[0734] The server receives a purchase instruction from the user and initiates the purchase process within the e-commerce system. This includes adding items to the shopping cart, entering payment information, and setting shipping information.

[0735] Step 11:

[0736] Once the purchase process is complete, the server sends a confirmation of the purchase to the device. The device then displays a notification to the user that includes this confirmation.

[0737] (Example 2)

[0738] 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".

[0739] Gathering a large amount of word-of-mouth information from diverse sources and providing information that responds to users' emotional states is technically very complex. Furthermore, systems that provide personalized information based on user emotions have not been effectively implemented with existing technologies. In addition to the sheer volume and variability in quality of information, there are challenges in how to provide information that takes user emotions into account.

[0740] 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.

[0741] In this invention, the server includes means for receiving search conditions, means for collecting information, means for analyzing the information and generating a summary using natural language processing technology, and means for adjusting the order in which information is presented using an emotion engine that evaluates the user's emotional state. This enables the rapid and accurate presentation of information of interest to the user, resulting in a personalized information acquisition experience.

[0742] "Means for receiving search conditions" refers to technical measures that enable the system's server to obtain specific keywords or conditions entered by the user via a communication terminal.

[0743] "Means of information gathering" refers to functions and protocols for collecting data from multiple specified sources and aggregating it on a server.

[0744] "Natural language processing technology" refers to computer processing techniques used to analyze and understand text data, and to classify or summarize information as needed.

[0745] An "emotion engine" is a system component that analyzes user behavior and operation history to detect and evaluate the user's emotional state in real time.

[0746] "Means for adjusting the order in which information is presented" refers to technical measures that have the functionality to arrange and present information to the user in an optimal order based on the user's emotional state and interests.

[0747] "A means of conducting purchase procedures via a transaction system" refers to a mechanism that connects with an e-commerce platform to automatically perform the necessary purchase procedures for the goods or services selected by the user and complete the transaction.

[0748] The system for implementing this invention has functions to analyze text data collected from multiple sources using natural language processing technology, create positive and negative summaries, and optimize information delivery based on the user's emotions.

[0749] First, the user uses a communication device to enter search criteria for a specific product or service. The server immediately receives these search criteria and collects relevant data from multiple sources (e.g., websites and review sites). Web scraping and APIs can be used to efficiently collect diverse data.

[0750] Next, the server performs natural language processing on the collected data. Specifically, it analyzes the information and generates summaries using advanced natural language processing technologies such as Python's NLTK library and Google's BERT model. In this process, it classifies the information into positive and negative evaluations and extracts the key points.

[0751] Furthermore, the user's device is equipped with an emotion engine. This engine monitors user interaction data (click patterns, page dwell time, etc.) and evaluates the user's emotional state in real time. Based on the emotion engine's evaluation, the server adjusts the order in which information is presented, prioritizing information that the user is interested in.

[0752] As a concrete example, consider a scenario where a user is researching fitness equipment. When the user searches for "high-performance treadmill," the server collects and analyzes relevant user reviews and provides a summary tailored to the user's emotional state. For users who spend a long time viewing reviews, the sentiment engine determines that they are interested, and the server prioritizes displaying information with positive reviews.

[0753] The input to the generative AI model will use a specific prompt such as, "Summarize reviews suitable for users considering purchasing fitness equipment, and present them with a priority given to positive reviews."

[0754] In this way, the system enables the provision of information that responds to the user's emotions and can meet diverse needs.

[0755] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0756] Step 1:

[0757] The server receives search criteria entered by the user via a communication terminal. It receives the user-specified keyword (e.g., "treadmill") as input data and functions as a trigger to proceed to the next step. Based on these search criteria, data collection begins from appropriate sources.

[0758] Step 2:

[0759] The server collects data from specified sources. The input is the search criteria received in step 1, and based on this, it retrieves relevant information from websites and databases via crawling or APIs. The output is a collection of raw, collected user reviews. This data collection process utilizes technology to retrieve regularly updated information in real time.

[0760] Step 3:

[0761] The server applies natural language processing to the collected data. It receives the word-of-mouth information obtained in step 2 as input, analyzes the data using Python's NLTK library and Google's BERT model, and generates summaries including positive and negative evaluations. The output is the analyzed summary data, which is then organized into the content presented to the user.

[0762] Step 4:

[0763] The emotion engine, located on the device, monitors user interaction data. Inputs include behavioral data such as user click patterns and page dwell time. The engine analyzes this data and infers the user's emotional state in real time. The output is evaluation data regarding the user's emotional state.

[0764] Step 5:

[0765] The server uses evaluation data from the emotion engine to adjust the order in which information is presented. The inputs here are the summary data from step 3 and the emotion evaluation data from step 4. The server rearranges the information and optimizes it to align with the user's emotions. The output is a set of feedback information to be displayed to the user, which is then sent to the terminal.

[0766] Step 6:

[0767] When a user selects an item, the terminal sends a purchase instruction to the server. The input is the purchase information that the user has confirmed and selected. Based on this, the server calls the transaction system and quickly completes the purchase process. The output is the confirmed purchase information and a purchase completion notification. The server immediately sends this to the terminal to inform the user that the transaction is complete.

