System

Abstract

A system is provided.SOLUTION: This system includes a means for automatically collecting merchandise information from the Internet, a means for arranging the collected merchandise information, and for generating a merchandise comparison table, a means for generating a sentence for introducing the features or advantages of merchandise by using a generation AI model, and a means for displaying contents including the generated sentence and a purchase link.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Manually searching, comparing, and recommending specific products from the vast amount of product information available on the Internet is extremely time-consuming and labor-intensive. This makes it difficult to provide up-to-date information quickly and efficiently. Furthermore, it is necessary to create a flow that allows users to smoothly purchase products by providing purchase links in an automated manner while maintaining the quality of product recommendations. Existing methods make it difficult to efficiently execute this process, and a system that can improve the user experience is needed. [Means for solving the problem]

[0005] The present invention provides a means for automatically collecting product information from the Internet and a means for organizing the collected product information and generating a product comparison table. The above-mentioned problems are solved by providing a system that includes a means for generating text introducing product features and benefits using a generative AI model and a means for displaying content including the generated text and purchase links. Furthermore, by including a means for automatically integrating product introduction text generated using the generative AI model with data on each product, it is possible to enhance the appeal of the product and provide useful information to users. Additionally, the system includes a means for providing an interface that allows users to filter and sort product information, improving user convenience and supporting efficient product selection.

[0006] The "Internet" is a huge computer network system that interconnects computer networks all over the world.

[0007] "Product information" refers to detailed data about a specific product, including multiple attributes such as price, specifications, and user reviews.

[0008] "Collection" refers to the process of obtaining the necessary data from multiple sources on the Internet and inputting it into the system.

[0009] "Organization" refers to the process of converting acquired data into a unified format and making it usable.

[0010] A "product comparison table" is a table that compiles information on multiple products into one easy-to-compare format.

[0011] A "generative AI model" is an algorithm and its implementation that uses artificial intelligence technology to generate useful information or text from data.

[0012] "Product features" refer to the individual attributes of a particular product, such as its unique functions, performance, and design.

[0013] "Advantages" refer to the superiority that a particular product has over other products and the benefits it offers to users.

[0014] A "purchase link" is a web link that allows a user to directly purchase a product and is connected to a specific e-commerce site or affiliate program.

[0015] "Content" is the collection of information displayed on a web page or application, including text, images, links, etc.

[0016] "User" refers to an individual or corporation that uses the system to search for and view product information and make purchases as needed.

[0017] An "interface" is the input / output means and screen display that allow a user to interact with a system.

[0018] "Filtering" is the process of sorting through data based on specific criteria to extract only the information you need.

[0019] "Sorting" is the process of ordering data according to a particular criterion (e.g., by price, by rating). [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] This invention relates to a system for automating the collection, organization, comparison, and introduction of product information from the Internet. This system is composed of a server, terminals, and users.

[0042] The server automatically collects product information from multiple websites and databases, using API calls and web scraping techniques to obtain information such as product names, prices, specifications, user reviews, and images. The server then converts the collected data into a unified format and generates a product comparison table.

[0043] The generated product comparison chart includes product names, prices, key specifications, and user review ratings. The server then uses the generative AI model to generate text that explains the features and benefits of each product, providing users with information in a way that clearly conveys the product's appeal.

[0044] The system uses a device (the user's browser or application) to display information in a way that is easily accessible to the user. The device receives data sent from the server and displays product comparison tables and detailed descriptions. The user can filter and sort the displayed information through the device. For example, they can sort by lowest price or filter by specific specifications.

[0045] As a concrete example, consider the case where a server collects smartphone product information. The server obtains smartphone information from each manufacturer's official website and major e-commerce platforms. Next, it organizes the collected information and compiles a comparison table of smartphone prices, screen sizes, battery capacities, camera resolutions, etc. Then, it uses a generative AI model to generate a description such as, "This smartphone is equipped with a high-resolution camera and can take professional-level photos." Finally, the server automatically generates a purchase link for each product and associates it with each target product.

[0046] When a user accesses the system through a browser, the device displays a comparison chart and introductions of smartphones sent from the server. The user can then select the most suitable smartphone based on this and proceed with the purchase process directly from the displayed purchase link. This process allows users to compare and select products efficiently and quickly, improving the experience leading up to the purchase.

[0047] This system automates the entire process from collecting product information to purchasing, improving user convenience and enabling the rapid provision of the latest information.

[0048] The processing flow will be explained below.

[0049] Program processing steps

[0050] Server-side processing steps

[0051] Step 1:

[0052] The server automatically collects product information from multiple websites and databases on the Internet, specifically using API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images.

[0053] Step 2:

[0054] The server converts the collected product information into a unified format, which involves a data cleaning and normalization process to organize and consolidate data from different sources into a common format.

[0055] Step 3:

[0056] The server generates a product comparison table based on the organized product information. The comparison table includes product names, prices, main specifications, and user reviews, and is organized to allow users to easily compare products.

[0057] Step 4:

[0058] The server uses a generative AI model to generate text that explains the features and benefits of each product. Specifically, product data is input into the AI ​​model, and the model automatically generates text that conveys the product's appeal.

[0059] Step 5:

[0060] The server then integrates the generated product descriptions into the data for each product, thereby creating detailed product information including the descriptions.

[0061] Step 6:

[0062] The server automatically generates a purchase link for each product and adds it to the product data. The purchase link is designed to enable users to quickly purchase the product they are interested in.

[0063] Terminal processing steps

[0064] Step 1:

[0065] The device (user's browser or application) receives the product comparison chart and detailed descriptions sent from the server, parses (analyzes) the received data, and converts it into the format required for display.

[0066] Step 2:

[0067] The device displays product comparison tables and detailed descriptions on web pages and app UIs. Specifically, it uses HTML and CSS to present product information to users in table or list format.

[0068] Step 3:

[0069] The terminal receives user operations (filtering and sorting instructions) and processes the data accordingly. For example, if the user selects "sort by price," the terminal sorts the product data by price and redisplays it.

[0070] User processing steps

[0071] Step 1:

[0072] Users can view a product comparison chart displayed on their device, compare the prices, specifications, and user reviews of each product, and then select the product that best suits their needs.

[0073] Step 2:

[0074] Users check the detailed description of the product they are interested in to better understand its features and benefits. The description clearly describes the product's advantages, which helps them make a purchasing decision.

[0075] Step 3:

[0076] Users click the purchase link to go to the e-commerce site and proceed with the purchase. The purchase link allows users to quickly access the purchase page and smoothly purchase the product.

[0077] Example 1

[0078] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0079] Today, the internet is packed with a vast amount of product information, making it difficult to select the right product. Manually collecting and comparing information is time-consuming and labor-intensive, and there are concerns about the reliability and accuracy of the information. Furthermore, collecting data from diverse websites and converting it into a unified format is technically challenging, and generating appropriate product descriptions requires skill. There is a need for a system that can resolve these issues and provide users with convenient and fast product information.

[0080] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0081] In this invention, the server includes means for automatically collecting product information from the Internet, means for converting the collected product information into a unified format and organizing it, and means for generating a product comparison table, which makes it possible to efficiently compare and organize the collected product information and provide it as useful data to users.

[0082] The system further includes a means for generating text introducing the features and benefits of the product using a generative AI model, and a means for displaying content including the generated text and a purchase link, thereby enabling users to easily understand product information and quickly obtain information for selecting an appropriate product.

[0083] The system also includes a means for providing an interface for users to filter and sort the product information, allowing users to customize the product information to suit their needs and quickly find the products that best suit their needs.

[0084] The "Internet" is a global network for exchanging information, consisting of multiple interconnected computer networks.

[0085] "Product information" refers to detailed data about a specific product, such as the name, price, specifications, user reviews, and images.

[0086] "Means of collection" refers to the technologies and methods used to obtain product information from various websites and databases on the Internet.

[0087] "Means for converting and organizing into a unified format" refers to techniques and methods for converting product information collected in different formats into a consistent format and organizing it in an orderly manner.

[0088] A "product comparison table" is data in a table format that displays multiple product information in a list format that makes it easy to compare them.

[0089] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate text, and is used to generate product descriptions, etc.

[0090] A "purchase link" is a hyperlink to a web page that allows a user to purchase a product.

[0091] "Filtering" is the process of selecting data based on specific conditions.

[0092] "Sorting" is the operation of changing the order of data based on specific criteria.

[0093] An "interface" refers to the means or techniques by which a user interacts with a system, including graphical user interfaces (GUIs).

[0094] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet. The system is composed of a server, terminals, and users, and is described in detail below.

[0095] Server configuration and processing

[0096] The server automatically collects product information from multiple websites and databases using API calls and web scraping techniques, such as issuing HTTP requests and parsing the HTML files or JSON data received as responses to extract product information.

[0097] The server then converts the collected data into a unified format. This conversion process involves normalizing the data, such as unifying different JSON key names and converting price information into a uniform currency unit. For example, all price information obtained from multiple websites can be managed under a unified key called "price" and currency conversion can be performed.

[0098] Based on the organized data, the server generates a product comparison table, which includes product names, prices, key specifications, user reviews, etc. To display the table in a tabular format, an appropriate data structure such as a data frame is used.

[0099] Next, the server uses the generative AI model to generate a product description. By inputting the following prompt into the generative AI model, the server generates a sentence that describes the product's features and benefits.

[0100] Example prompt sentence:

[0101] "Collect and organize smartphone product information, and generate a comparison chart and compelling product descriptions. Required information includes product name, price, specifications, user reviews, and images. Include the features and benefits of each product in the description."