[0768] (Application Example 2)

[0769] 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".

[0770] When users gather information or make purchases through communication devices, it is difficult to efficiently obtain relevant information, and in particular, it is difficult to grasp a large amount of word-of-mouth information at once. Furthermore, there is a challenge in providing personalized information because the customization of information based on the user's emotional state is insufficient.

[0771] 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.

[0772] In this invention, the server includes means for receiving search conditions from a communication terminal, means for collecting information from websites and information exchange platforms, means for analyzing the collected information using natural language processing and generating a summary, and means for analyzing the user's emotions and adjusting the order in which the collected information is presented. This enables users to have an efficient and personalized information gathering and purchasing experience that is tailored to their emotional state.

[0773] A "communication terminal" is a device used by a user to perform information processing, and includes smartphones, tablets, and other similar devices.

[0774] "Search criteria" refer to keywords and filtering requirements specified by the user, and relevant information is collected based on these criteria.

[0775] A "website" is a collection of online pages that exist on the internet and provide information.

[0776] An "information exchange platform" is an online service that allows users to exchange information with each other, and includes social networks and messaging applications.

[0777] "Natural language processing" is a technology that enables computers to understand and process human language, making it possible to analyze text and generate summaries.

[0778] A "summary" is a concise explanation that extracts the key points from a large amount of information, enabling users to understand the information efficiently.

[0779] "User emotions" refer to information that indicates the user's psychological state, and are inferred from behavioral data and biosignals.

[0780] "Adjusting the presentation order" refers to changing the display order of information to take into account the user's emotional state and providing personalized information.

[0781] An "electronic commerce system" is a system for buying and selling goods and services online, where the purchase process is automated.

[0782] A "purchase instruction" is an action in which a user expresses their intention to purchase a specific product or service.

[0783] This invention is a system that operates based on data communication between a communication terminal and a server. The user enters search criteria using the communication terminal. These search criteria are sent to the server, which then collects relevant information from specified websites and information exchange platforms. By using multiple data acquisition interfaces, efficient and comprehensive data collection can be achieved.

[0784] The server also uses natural language processing techniques to analyze the collected information and generate a summary. This summary includes positive and negative evaluations, allowing users to concisely understand the overall picture of the information.

[0785] Furthermore, the server analyzes user interaction data to evaluate user emotions in real time. Based on the results of the emotion analysis, it adjusts the presentation order to prioritize information that the user is interested in. This process utilizes machine learning models and is optimized to provide the most relevant information to the user.

[0786] In the purchase flow, when a user indicates a purchase instruction for a product, the server quickly processes the purchase via the e-commerce system. After the purchase is complete, a completion notification is displayed on the communication terminal. This allows users to enjoy a seamless and efficient purchasing experience. Furthermore, it is possible to learn which information the user showed the most interest in and use that information to provide information in the future.

[0787] For example, when a user searches for "treadmill," the server collects reviews from fitness-related review sites and video platforms and generates a summary. If the user's browsing behavior indicates positive emotions, the system is configured to prioritize displaying reviews that have received particularly high ratings. This allows the user to enjoy a more comfortable information gathering experience. Further analysis and customization are possible by utilizing prompts to the generative AI model, such as, "If a user has been browsing treadmill reviews for a long time, they are likely to have positive emotions. Suggest how we can customize the information to encourage purchase based on those emotions."

[0788] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0789] Step 1:

[0790] The user uses a communication terminal to enter search criteria. The entered search criteria are in keyword format and are sent as a request to the server. The server receives this input, parses the search criteria, and prepares for the next step.

[0791] Step 2:

[0792] The server collects information based on the received search criteria through data acquisition interfaces of multiple websites and information exchange platforms. During this process, it uses APIs to gather relevant reviews and testimonials from specified platforms and stores them as text data. This collected text data serves as input for analysis in the next step.

[0793] Step 3:

[0794] The server uses natural language processing technology to analyze the collected text data and generate a summary. This process utilizes a generative AI model to extract key points from the text and classify them into positive and negative opinions. This generates a summary, which is then transformed into a user-friendly format. The generated summary is then used to prepare for presentation in the next step.

[0795] Step 4:

[0796] User operation data from their communication device is sent to the server, where sentiment analysis is performed. The server analyzes the user's operation time, click count, etc., and evaluates the user's emotional state. Based on this evaluation, the server adjusts the order in which it presents information. The results of the sentiment analysis are used to personalize the information presentation and serve as input for setting the priority of the content to be provided next.

[0797] Step 5:

[0798] The server provides the communication terminal with a summary generated in a coordinated order. The user can view and review the information on the communication terminal. This includes priority information that reflects sentiment analysis, providing information tailored to the user. If the user shows interest in a particular product among the displayed information, the system prepares to proceed to the next step.

[0799] Step 6:

[0800] When a user places a purchase order for a product on their device, the order is sent to the server. The server then proceeds with the purchase process via the e-commerce system. During the purchase process, transaction details are processed, a completion notification is generated, and sent to the device. This confirms to the user that the purchase has been completed.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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."