[0102] The generated content, such as a description, a product comparison chart, and a purchase link, is sent to the terminal by the server.

[0103] Terminal configuration and handling

[0104] When a user accesses the system, the terminal receives the data sent from the server. This terminal is the user's browser or application, and displays the received product comparison chart and testimonials in an easy-to-read format.

[0105] Specifically, it uses HTML and CSS to organize the display and provides functions for sorting and filtering products for easy viewing. For example, if a user selects "Price: Ascending," the device will sort the displayed product list from lowest to highest price.

[0106] User operations

[0107] Users can browse, filter, and sort product information through their devices. For example, by filtering by specific specifications, they can display only products that meet their needs. This allows users to quickly find the perfect product.

[0108] Furthermore, the user can click on the displayed purchase link to directly access the purchase page and proceed with the purchase process.

[0109] Specific examples

[0110] For example, when collecting smartphone information, the server retrieves it from each manufacturer's official website and major e-commerce platforms. The collected information is converted into a unified format and a comparison table is compiled of information such as screen size, battery capacity, and camera resolution. The generative AI model is then used to generate a description such as, "This smartphone is equipped with a high-resolution camera and can take professional-quality photos." The server then generates a purchase link for each product and associates it with each target product.

[0111] This system automates the entire process from collecting product information to purchasing, improving user convenience and enabling the prompt provision of the latest information.

[0112] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0113] Step 1: Data collection

[0114] The server automatically collects product information from multiple websites and databases. It uses a list of URLs from each website and database as input. Specifically, the server issues an HTTP request and extracts product information by parsing the HTML file or JSON data received as a response. This process obtains data such as product name, price, specifications, user reviews, and images. The collected raw data is generated as output.

[0115] Step 2: Cleanse and transform the data

[0116] The server converts the collected raw data into a unified format. The raw data obtained in step 1 is used as input. Specific operations include normalizing the data by unifying different JSON key names and converting price information into a single currency unit. For example, "price_usd" and "price_euro" are unified into "price" and converted to USD. Data in a unified format is generated as output.

[0117] Step 3: Generate a product comparison table

[0118] The server generates a product comparison table based on the unified format data. The unified format data generated in step 2 is used as input. Specifically, it organizes product names, prices, key specifications, user review ratings, etc. in a table format. Using an appropriate data structure such as a data frame format makes table generation easy. A product comparison table is generated as output.

[0119] Step 4: Generate a testimonial

[0120] The server uses a generative AI model to generate product descriptions. The input is the data for each product listed in the product comparison chart and a prompt. Specifically, the prompt is input into the generative AI model to generate a description that explains the product's features and benefits. For example, the prompt could be "This smartphone is equipped with a high-resolution camera, allowing you to take professional-quality photos." The output is a description of each product.

[0121] Step 5: Generate a purchase link

[0122] The server automatically generates a purchase link for each product based on links from the collected website or e-commerce platform. The input is the data for each product and the URL template for the purchase page. Specifically, the purchase link is generated by embedding the product ID and parameters in the URL template. For example, a link is generated by embedding the ID "12345" in the template "https: / / example.com / product / {product_id}". The output is a purchase link for each product.

[0123] Step 6: View the data

[0124] When a user accesses the system, the terminal receives the product comparison table, testimonials, and purchase links sent from the server. The data from the server is used as input. Specifically, the terminal uses HTML and CSS to display the received data in an easy-to-read format. For example, the product comparison table is displayed in a table format, with testimonials and purchase links appropriately arranged. As output, the information is displayed on the user's screen.

[0125] Step 7: Filtering and Sorting

[0126] The user can filter and sort product information through the terminal. The input uses the filter and sort conditions selected by the user. Specifically, the terminal dynamically updates the displayed product list using JavaScript (registered trademark) or the like. For example, if the user selects "Price: Ascending", the terminal sorts and displays products in ascending order of price. The output displays the product list filtered and sorted according to the user's selection.

[0127] (Application example 1)

[0128] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0129] There is a need to efficiently collect and organize product information on the Internet and provide users with fast and accurate product comparisons and introductions. With current systems, collecting, organizing, comparing, and introducing this information takes a lot of time and effort, and it is difficult for users to find the information they are looking for. For this reason, it is necessary to automate the process from collecting product information to purchasing, thereby improving user convenience.

[0130] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0131] In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and generating a product comparison table, means for generating text introducing the features and advantages of the products using a generative AI model, means for displaying content including the generated text and purchase links, and means for providing filtering and sorting functions. This allows users to efficiently collect product information and browse the organized product comparison table to quickly compare and select products and choose the most suitable product.

[0132] "On the Internet" refers to websites and online databases accessible via the Internet.

[0133] "Product information" refers to information necessary for consumers to evaluate a product, such as product name, price, specifications, user reviews, images, and purchase links.

[0134] "Automatic collection means" refers to the process of using programs or scripts to obtain product information without human intervention through API calls or web scraping technology.

[0135] "Means for organizing and generating a product comparison table" refers to the process of converting collected product information into a unified format and compiling it into a form that allows the features of multiple products to be compared.

[0136] A "generative AI model" refers to a type of artificial intelligence that uses machine learning techniques to generate text.

[0137] "Means for generating text introducing product features and benefits" refers to the process of using a generative AI model to automatically generate text describing the features and benefits of each product.

[0138] "Generated Text" refers to text describing product features and benefits created using a generative AI model.

[0139] "Content with a purchase link" refers to information that includes a link for users to purchase the product along with generated text and detailed product information.

[0140] "Means for displaying" refers to the method for displaying the collected and organized product information and generated text on the user's device.

[0141] "Means for providing filtering and sorting functionality" refers to functionality that allows users to narrow down product information by criteria such as price or specifications, or sort it in a specific order.

[0142] This invention is a system for automating the collection, organization, comparison, and introduction of product information from the Internet. This system consists of three elements: a server, a terminal, and a user. Each element is described in detail below.

[0143] Users access the system mainly using terminals such as smartphones and personal computers. When a user accesses the system, the terminal sends a request for product information to the server. The server automatically collects product information from various websites and online databases on the Internet.

[0144] The server primarily uses the following hardware and software:

[0145] Hardware: Regular servers (on-premise or cloud-based)

[0146] Software: Node.js, axios, generative AI model (e.g., OpenAI's GPT-3)

[0147] First, the server uses programs and scripts to call APIs and web scraping techniques to collect information such as product names, prices, specifications, user reviews, images, and purchase links. The collected product information is then converted into a unified format within the server. Next, a product comparison table is generated based on this data.

[0148] The server then uses the generative AI model to generate sentences that explain the features and benefits of each product. Specifically, the server provides the following prompt sentences as input to the generative AI model:

[0149] Product name: [Product name]

[0150] Price: [Price]

[0151] Specs: [Specs]

[0152] Review: [Review]

[0153] Image URL: [Image URL]

[0154] Purchase link: [Purchase link]

[0155] Generate a testimonial about the features and benefits of this product.

[0156] For example, a description such as "This smartphone is equipped with a high-resolution camera and can take professional-quality photos" is generated based on the smartphone's information. The generated content, including the purchase link, is then sent to the device.

[0157] The terminal displays the product comparison chart and product descriptions sent from the server to the user. The user can filter and sort products based on the displayed information. This filtering and sorting function allows the user to sort products by lowest price or narrow down products by specific specifications.

[0158] Through the above process, users can efficiently and quickly compare and select products, and choose the most suitable one. This system can greatly improve user convenience by automating the entire process from collecting product information to purchasing.

[0159] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0160] Step 1:

[0161] The server receives product information requests from users. The input is the product information request sent by the user through the terminal. The output is the preparation of product information collection on the Internet based on the request.

[0162] Step 2:

[0163] The server automatically collects product information from various websites and online databases on the Internet. Specifically, it uses programs and scripts to call APIs and web scraping techniques. The input is the URL of the website or database to be collected. The output is the collected raw product information data.

[0164] Step 3:

[0165] The server converts the collected product information into a unified format. Specifically, it organizes the data into the form of product name, price, specifications, user reviews, image URL, purchase link, etc. The input is the collected raw product information data. The output is the product information converted into a unified format.

[0166] Step 4:

[0167] The server generates a product comparison table based on the product information converted into a unified format. The input is formatted product information data. The output is a product comparison table in a format that allows multiple products to be compared.

[0168] Step 5:

[0169] The server uses a generative AI model to generate text that describes the features and benefits of each product. Specific prompts are input to the generative AI model to generate the text. The inputs are detailed information about each product and the following prompts:

[0170] Product name: [Product name]

[0171] Price: [Price]

[0172] Specs: [Specs]

[0173] Review: [Review]

[0174] Image URL: [Image URL]

[0175] Purchase link: [Purchase link]

[0176] Generate a testimonial about the features and benefits of this product.

[0177] The output is a description of the features and benefits of the generated product.

[0178] Step 6:

[0179] The server integrates the generated testimonials and purchase links into a product comparison table and prepares it for transmission to the terminal. The input is the product comparison table, testimonials, and purchase links. The output is the integrated content to be transmitted to the terminal.

[0180] Step 7:

[0181] The terminal displays the product comparison table and product introductions sent from the server to the user. The input is the integrated content sent from the server. The output is the product comparison table and product introductions that the user can view.

[0182] Step 8:

[0183] Users can filter and sort the product information displayed through their devices. The input is the filtering and sorting conditions set by the user. The output is a product comparison table updated based on the conditions.

[0184] Step 9:

[0185] The user can select the most suitable product and proceed with the purchase procedure directly from the purchase link of the selected product. The input is the purchase link of the product selected by the user. The output is a transition to an external site where the purchase procedure is carried out.

[0186] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0187] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet, and aims to realize personalized product recommendations by combining it with an emotion engine that recognizes user emotions. This system is composed of a server, terminals, and users.

[0188] The server automatically collects product information from multiple websites and databases. Specifically, it uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images. The server then converts the collected information into a unified format and generates a product comparison table.

[0189] Next, the server uses the generative AI model to generate text describing the features and benefits of each product, highlighting the product's appeal to users. Furthermore, the server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase the product they're interested in.

[0190] When combined with an emotion engine, the server analyzes the user's facial expressions, voice, input text, etc. to recognize the user's emotions in real time. For example, if the user uses a webcam or microphone, the emotion engine obtains emotional data from the user's facial expressions and tone of voice. It also extracts and analyzes emotions from the text entered by the user. Product information and product descriptions are optimized based on the emotional data recognized by the emotion engine. For example, if the user is excited, it generates text that emphasizes the product's positive features. The emotion engine also integrates the user's purchase history with emotional data to recommend appropriate products.

[0191] The device receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application UI. The device also accepts user operations (filtering and sorting instructions) and performs corresponding data processing. For example, if the user selects "sort by price," the device sorts the product data by price and redisplays it. Furthermore, the device displays product recommendations suitable for the user based on the emotion data acquired by the emotion engine.

[0192] Users can view a product comparison chart displayed on their device to select the product that best suits them. They can also review the product details to understand the product's features and benefits. Recommendations based on the user's emotions allow for more personalized product selection. Finally, they can quickly purchase the product by clicking the purchase link.

[0193] As a specific example, when a user uses this system on a device with a webcam, the emotion engine recognizes emotions such as joy, excitement, and interest from the user's facial expressions. For example, if the user is smiling while browsing a product, the system generates a description that emphasizes the product's positive features. Conversely, if the user looks confused, the system displays detailed specifications and FAQ links to resolve the user's questions. This provides users with appropriate information tailored to their emotional state, making it easier for them to select the most suitable product.

[0194] This system not only automates the entire process from collecting product information to purchasing, but also takes user emotions into account to provide a richer and more personalized purchasing experience.

[0195] The processing flow will be explained below.

[0196] Program processing steps

[0197] Server-side processing steps

[0198] Step 1:

[0199] The server uses designated API endpoints and web scraping technology to collect product information from multiple sources on the Internet, including product names, prices, specifications, user reviews, and images.

[0200] Step 2:

[0201] The server converts the collected product information into a unified format, which includes data cleaning and normalization to ensure data from different sources is in a consistent format.

[0202] Step 3:

[0203] The server uses the organized product information to generate a product comparison table, which includes product names, prices, key specifications, and user reviews, and is organized to allow users to easily compare products.

[0204] Step 4:

[0205] The server uses the generative AI model to generate text that explains the features and benefits of each product. Specifically, it inputs product data into the AI ​​model and automatically generates an introductory text that conveys the product's appeal.

[0206] Step 5:

[0207] The server integrates the generated product description text into the data for each product, thereby adding the description text to the product data as detailed product information.

[0208] Step 6:

[0209] The server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase products they are interested in.

[0210] Step 7:

[0211] The server uses an emotion engine to analyze the user's facial expressions, voice, input text, etc. to recognize the user's emotions in real time, and optimizes product information and introductory text based on the emotion data.

[0212] Terminal processing steps

[0213] Step 1:

[0214] The device (user's browser or application) receives the product comparison chart, detailed descriptions, and purchase links sent from the server, analyzes the received data, and converts it into the format required for display.

[0215] Step 2:

[0216] The device displays product comparison tables and detailed descriptions as the UI of a web page or application. Specifically, it uses HTML and CSS to present product information to the user in a table or list format.

[0217] Step 3:

[0218] The terminal accepts user operations (filtering and sorting instructions) and performs the corresponding data processing. For example, if the user selects "sort by price," the terminal sorts the product data by price and redisplays it.

[0219] Step 4:

[0220] The device transmits the user's facial expressions and voice to an emotion engine that analyzes the user's emotions in real time. For example, it analyzes data acquired through a webcam or microphone to recognize the user's emotional state.

[0221] Step 5:

[0222] The device will then display appropriate product recommendations based on the recognized emotion data, emphasizing the positive aspects if the user is excited and providing detailed explanations if the user is confused.

[0223] User processing steps

[0224] Step 1:

[0225] Users can view a product comparison chart displayed on their device, compare the prices, specifications, and user reviews of each product, and consider which product best suits their needs.

[0226] Step 2:

[0227] The user checks the detailed product description displayed on the device to deepen their understanding of the product's features and advantages, for example, by referring to the product's advantages and unique features.

[0228] Step 3:

[0229] The user clicks on the purchase link and is taken to the e-commerce site, where they can proceed with the purchase. The purchase link takes the user directly to the purchase page, allowing for quick purchases.

[0230] Step 4:

[0231] Users can continue to check the details of the products they are interested in and, if necessary, refer to additional information and product recommendations provided by the emotion engine. The emotion engine analyzes the user's real-time emotional state and provides personalized information, making the purchasing experience richer and more efficient.

[0232] This system automates the entire process from collecting product information to making a purchase, and by taking into account the user's emotions, it is possible to provide a more personalized purchasing experience.

[0233] Example 2

[0234] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0235] Conventional online shopping systems have limitations in their functionality for aggregating and comparing information on products that users are interested in. In addition, product descriptions are standardized and lack personalization based on individual users' preferences and emotions. This has led to problems such as users being unable to select the most suitable product, which reduces their motivation to purchase.

[0236] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0237] In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and converting it into a unified format, means for generating a product comparison table, means for generating text introducing the features and advantages of products using a generative AI model, means for displaying content including the generated text and purchase links, means for analyzing user emotions in real time, and means for presenting optimal product information based on the emotion data, thereby enabling the provision of personalized product information for users and efficient product selection.

[0238] The "Internet" is a global information and communications network that connects computer networks around the world.

[0239] "Product information" refers to data about the characteristics and features of a product, such as the product name, price, specifications, user reviews, and images.

[0240] "Collection" is the process of obtaining and gathering specific information.

[0241] "Organization" is the process of arranging acquired data based on certain rules and standards to make it easier to view and use.

[0242] A "uniform format" is a method for aligning information into a certain format or structure.

[0243] A "product comparison table" is a table that displays the characteristics of multiple products in a list format to make it easier to compare them.

[0244] A "generative AI model" is a computational method or model that uses artificial intelligence techniques to automatically perform specific tasks.

[0245] "Sentence generation" is the process by which a computer automatically creates text using natural language.

[0246] A "purchase link" is a web link that a user can click to purchase an item.

[0247] "Content" is a general term for information displayed on a web page or application.

[0248] "Display" is the process of visually presenting information to a user.

[0249] "Real-time emotion analysis" is the process of analyzing a user's facial expressions, voice, text, etc. in real time to detect their emotional state.

[0250] "Emotion data" is information relating to the user's emotional state.

[0251] "Presenting optimal product information" is the process of suggesting the most suitable product information for the user based on the user's emotional state and other data.

[0252] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet. Furthermore, by combining it with an emotion engine that recognizes user emotions, it aims to realize personalized product recommendations. This system consists of a server, a terminal, and a user.

[0253] The server automatically collects product information from multiple websites and databases. Specifically, it uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images. For example, when collecting product information from Amazon or Rakuten Ichiba, the server uses those APIs. The collected information is converted into a unified format on the server side. This unifies the different data formats from each site and ensures data consistency.

[0254] Next, the server generates a product comparison table based on the product information converted into a unified format. This comparison table displays each product's price, specifications, user reviews, and other information in a list format. The server then uses a generative AI model to generate text that explains the features and benefits of each product. To do this, it issues a prompt to the generative AI model. As a concrete example, the prompt used is, "Generate a text that introduces the benefits of the latest smartphone."

[0255] In addition, the server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase products they are interested in. Using an emotion engine, the server analyzes the user's facial expressions, voice, and input text to obtain emotional data in real time. If the user is using a webcam or microphone, the emotion engine analyzes emotions from the user's facial expressions and tone of voice. Based on this emotional data, the server presents optimal product information.

[0256] The terminal receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application user interface. Furthermore, the terminal can redisplay the product data in response to user operations (filtering or sorting instructions). For example, if the user selects "sort by price," the terminal sorts and redisplays the product data in price order. In addition, the terminal displays recommended products that are most suitable for the user based on the emotion data acquired by the emotion engine.

[0257] Users can view a product comparison chart displayed on their device to select the product that best suits them. They can then review the product details to understand the product's features and benefits. Recommendation information based on emotional data is provided, enabling a more personalized product selection. Finally, users can quickly purchase the product by clicking the purchase link for the product that interests them.

[0258] As a concrete example, when a user uses this system with a device equipped with a webcam, the emotion engine recognizes the user's emotions from their facial expressions. For example, if the user is smiling while browsing a product, the system generates a description that emphasizes the product's positive features. Conversely, if the user looks confused, the system displays detailed specifications and FAQ links to resolve the user's questions.

[0259] This system automates the entire process from collecting product information to purchasing, and makes it possible to provide a personalized purchasing experience that takes user emotions into consideration.

[0260] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0261] Step 1:

[0262] The server collects product information from multiple websites and databases on the Internet. Specifically, it uses API calls and web scraping technology. For example, the server retrieves data such as product names, prices, specifications, user reviews, and images from specific websites. The input is raw data from websites and databases, and the output is the collected raw product information data.