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] The following is further disclosed regarding the embodiments described above.

[0823] (Claim 1)

[0824] A means of receiving search conditions from a communication terminal,

[0825] Means of collecting information from websites and communication platforms,

[0826] A means for analyzing information collected using natural language processing and generating a summary,

[0827] A means for providing the generated summary to a communication terminal,

[0828] A means of receiving purchase instructions from users and carrying out purchase procedures via an e-commerce system,

[0829] A means of notifying the user of purchase completion information,

[0830] A system that includes this.

[0831] (Claim 2)

[0832] The information gathering means is the system according to claim 1, which acquires information using APIs of multiple websites and communication platforms.

[0833] (Claim 3)

[0834] The system according to claim 1, wherein the means for generating the summary summarizes the information collected using an artificial intelligence model and classifies the information into positive and negative evaluations.

[0835] "Example 1"

[0836] (Claim 1)

[0837] Means for receiving search criteria from a communication device,

[0838] Means for collecting data from information provision services and information exchange media,

[0839] A means for analyzing data collected using natural language processing technology and generating a summary,

[0840] Means for providing the generated summary to a communication device,

[0841] A means of receiving purchase instructions from users and carrying out purchase procedures via an electronic transaction system,

[0842] A means of notifying the user of purchase completion information,

[0843] Means for executing automated trading procedures,

[0844] Means for structuring data,

[0845] A means for identifying and classifying positive and negative evaluations from collected data,

[0846] A method for summarizing data using a generative artificial intelligence model,

[0847] A system that includes this.

[0848] (Claim 2)

[0849] The system according to claim 1, wherein the data collection means acquires data using data interfaces of multiple information provision services and information exchange media.

[0850] (Claim 3)

[0851] The means for generating the summary is the system according to claim 1, which summarizes the data collected using an artificial intelligence model and identifies and classifies positive and negative evaluations of the data.

[0852] "Application Example 1"

[0853] (Claim 1)

[0854] Means for receiving search criteria from a communication device,

[0855] Means for obtaining information from information sources,

[0856] A means of analyzing information obtained using natural language processing and creating a summary,

[0857] Means for providing the created summary to a communication device,

[0858] A means of receiving purchase instructions from users and processing purchases through a commercial transaction platform,

[0859] A means of notifying the user of purchase completion information,

[0860] A means of performing automated payment procedures using summary information,

[0861] A system that includes this.

[0862] (Claim 2)

[0863] The information acquisition means collects information using application program interfaces of multiple information sources, as described in claim 1.

[0864] (Claim 3)

[0865] The means for creating the summary is the system according to claim 1, which summarizes information obtained using a generative AI model and classifies positive and negative evaluations within the information.

[0866] "Example 2 of combining an emotion engine"

[0867] (Claim 1)

[0868] A means of receiving search conditions from a communication terminal,

[0869] Means of gathering information from multiple sources,

[0870] A means for analyzing information collected using natural language processing technology and generating a summary,

[0871] A means for adjusting the order in which information is presented, using an emotion engine that analyzes user operation data to evaluate emotional state,

[0872] A means for providing the generated summary to a communication terminal,

[0873] A means of receiving purchase instructions from users and carrying out purchase procedures through a transaction system,

[0874] A means of notifying the user of purchase completion information,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The information gathering means acquires information using an interface of multiple information sources, as described in claim 1.

[0878] (Claim 3)

[0879] The system according to claim 1, wherein the means for generating the summary includes summarizing information collected using artificial intelligence technology, classifying the information into positive and negative evaluations, and optimizing the order in which the information is presented based on sentiment data.

[0880] "Application example 2 when combining with an emotional engine"

[0881] (Claim 1)

[0882] A means of receiving search conditions from a communication terminal,

[0883] Means of collecting information from websites and information exchange platforms,

[0884] A means for analyzing information collected using natural language processing and generating a summary,

[0885] A means of analyzing user emotions and adjusting the order in which the collected information is presented,

[0886] A means for providing the generated summary to a communication terminal,

[0887] A means of receiving purchase instructions from users and carrying out purchase procedures via an e-commerce system,

[0888] A means of notifying the user of purchase completion information,

[0889] A system that includes this.

[0890] (Claim 2)

[0891] The information gathering means acquires information using data acquisition interfaces of multiple websites and information exchange platforms, as described in claim 1.

[0892] (Claim 3)

[0893] The means for generating the summary is a system according to claim 1, which summarizes information collected using a machine learning model and classifies the information into positive and negative evaluations. [Explanation of Symbols]

[0894] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving search conditions from a communication terminal, Means of collecting information from websites and communication platforms, A means for analyzing information collected using natural language processing and generating a summary, A means for providing the generated summary to a communication terminal, A means of receiving purchase instructions from users and carrying out purchase procedures via an e-commerce system, A means of notifying the user of purchase completion information, A system that includes this.

2. The information gathering means is the system according to claim 1, which acquires information using APIs of multiple websites and communication platforms.

3. The means for generating the summary is the system according to claim 1, which uses an artificial intelligence model to summarize the information collected and classifies the information into positive and negative evaluations.

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