[0263] Step 2:

[0264] The server organizes the collected product information and converts it into a unified format. Specifically, it parses different data formats (e.g., JSON, HTML) and converts them into a consistent format (e.g., CSV, database entries). It also cleans up missing values ​​and duplicate data. The input is the raw data of the collected product information, and the output is the product information converted into a unified format.

[0265] Step 3:

[0266] The server generates a product comparison table based on the product information converted into a unified format. Specifically, it creates a table that displays information such as the price, specifications, and user reviews of each product in a list format. This table is generated in Excel file or HTML format. The input is the product information converted into a unified format, and the output is a product comparison table.

[0267] Step 4:

[0268] The server uses the generative AI model to generate sentences that explain the features and benefits of each product. Specifically, it issues a prompt to the generative AI model: "Generate a sentence that introduces the benefits of the latest smartphone." The generated sentences are saved in JSON format. The inputs are the prompt and product information, and the output is the generated product description sentence.

[0269] Step 5:

[0270] The server uses an affiliate program to automatically generate a purchase link for each product. Specifically, it accesses the affiliate programs of Amazon and Rakuten Ichiba and obtains the URL for each product. This is then added to the product data. The input is product information and data from the affiliate program, and the output is the product data with the product purchase link added.

[0271] Step 6:

[0272] The server uses the emotion engine to analyze the user's facial expressions, voice, and input text to obtain emotion data. Specifically, when the user uses a webcam or microphone, the emotion engine analyzes the user's facial expressions and tone of voice in real time. The input is the user's facial expressions, voice, and input text, and the output is emotion data.

[0273] Step 7:

[0274] The device receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application user interface. Furthermore, the device redisplays the product data in response to user operations (filtering and sorting instructions). The input is data from the server and user operations, and the output is the product data displayed in the updated UI.

[0275] Step 8:

[0276] The user looks at the product comparison table displayed on the device and selects the product that best suits them. They check the product details and understand the product's features and benefits. They click on the purchase link for the product that interests them and quickly purchase the product. The input is the displayed product data, and the output is the user's selection and purchase operation.

[0277] (Application example 2)

[0278] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0279] Conventional online shopping sites and advertising systems provide uniform information without considering the user's feelings, making it difficult to recommend optimal products for the user and failing to fully stimulate purchasing motivation. In addition, providing a large amount of information at once confuses the user, making it take a long time to find the optimal product.

[0280] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and generating a product comparison table, means for generating text introducing product features and advantages using a generative AI model, means for recognizing user emotions and optimizing product information and introduction text based on the emotions, and means for displaying content including the generated text and purchase links. This allows users to receive personalized product recommendations in a more emotionally satisfying manner, increasing their desire to purchase and enabling them to find the best product efficiently and quickly.

[0281] "Means for automatically collecting product information from the Internet" refers to a function that uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images from multiple websites and databases.

[0282] The "means for organizing collected product information and generating a product comparison table" is a function that converts collected product information into a unified format and creates a product comparison table organized in an easy-to-compare format.

[0283] "Means for generating text introducing the features and benefits of a product using a generative AI model" refers to a function that uses a generative AI model to generate natural language text to explain the features and benefits of a product based on collected and organized product information.

[0284] "Means for recognizing the user's emotions and optimizing product information and descriptions based on those emotions" refers to a function that analyzes emotions from the user's facial expressions, voice, input text, etc., and optimizes product information and descriptions based on that emotional data.

[0285] The "means for displaying the content including the generated text and the purchase link" is an interface having a function for displaying the content including the generated text and the purchase link to the user.

[0286] This invention is a system that automatically collects product information from the Internet and provides personalized product recommendations using an emotion engine. This system is composed of a server, terminals, and users.

[0287] Server Roles

[0288] The server has the following main functions:

[0289] 1. Collecting product information:

[0290] The server uses API calls and web scraping technology to automatically collect data such as product names, prices, specifications, user reviews, and images from multiple websites and databases.

[0291] The collected information is stored in a database.

[0292] 2. Organizing product information and generating product comparison tables:

[0293] The collected product information is converted into a unified format and a product comparison table is generated.

[0294] 3. Generating introductory text using a generative AI model:

[0295] Using a generative AI model, text introducing product features and benefits is generated based on collected and organized data.

[0296] The generated text is automatically integrated with the data for each product.

[0297] 4. Use of Emotion Engine:

[0298] The server analyzes the user's facial expressions, voice, input text, etc., and recognizes the user's emotions in real time.

[0299] If the user is excited, it generates text that emphasizes the product's positive features, and if the user is confused, it displays detailed specifications and FAQ links.

[0300] Device Role

[0301] The device provides the user with the information sent by the server:

[0302] 1. Displaying information:

[0303] Show users a product comparison chart, detailed descriptions, and purchase links.

[0304] To display product recommendation information optimized based on a user's emotions.

[0305] 2. Accepting user operations:

[0306] It provides an interface for users to filter and sort product information and responds to user actions.

[0307] User Roles

[0308] Users receive information based on their emotions and make purchasing decisions:

[0309] 1. Check and compare information:

[0310] The user checks the product comparison chart displayed on the device and understands the features and advantages of the products.

[0311] 2. Purchasing behavior:

[0312] The user selects the most suitable product and purchases it by clicking the purchase link.

[0313] Hardware and software used

[0314] Hardware:

[0315] Smartphone (with camera and microphone)

[0316] software:

[0317] Frontend: React Native

[0318] Backend: Node.js + Express

[0319] Database: MongoDB

[0320] Emotion Recognition API: General facial recognition and voice analysis API

[0321] Generative AI Model: A general generative AI model

[0322] Specific examples

[0323] If a user smiles excitedly while browsing products in the gadget category, the emotion engine recognizes this smile and sends it to the server as an "excited" state. The server then receives this data and generates a prompt for the generative AI model, which then generates a positive description such as, "This gadget is equipped with the latest technology, has amazing performance, and is especially recommended for game enthusiasts!" and displays it on the device.

[0324] Prompt Sentence Examples

[0325] The user is browsing products in the Gadgets category. Their current emotion is "Excited." Generate a description that highlights the positive features of the following product:

[0326] Product Name: Smart Watch Pro

[0327] Price: 25,000 yen

[0328] Specifications: Built-in GPS, waterproof, long battery life

[0329] User review: "Very easy to use!"

[0330] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0331] Step 1: Gather product information

[0332] The server automatically collects data such as product name, price, specifications, user reviews, and images from multiple websites and databases on the Internet using API calls and web scraping technology. This data is then temporarily stored in a database on the server. The input is the website URL or API endpoint, and the output is the raw data of the retrieved product information.

[0333] Step 2: Organize product information and generate a product comparison table

[0334] The server converts the collected product information into a unified format and generates a product comparison table. Here, data cleansing and normalization are performed to make it easier for users to compare. The input is the collected raw product information data, and the output is a comparison table in a unified format.

[0335] Step 3: Generate an introduction

[0336] The server uses a generative AI model to generate text introducing the product's features and benefits based on the collected and organized data. The generated text is automatically integrated with the data for each product. The input is organized product information and a product comparison table, and the output is a text created by the generative AI model that explains the product's features.

[0337] Step 4: Real-time emotion recognition

[0338] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice. The emotion recognition API analyzes the user's emotions from this data and obtains emotional data in real time. The input is the captured image and audio, and the output is the analyzed emotional data.

[0339] Step 5: Optimize your text based on sentiment

[0340] The server uses the emotion data obtained from the emotion recognition API to optimize the generated product description. For example, if the user is excited, it generates a description that emphasizes the product's positive features. The input is the emotion data and the generated description, and the output is the optimized description.

[0341] Step 6: Displaying Content

[0342] The terminal displays the generated content to the user, such as a product comparison chart, detailed descriptions, and purchase links. The input is the optimized text and other product data sent from the server, and the output is the content displayed on the user's screen.

[0343] Step 7: Accepting user actions

[0344] The terminal provides an interface for users to filter and sort product information, accepts user operations, and updates the display based on the user operations. The input is the filter and sort conditions provided by the user, and the output is the updated product information after filtering and sorting.

[0345] Step 8: Making a purchase

[0346] Based on the optimized information displayed on the device, the user clicks on the purchase link to purchase the product. The input is the displayed product information and the purchase link, and the output is the user's purchasing behavior after going through the purchasing process.

[0347] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0348] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0349] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0350] [Second embodiment]

[0351] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0352] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0353] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0354] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0355] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0356] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0357] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0358] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0359] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0360] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0361] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0362] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0363] This invention relates to a system for automating the collection, organization, comparison, and introduction of product information from the Internet. This system is composed of a server, terminals, and users.

[0364] The server automatically collects product information from multiple websites and databases, using API calls and web scraping techniques to obtain information such as product names, prices, specifications, user reviews, and images. The server then converts the collected data into a unified format and generates a product comparison table.

[0365] The generated product comparison chart includes product names, prices, key specifications, and user review ratings. The server then uses the generative AI model to generate text that explains the features and benefits of each product, providing users with information in a way that clearly conveys the product's appeal.

[0366] The system uses a device (the user's browser or application) to display information in a way that is easily accessible to the user. The device receives data sent from the server and displays product comparison tables and detailed descriptions. The user can filter and sort the displayed information through the device. For example, they can sort by lowest price or filter by specific specifications.

[0367] As a concrete example, consider the case where a server collects smartphone product information. The server obtains smartphone information from each manufacturer's official website and major e-commerce platforms. Next, it organizes the collected information and compiles a comparison table of smartphone prices, screen sizes, battery capacities, camera resolutions, etc. Then, it uses a generative AI model to generate a description such as, "This smartphone is equipped with a high-resolution camera and can take professional-level photos." Finally, the server automatically generates a purchase link for each product and associates it with each target product.

[0368] When a user accesses the system through a browser, the device displays a comparison chart and introductions of smartphones sent from the server. The user can then select the most suitable smartphone based on this and proceed with the purchase process directly from the displayed purchase link. This process allows users to compare and select products efficiently and quickly, improving the experience leading up to the purchase.

[0369] This system automates the entire process from collecting product information to purchasing, improving user convenience and enabling the rapid provision of the latest information.

[0370] The processing flow will be explained below.

[0371] Program processing steps

[0372] Server-side processing steps

[0373] Step 1:

[0374] The server automatically collects product information from multiple websites and databases on the Internet, specifically using API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images.

[0375] Step 2:

[0376] The server converts the collected product information into a unified format, which involves a data cleaning and normalization process to organize and consolidate data from different sources into a common format.

[0377] Step 3:

[0378] The server generates a product comparison table based on the organized product information. The comparison table includes product names, prices, main specifications, and user reviews, and is organized to allow users to easily compare products.

[0379] Step 4:

[0380] The server uses a generative AI model to generate text that explains the features and benefits of each product. Specifically, product data is input into the AI ​​model, and the model automatically generates text that conveys the product's appeal.

[0381] Step 5:

[0382] The server then integrates the generated product descriptions into the data for each product, thereby creating detailed product information including the descriptions.

[0383] Step 6:

[0384] The server automatically generates a purchase link for each product and adds it to the product data. The purchase link is designed to enable users to quickly purchase the product they are interested in.

[0385] Terminal processing steps

[0386] Step 1:

[0387] The device (user's browser or application) receives the product comparison chart and detailed descriptions sent from the server, parses (analyzes) the received data, and converts it into the format required for display.

[0388] Step 2:

[0389] The device displays product comparison tables and detailed descriptions on web pages and app UIs. Specifically, it uses HTML and CSS to present product information to users in table or list format.

[0390] Step 3:

[0391] The terminal receives user operations (filtering and sorting instructions) and processes the data accordingly. For example, if the user selects "sort by price," the terminal sorts the product data by price and redisplays it.

[0392] User processing steps

[0393] Step 1:

[0394] Users can view a product comparison chart displayed on their device, compare the prices, specifications, and user reviews of each product, and then select the product that best suits their needs.

[0395] Step 2:

[0396] Users check the detailed description of the product they are interested in to better understand its features and benefits. The description clearly describes the product's advantages, which helps them make a purchasing decision.

[0397] Step 3:

[0398] Users click the purchase link to go to the e-commerce site and proceed with the purchase. The purchase link allows users to quickly access the purchase page and smoothly purchase the product.

[0399] Example 1

[0400] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0401] Today, the internet is packed with a vast amount of product information, making it difficult to select the right product. Manually collecting and comparing information is time-consuming and labor-intensive, and there are concerns about the reliability and accuracy of the information. Furthermore, collecting data from diverse websites and converting it into a unified format is technically challenging, and generating appropriate product descriptions requires skill. There is a need for a system that can resolve these issues and provide users with convenient and fast product information.

[0402] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0403] In this invention, the server includes means for automatically collecting product information from the Internet, means for converting the collected product information into a unified format and organizing it, and means for generating a product comparison table, which makes it possible to efficiently compare and organize the collected product information and provide it as useful data to users.

[0404] The system further includes a means for generating text introducing the features and benefits of the product using a generative AI model, and a means for displaying content including the generated text and a purchase link, thereby enabling users to easily understand product information and quickly obtain information for selecting an appropriate product.

[0405] The system also includes a means for providing an interface for users to filter and sort the product information, allowing users to customize the product information to suit their needs and quickly find the products that best suit their needs.

[0406] The "Internet" is a global network for exchanging information, consisting of multiple interconnected computer networks.

[0407] "Product information" refers to detailed data about a specific product, such as the name, price, specifications, user reviews, and images.

[0408] "Means of collection" refers to the technologies and methods used to obtain product information from various websites and databases on the Internet.

[0409] "Means for converting and organizing into a unified format" refers to techniques and methods for converting product information collected in different formats into a consistent format and organizing it in an orderly manner.

[0410] A "product comparison table" is data in a table format that displays multiple product information in a list format that makes it easy to compare them.

[0411] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate text, and is used to generate product descriptions, etc.

[0412] A "purchase link" is a hyperlink to a web page that allows a user to purchase a product.

[0413] "Filtering" is the process of selecting data based on specific conditions.

[0414] "Sorting" is the operation of changing the order of data based on specific criteria.

[0415] An "interface" refers to the means or techniques by which a user interacts with a system, including graphical user interfaces (GUIs).

[0416] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet. The system is composed of a server, terminals, and users, and is described in detail below.

[0417] Server configuration and processing

[0418] The server automatically collects product information from multiple websites and databases using API calls and web scraping techniques, such as issuing HTTP requests and parsing the HTML files or JSON data received as responses to extract product information.

[0419] The server then converts the collected data into a unified format. This conversion process involves normalizing the data, such as unifying different JSON key names and converting price information into a uniform currency unit. For example, all price information obtained from multiple websites can be managed under a unified key called "price" and currency conversion can be performed.

[0420] Based on the organized data, the server generates a product comparison table, which includes product names, prices, key specifications, user reviews, etc. To display the table in a tabular format, an appropriate data structure such as a data frame is used.

[0421] Next, the server uses the generative AI model to generate a product description. By inputting the following prompt into the generative AI model, it generates a sentence that explains the product's features and benefits.

[0422] Example prompt sentence:

[0423] "Collect and organize smartphone product information, and generate a comparison chart and compelling product descriptions. Required information includes product name, price, specifications, user reviews, and images. Include the features and benefits of each product in the description."

[0424] The generated content, such as a description, a product comparison chart, and a purchase link, is sent to the terminal by the server.

[0425] Terminal configuration and handling

[0426] When a user accesses the system, the terminal receives the data sent from the server. This terminal is the user's browser or application, and displays the received product comparison chart and testimonials in an easy-to-read format.

[0427] Specifically, it uses HTML and CSS to organize the display and provides functions for sorting and filtering products for easy viewing. For example, if a user selects "Price: Ascending," the device will sort the displayed product list from lowest to highest price.

[0428] User operations

[0429] Users can browse, filter, and sort product information through their devices. For example, by filtering by specific specifications, they can display only products that meet their needs. This allows users to quickly find the perfect product.

[0430] Furthermore, the user can click on the displayed purchase link to directly access the purchase page and proceed with the purchase process.

[0431] Specific examples

[0432] For example, when collecting smartphone information, the server retrieves it from each manufacturer's official website and major e-commerce platforms. The collected information is converted into a unified format and a comparison table is compiled of information such as screen size, battery capacity, and camera resolution. The generative AI model is then used to generate a description such as, "This smartphone is equipped with a high-resolution camera and can take professional-quality photos." The server then generates a purchase link for each product and associates it with each target product.

[0433] This system automates the entire process from collecting product information to purchasing, improving user convenience and enabling the prompt provision of the latest information.

[0434] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0435] Step 1: Data collection

[0436] The server automatically collects product information from multiple websites and databases. It uses a list of URLs from each website and database as input. Specifically, the server issues an HTTP request and extracts product information by parsing the HTML file or JSON data received as a response. This process obtains data such as product name, price, specifications, user reviews, and images. The collected raw data is generated as output.

[0437] Step 2: Cleanse and transform the data

[0438] The server converts the collected raw data into a unified format. The raw data obtained in step 1 is used as input. Specific operations include normalizing the data by unifying different JSON key names and converting price information into a single currency unit. For example, "price_usd" and "price_euro" are unified into "price" and converted to USD. Data in a unified format is generated as output.

[0439] Step 3: Generate a product comparison table

[0440] The server generates a product comparison table based on the unified format data. The unified format data generated in step 2 is used as input. Specifically, it organizes product names, prices, key specifications, user review ratings, etc. in a table format. Using an appropriate data structure such as a data frame format makes table generation easy. A product comparison table is generated as output.

[0441] Step 4: Generate a testimonial

[0442] The server uses a generative AI model to generate product descriptions. The input is the data for each product listed in the product comparison chart and a prompt. Specifically, the prompt is input into the generative AI model to generate a description that explains the product's features and benefits. For example, the prompt could be "This smartphone is equipped with a high-resolution camera, allowing you to take professional-quality photos." The output is a description of each product.

[0443] Step 5: Generate a purchase link

[0444] The server automatically generates a purchase link for each product based on links from the collected website or e-commerce platform. The input is the data for each product and the URL template for the purchase page. Specifically, the purchase link is generated by embedding the product ID and parameters in the URL template. For example, a link is generated by embedding the ID "12345" in the template "https: / / example.com / product / {product_id}". The output is a purchase link for each product.

[0445] Step 6: View the data

[0446] When a user accesses the system, the terminal receives the product comparison table, testimonials, and purchase links sent from the server. The data from the server is used as input. Specifically, the terminal uses HTML and CSS to display the received data in an easy-to-read format. For example, the product comparison table is displayed in a table format, with testimonials and purchase links appropriately arranged. As output, the information is displayed on the user's screen.

[0447] Step 7: Filtering and Sorting

[0448] The user can filter and sort product information through the terminal. The filter and sort conditions selected by the user are used as input. Specifically, the terminal dynamically updates the displayed product list using JavaScript or other methods. For example, if the user selects "Price: Ascending", the terminal sorts and displays products in ascending order of price. The output displays a product list filtered and sorted according to the user's selection.

[0449] (Application example 1)

[0450] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0451] There is a need to efficiently collect and organize product information on the Internet and provide users with fast and accurate product comparisons and introductions. With current systems, collecting, organizing, comparing, and introducing this information takes a lot of time and effort, and it is difficult for users to find the information they are looking for. For this reason, it is necessary to automate the process from collecting product information to purchasing, thereby improving user convenience.

[0452] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0453] In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and generating a product comparison table, means for generating text introducing the features and advantages of the products using a generative AI model, means for displaying content including the generated text and purchase links, and means for providing filtering and sorting functions. This allows users to efficiently collect product information and browse the organized product comparison table to quickly compare and select products and choose the most suitable product.

[0454] "On the Internet" refers to websites and online databases accessible via the Internet.

[0455] "Product information" refers to information necessary for consumers to evaluate a product, such as product name, price, specifications, user reviews, images, and purchase links.

[0456] "Automatic collection means" refers to the process of using programs or scripts to obtain product information without human intervention through API calls or web scraping technology.

[0457] "Means for organizing and generating a product comparison table" refers to the process of converting collected product information into a unified format and compiling it into a form that allows the features of multiple products to be compared.

[0458] A "generative AI model" refers to a type of artificial intelligence that uses machine learning techniques to generate text.

[0459] "Means for generating text introducing product features and benefits" refers to the process of using a generative AI model to automatically generate text describing the features and benefits of each product.

[0460] "Generated Text" refers to text describing product features and benefits created using a generative AI model.

[0461] "Content with a purchase link" refers to information that includes a link for users to purchase the product along with generated text and detailed product information.

[0462] "Means for displaying" refers to the method for displaying the collected and organized product information and generated text on the user's device.

[0463] "Means for providing filtering and sorting functionality" refers to functionality that allows users to narrow down product information by criteria such as price or specifications, or sort it in a specific order.

[0464] This invention is a system for automating the collection, organization, comparison, and introduction of product information from the Internet. This system consists of three elements: a server, a terminal, and a user. Each element is described in detail below.

[0465] Users access the system mainly using terminals such as smartphones and personal computers. When a user accesses the system, the terminal sends a request for product information to the server. The server automatically collects product information from various websites and online databases on the Internet.

[0466] The server primarily uses the following hardware and software:

[0467] Hardware: Regular servers (on-premise or cloud-based)

[0468] Software: Node.js, axios, generative AI model (e.g., OpenAI's GPT-3)

[0469] First, the server uses programs and scripts to call APIs and web scraping techniques to collect information such as product names, prices, specifications, user reviews, images, and purchase links. The collected product information is then converted into a unified format within the server. Next, a product comparison table is generated based on this data.

[0470] The server then uses the generative AI model to generate sentences that explain the features and benefits of each product. Specifically, the server provides the following prompt sentences as input to the generative AI model:

[0471] Product name: [Product name]

[0472] Price: [Price]

[0473] Specs: [Specs]

[0474] Review: [Review]

[0475] Image URL: [Image URL]

[0476] Purchase link: [Purchase link]

[0477] Generate a testimonial about the features and benefits of this product.

[0478] For example, a description such as "This smartphone is equipped with a high-resolution camera and can take professional-quality photos" is generated based on the smartphone's information. The generated content, including the purchase link, is then sent to the device.

[0479] The terminal displays the product comparison chart and product descriptions sent from the server to the user. The user can filter and sort products based on the displayed information. This filtering and sorting function allows the user to sort products by lowest price or narrow down products by specific specifications.

[0480] Through the above process, users can efficiently and quickly compare and select products, and choose the most suitable one. This system can greatly improve user convenience by automating the entire process from collecting product information to purchasing.

[0481] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0482] Step 1:

[0483] The server receives product information requests from users. The input is the product information request sent by the user through the terminal. The output is the preparation of product information collection on the Internet based on the request.

[0484] Step 2:

[0485] The server automatically collects product information from various websites and online databases on the Internet. Specifically, it uses programs and scripts to call APIs and web scraping techniques. The input is the URL of the website or database to be collected. The output is the collected raw product information data.

[0486] Step 3:

[0487] The server converts the collected product information into a unified format. Specifically, it organizes the data into the form of product name, price, specifications, user reviews, image URL, purchase link, etc. The input is the collected raw product information data. The output is the product information converted into a unified format.

[0488] Step 4:

[0489] The server generates a product comparison table based on the product information converted into a unified format. The input is formatted product information data. The output is a product comparison table in a format that allows multiple products to be compared.

[0490] Step 5:

[0491] The server uses a generative AI model to generate text that describes the features and benefits of each product. Specific prompts are input to the generative AI model to generate the text. The inputs are detailed information about each product and the following prompts:

[0492] Product name: [Product name]

[0493] Price: [Price]

[0494] Specs: [Specs]

[0495] Review: [Review]

[0496] Image URL: [Image URL]

[0497] Purchase link: [Purchase link]

[0498] Generate a testimonial about the features and benefits of this product.

[0499] The output is a description of the features and benefits of the generated product.

[0500] Step 6:

[0501] The server integrates the generated testimonials and purchase links into a product comparison table and prepares it for transmission to the terminal. The input is the product comparison table, testimonials, and purchase links. The output is the integrated content to be transmitted to the terminal.

[0502] Step 7:

[0503] The terminal displays the product comparison table and product introductions sent from the server to the user. The input is the integrated content sent from the server. The output is the product comparison table and product introductions that the user can view.

[0504] Step 8:

[0505] Users can filter and sort the product information displayed through their devices. The input is the filtering and sorting conditions set by the user. The output is a product comparison table updated based on the conditions.

[0506] Step 9:

[0507] The user can select the most suitable product and proceed with the purchase procedure directly from the purchase link of the selected product. The input is the purchase link of the product selected by the user. The output is a transition to an external site where the purchase procedure is carried out.

[0508] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0509] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet, and aims to realize personalized product recommendations by combining it with an emotion engine that recognizes user emotions. This system is composed of a server, terminals, and users.

[0510] The server automatically collects product information from multiple websites and databases. Specifically, it uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images. The server then converts the collected information into a unified format and generates a product comparison table.

[0511] Next, the server uses the generative AI model to generate text describing the features and benefits of each product, highlighting the product's appeal to users. Furthermore, the server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase the product they're interested in.

[0512] When combined with an emotion engine, the server analyzes the user's facial expressions, voice, input text, etc. to recognize the user's emotions in real time. For example, if the user uses a webcam or microphone, the emotion engine obtains emotional data from the user's facial expressions and tone of voice. It also extracts and analyzes emotions from the text entered by the user. Product information and product descriptions are optimized based on the emotional data recognized by the emotion engine. For example, if the user is excited, it generates text that emphasizes the product's positive features. The emotion engine also integrates the user's purchase history with emotional data to recommend appropriate products.

[0513] The device receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application UI. The device also accepts user operations (filtering and sorting instructions) and performs corresponding data processing. For example, if the user selects "sort by price," the device sorts the product data by price and redisplays it. Furthermore, the device displays product recommendations suitable for the user based on the emotion data acquired by the emotion engine.

[0514] Users can view a product comparison chart displayed on their device to select the product that best suits them. They can also review the product details to understand the product's features and benefits. Recommendations based on the user's emotions allow for more personalized product selection. Finally, they can quickly purchase the product by clicking the purchase link.

[0515] As a specific example, when a user uses this system on a device with a webcam, the emotion engine recognizes emotions such as joy, excitement, and interest from the user's facial expressions. For example, if the user is smiling while browsing a product, the system generates a description that emphasizes the product's positive features. Conversely, if the user looks confused, the system displays detailed specifications and FAQ links to resolve the user's questions. This provides users with appropriate information tailored to their emotional state, making it easier for them to select the most suitable product.

[0516] This system not only automates the entire process from collecting product information to purchasing, but also takes user emotions into account to provide a richer and more personalized purchasing experience.

[0517] The processing flow will be explained below.

[0518] Program processing steps

[0519] Server-side processing steps

[0520] Step 1:

[0521] The server uses designated API endpoints and web scraping technology to collect product information from multiple sources on the Internet, including product names, prices, specifications, user reviews, and images.

[0522] Step 2:

[0523] The server converts the collected product information into a unified format, which includes data cleaning and normalization to ensure data from different sources is in a consistent format.

[0524] Step 3:

[0525] The server uses the organized product information to generate a product comparison table, which includes product names, prices, key specifications, and user reviews, and is organized to allow users to easily compare products.

[0526] Step 4:

[0527] The server uses the generative AI model to generate text that explains the features and benefits of each product. Specifically, it inputs product data into the AI ​​model and automatically generates an introductory text that conveys the product's appeal.

[0528] Step 5:

[0529] The server integrates the generated product description text into the data for each product, thereby adding the description text to the product data as detailed product information.

[0530] Step 6:

[0531] The server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase products they are interested in.

[0532] Step 7:

[0533] The server uses an emotion engine to analyze the user's facial expressions, voice, input text, etc. to recognize the user's emotions in real time, and optimizes product information and introductory text based on the emotion data.

[0534] Terminal processing steps

[0535] Step 1:

[0536] The device (user's browser or application) receives the product comparison chart, detailed descriptions, and purchase links sent from the server, analyzes the received data, and converts it into the format required for display.

[0537] Step 2:

[0538] The device displays product comparison tables and detailed descriptions as the UI of a web page or application. Specifically, it uses HTML and CSS to present product information to the user in a table or list format.

[0539] Step 3:

[0540] The terminal accepts user operations (filtering and sorting instructions) and performs the corresponding data processing. For example, if the user selects "sort by price," the terminal sorts the product data by price and redisplays it.

[0541] Step 4:

[0542] The device transmits the user's facial expressions and voice to an emotion engine that analyzes the user's emotions in real time. For example, it analyzes data acquired through a webcam or microphone to recognize the user's emotional state.

[0543] Step 5:

[0544] The device will then display appropriate product recommendations based on the recognized emotion data, emphasizing the positive aspects if the user is excited and providing detailed explanations if the user is confused.

[0545] User processing steps

[0546] Step 1:

[0547] Users can view a product comparison chart displayed on their device, compare the prices, specifications, and user reviews of each product, and consider which product best suits their needs.

[0548] Step 2:

[0549] The user checks the detailed product description displayed on the device to deepen their understanding of the product's features and advantages, for example, by referring to the product's advantages and unique features.

[0550] Step 3:

[0551] The user clicks on the purchase link and is taken to the e-commerce site, where they can proceed with the purchase. The purchase link takes the user directly to the purchase page, allowing for quick purchases.

[0552] Step 4:

[0553] Users can continue to check the details of the products they are interested in and, if necessary, refer to additional information and product recommendations provided by the emotion engine. The emotion engine analyzes the user's real-time emotional state and provides personalized information, making the purchasing experience richer and more efficient.

[0554] This system automates the entire process from collecting product information to making a purchase, and by taking into account the user's emotions, it is possible to provide a more personalized purchasing experience.

[0555] Example 2

[0556] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0557] Conventional online shopping systems have limitations in their functionality for aggregating and comparing information on products that users are interested in. In addition, product descriptions are standardized and lack personalization based on individual users' preferences and emotions. This has led to problems such as users being unable to select the most suitable product, which reduces their motivation to purchase.

[0558] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0559] In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and converting it into a unified format, means for generating a product comparison table, means for generating text introducing the features and advantages of products using a generative AI model, means for displaying content including the generated text and purchase links, means for analyzing user emotions in real time, and means for presenting optimal product information based on the emotion data, thereby enabling the provision of personalized product information for users and efficient product selection.

[0560] The "Internet" is a global information and communications network that connects computer networks around the world.

[0561] "Product information" refers to data about the characteristics and features of a product, such as the product name, price, specifications, user reviews, and images.

[0562] "Collection" is the process of obtaining and gathering specific information.

[0563] "Organization" is the process of arranging acquired data based on certain rules and standards to make it easier to view and use.

[0564] A "uniform format" is a method for aligning information into a certain format or structure.

[0565] A "product comparison table" is a table that displays the characteristics of multiple products in a list format to make it easier to compare them.

[0566] A "generative AI model" is a computational method or model that uses artificial intelligence techniques to automatically perform specific tasks.

[0567] "Sentence generation" is the process by which a computer automatically creates text using natural language.

[0568] A "purchase link" is a web link that a user can click to purchase an item.

[0569] "Content" is a general term for information displayed on a web page or application.

[0570] "Display" is the process of visually presenting information to a user.

[0571] "Real-time emotion analysis" is the process of analyzing a user's facial expressions, voice, text, etc. in real time to detect their emotional state.

[0572] "Emotion data" is information relating to the user's emotional state.

[0573] "Presenting optimal product information" is the process of suggesting the most suitable product information for the user based on the user's emotional state and other data.

[0574] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet. Furthermore, by combining it with an emotion engine that recognizes user emotions, it aims to realize personalized product recommendations. This system consists of a server, a terminal, and a user.

[0575] The server automatically collects product information from multiple websites and databases. Specifically, it uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images. For example, when collecting product information from Amazon or Rakuten Ichiba, the server uses those APIs. The collected information is converted into a unified format on the server side. This unifies the different data formats from each site and ensures data consistency.

[0576] Next, the server generates a product comparison table based on the product information converted into a unified format. This comparison table displays each product's price, specifications, user reviews, and other information in a list format. The server then uses a generative AI model to generate text that explains the features and benefits of each product. To do this, it issues a prompt to the generative AI model. As a concrete example, the prompt used is, "Generate a text that introduces the benefits of the latest smartphone."

[0577] In addition, the server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase products they are interested in. Using an emotion engine, the server analyzes the user's facial expressions, voice, and input text to obtain emotional data in real time. If the user is using a webcam or microphone, the emotion engine analyzes emotions from the user's facial expressions and tone of voice. Based on this emotional data, the server presents optimal product information.

[0578] The terminal receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application user interface. Furthermore, the terminal can redisplay the product data in response to user operations (filtering or sorting instructions). For example, if the user selects "sort by price," the terminal sorts and redisplays the product data in price order. In addition, the terminal displays recommended products that are most suitable for the user based on the emotion data acquired by the emotion engine.

[0579] Users can view a product comparison chart displayed on their device to select the product that best suits them. They can then review the product details to understand the product's features and benefits. Recommendation information based on emotional data is provided, enabling a more personalized product selection. Finally, users can quickly purchase the product by clicking the purchase link for the product that interests them.

[0580] As a concrete example, when a user uses this system with a device equipped with a webcam, the emotion engine recognizes the user's emotions from their facial expressions. For example, if the user is smiling while browsing a product, the system generates a description that emphasizes the product's positive features. Conversely, if the user looks confused, the system displays detailed specifications and FAQ links to resolve the user's questions.

[0581] This system automates the entire process from collecting product information to purchasing, and makes it possible to provide a personalized purchasing experience that takes user emotions into consideration.

[0582] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0583] Step 1:

[0584] The server collects product information from multiple websites and databases on the Internet. Specifically, it uses API calls and web scraping technology. For example, the server retrieves data such as product names, prices, specifications, user reviews, and images from specific websites. The input is raw data from websites and databases, and the output is the collected raw product information data.

[0585] Step 2:

[0586] The server organizes the collected product information and converts it into a unified format. Specifically, it parses different data formats (e.g., JSON, HTML) and converts them into a consistent format (e.g., CSV, database entries). It also cleans up missing values ​​and duplicate data. The input is the raw data of the collected product information, and the output is the product information converted into a unified format.

[0587] Step 3:

[0588] The server generates a product comparison table based on the product information converted into a unified format. Specifically, it creates a table that displays information such as the price, specifications, and user reviews of each product in a list format. This table is generated in Excel file or HTML format. The input is the product information converted into a unified format, and the output is a product comparison table.

[0589] Step 4:

[0590] The server uses the generative AI model to generate sentences that explain the features and benefits of each product. Specifically, it issues a prompt to the generative AI model: "Generate a sentence that introduces the benefits of the latest smartphone." The generated sentences are saved in JSON format. The inputs are the prompt and product information, and the output is the generated product description sentence.

[0591] Step 5:

[0592] The server uses an affiliate program to automatically generate a purchase link for each product. Specifically, it accesses the affiliate programs of Amazon and Rakuten Ichiba and obtains the URL for each product. This is then added to the product data. The input is product information and data from the affiliate program, and the output is the product data with the product purchase link added.

[0593] Step 6:

[0594] The server uses the emotion engine to analyze the user's facial expressions, voice, and input text to obtain emotion data. Specifically, when the user uses a webcam or microphone, the emotion engine analyzes the user's facial expressions and tone of voice in real time. The input is the user's facial expressions, voice, and input text, and the output is emotion data.

[0595] Step 7:

[0596] The device receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application user interface. Furthermore, the device redisplays the product data in response to user operations (filtering and sorting instructions). The input is data from the server and user operations, and the output is the product data displayed in the updated UI.

[0597] Step 8:

[0598] The user looks at the product comparison table displayed on the device and selects the product that best suits them. They check the product details and understand the product's features and benefits. They click on the purchase link for the product that interests them and quickly purchase the product. The input is the displayed product data, and the output is the user's selection and purchase operation.

[0599] (Application example 2)

[0600] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0601] Conventional online shopping sites and advertising systems provide uniform information without considering the user's feelings, making it difficult to recommend optimal products for the user and failing to fully stimulate purchasing motivation. In addition, providing a large amount of information at once confuses the user, making it take a long time to find the optimal product.

[0602] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and generating a product comparison table, means for generating text introducing product features and advantages using a generative AI model, means for recognizing user emotions and optimizing product information and introduction text based on the emotions, and means for displaying content including the generated text and purchase links. This allows users to receive personalized product recommendations in a more emotionally satisfying manner, increasing their desire to purchase and enabling them to find the best product efficiently and quickly.

[0603] "Means for automatically collecting product information from the Internet" refers to a function that uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images from multiple websites and databases.

[0604] The "means for organizing collected product information and generating a product comparison table" is a function that converts collected product information into a unified format and creates a product comparison table organized in an easy-to-compare format.

[0605] "Means for generating text introducing the features and benefits of a product using a generative AI model" refers to a function that uses a generative AI model to generate natural language text to explain the features and benefits of a product based on collected and organized product information.

[0606] "Means for recognizing the user's emotions and optimizing product information and descriptions based on those emotions" refers to a function that analyzes emotions from the user's facial expressions, voice, input text, etc., and optimizes product information and descriptions based on that emotional data.

[0607] The "means for displaying the content including the generated text and the purchase link" is an interface having a function for displaying the content including the generated text and the purchase link to the user.

[0608] This invention is a system that automatically collects product information from the Internet and provides personalized product recommendations using an emotion engine. This system is composed of a server, terminals, and users.

[0609] Server Roles

[0610] The server has the following main functions:

[0611] 1. Collecting product information:

[0612] The server uses API calls and web scraping technology to automatically collect data such as product names, prices, specifications, user reviews, and images from multiple websites and databases.

[0613] The collected information is stored in a database.

[0614] 2. Organizing product information and generating product comparison tables:

[0615] The collected product information is converted into a unified format and a product comparison table is generated.

[0616] 3. Generating introductory text using a generative AI model:

[0617] Using a generative AI model, text introducing product features and benefits is generated based on collected and organized data.

[0618] The generated text is automatically integrated with the data for each product.

[0619] 4. Use of Emotion Engine:

[0620] The server analyzes the user's facial expressions, voice, input text, etc., and recognizes the user's emotions in real time.

[0621] If the user is excited, it generates text that emphasizes the product's positive features, and if the user is confused, it displays detailed specifications and FAQ links.

[0622] Device Role

[0623] The device provides the user with the information sent by the server:

[0624] 1. Displaying information:

[0625] Show users a product comparison chart, detailed descriptions, and purchase links.

[0626] To display product recommendation information optimized based on a user's emotions.

[0627] 2. Accepting user operations:

[0628] It provides an interface for users to filter and sort product information and responds to user actions.

[0629] User Roles

[0630] Users receive information based on their emotions and make purchasing decisions:

[0631] 1. Check and compare information:

[0632] The user checks the product comparison chart displayed on the device and understands the features and advantages of the products.

[0633] 2. Purchasing behavior:

[0634] The user selects the most suitable product and purchases it by clicking the purchase link.

[0635] Hardware and software used

[0636] Hardware:

[0637] Smartphone (with camera and microphone)

[0638] software:

[0639] Frontend: React Native

[0640] Backend: Node.js + Express

[0641] Database: MongoDB

[0642] Emotion Recognition API: General facial recognition and voice analysis API

[0643] Generative AI Model: A general generative AI model

[0644] Specific examples

[0645] If a user smiles excitedly while browsing products in the gadget category, the emotion engine recognizes this smile and sends it to the server as an "excited" state. The server then receives this data and generates a prompt for the generative AI model, which then generates a positive description such as, "This gadget is equipped with the latest technology, has amazing performance, and is especially recommended for game enthusiasts!" and displays it on the device.

[0646] Prompt Sentence Examples

[0647] The user is browsing products in the Gadgets category. Their current emotion is "Excited." Generate a description that highlights the positive features of the following product:

[0648] Product Name: Smart Watch Pro

[0649] Price: 25,000 yen

[0650] Specifications: Built-in GPS, waterproof, long battery life

[0651] User review: "Very easy to use!"

[0652] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0653] Step 1: Gather product information

[0654] The server automatically collects data such as product name, price, specifications, user reviews, and images from multiple websites and databases on the Internet using API calls and web scraping technology. This data is then temporarily stored in a database on the server. The input is the website URL or API endpoint, and the output is the raw data of the retrieved product information.

[0655] Step 2: Organize product information and generate a product comparison table

[0656] The server converts the collected product information into a unified format and generates a product comparison table. Here, data cleansing and normalization are performed to make it easier for users to compare. The input is the collected raw product information data, and the output is a comparison table in a unified format.

[0657] Step 3: Generate an introduction

[0658] The server uses a generative AI model to generate text introducing the product's features and benefits based on the collected and organized data. The generated text is automatically integrated with the data for each product. The input is organized product information and a product comparison table, and the output is a text created by the generative AI model that explains the product's features.

[0659] Step 4: Real-time emotion recognition

[0660] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice. The emotion recognition API analyzes the user's emotions from this data and obtains emotional data in real time. The input is the captured image and audio, and the output is the analyzed emotional data.

[0661] Step 5: Optimize your text based on sentiment

[0662] The server uses the emotion data obtained from the emotion recognition API to optimize the generated product description. For example, if the user is excited, it generates a description that emphasizes the product's positive features. The input is the emotion data and the generated description, and the output is the optimized description.

[0663] Step 6: Displaying Content

[0664] The terminal displays the generated content to the user, such as a product comparison chart, detailed descriptions, and purchase links. The input is the optimized text and other product data sent from the server, and the output is the content displayed on the user's screen.

[0665] Step 7: Accepting user actions

[0666] The terminal provides an interface for users to filter and sort product information, accepts user operations, and updates the display based on the user operations. The input is the filter and sort conditions provided by the user, and the output is the updated product information after filtering and sorting.

[0667] Step 8: Making a purchase

[0668] Based on the optimized information displayed on the device, the user clicks on the purchase link to purchase the product. The input is the displayed product information and the purchase link, and the output is the user's purchasing behavior after going through the purchasing process.

[0669] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0670] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0671] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0672] [Third embodiment]

[0673] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0674] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0675] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0676] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0677] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0678] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0679] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0680] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0681] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0682] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0683] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0684] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0685] This invention relates to a system for automating the collection, organization, comparison, and introduction of product information from the Internet. This system is composed of a server, terminals, and users.

[0686] The server automatically collects product information from multiple websites and databases, using API calls and web scraping techniques to obtain information such as product names, prices, specifications, user reviews, and images. The server then converts the collected data into a unified format and generates a product comparison table.

[0687] The generated product comparison chart includes product names, prices, key specifications, and user review ratings. The server then uses the generative AI model to generate text that explains the features and benefits of each product, providing users with information in a way that clearly conveys the product's appeal.

[0688] The system uses a device (the user's browser or application) to display information in a way that is easily accessible to the user. The device receives data sent from the server and displays product comparison tables and detailed descriptions. The user can filter and sort the displayed information through the device. For example, they can sort by lowest price or filter by specific specifications.

[0689] As a concrete example, consider the case where a server collects smartphone product information. The server obtains smartphone information from each manufacturer's official website and major e-commerce platforms. Next, it organizes the collected information and compiles a comparison table of smartphone prices, screen sizes, battery capacities, camera resolutions, etc. Then, it uses a generative AI model to generate a description such as, "This smartphone is equipped with a high-resolution camera and can take professional-level photos." Finally, the server automatically generates a purchase link for each product and associates it with each target product.

[0690] When a user accesses the system through a browser, the device displays a comparison chart and introductions of smartphones sent from the server. The user can then select the most suitable smartphone based on this and proceed with the purchase process directly from the displayed purchase link. This process allows users to compare and select products efficiently and quickly, improving the experience leading up to the purchase.

[0691] This system automates the entire process from collecting product information to purchasing, improving user convenience and enabling the rapid provision of the latest information.

[0692] The processing flow will be explained below.

[0693] Program processing steps

[0694] Server-side processing steps

[0695] Step 1:

[0696] The server automatically collects product information from multiple websites and databases on the Internet, specifically using API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images.

[0697] Step 2:

[0698] The server converts the collected product information into a unified format, which involves a data cleaning and normalization process to organize and consolidate data from different sources into a common format.

[0699] Step 3:

[0700] The server generates a product comparison table based on the organized product information. The comparison table includes product names, prices, main specifications, and user reviews, and is organized to allow users to easily compare products.

[0701] Step 4:

[0702] The server uses a generative AI model to generate text that explains the features and benefits of each product. Specifically, product data is input into the AI ​​model, and the model automatically generates text that conveys the product's appeal.

[0703] Step 5:

[0704] The server then integrates the generated product descriptions into the data for each product, thereby creating detailed product information including the descriptions.

[0705] Step 6:

[0706] The server automatically generates a purchase link for each product and adds it to the product data. The purchase link is designed to enable users to quickly purchase the product they are interested in.

[0707] Terminal processing steps

[0708] Step 1:

[0709] The device (user's browser or application) receives the product comparison chart and detailed descriptions sent from the server, parses (analyzes) the received data, and converts it into the format required for display.

[0710] Step 2:

[0711] The device displays product comparison tables and detailed descriptions on web pages and app UIs. Specifically, it uses HTML and CSS to present product information to users in table or list format.

[0712] Step 3:

[0713] The terminal receives user operations (filtering and sorting instructions) and processes the data accordingly. For example, if the user selects "sort by price," the terminal sorts the product data by price and redisplays it.

[0714] User processing steps

[0715] Step 1:

[0716] Users can view a product comparison chart displayed on their device, compare the prices, specifications, and user reviews of each product, and then select the product that best suits their needs.

[0717] Step 2:

[0718] Users check the detailed description of the product they are interested in to better understand its features and benefits. The description clearly describes the product's advantages, which helps them make a purchasing decision.

[0719] Step 3:

[0720] Users click the purchase link to go to the e-commerce site and proceed with the purchase. The purchase link allows users to quickly access the purchase page and smoothly purchase the product.

[0721] Example 1

[0722] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0723] Today, the internet is packed with a vast amount of product information, making it difficult to select the right product. Manually collecting and comparing information is time-consuming and labor-intensive, and there are concerns about the reliability and accuracy of the information. Furthermore, collecting data from diverse websites and converting it into a unified format is technically challenging, and generating appropriate product descriptions requires skill. There is a need for a system that can resolve these issues and provide users with convenient and fast product information.

[0724] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0725] In this invention, the server includes means for automatically collecting product information from the Internet, means for converting the collected product information into a unified format and organizing it, and means for generating a product comparison table, which makes it possible to efficiently compare and organize the collected product information and provide it as useful data to users.

[0726] The system further includes a means for generating text introducing the features and benefits of the product using a generative AI model, and a means for displaying content including the generated text and a purchase link, thereby enabling users to easily understand product information and quickly obtain information for selecting an appropriate product.

[0727] The system also includes a means for providing an interface for users to filter and sort the product information, allowing users to customize the product information to suit their needs and quickly find the products that best suit their needs.

[0728] The "Internet" is a global network for exchanging information, consisting of multiple interconnected computer networks.

[0729] "Product information" refers to detailed data about a specific product, such as the name, price, specifications, user reviews, and images.

[0730] "Means of collection" refers to the technologies and methods used to obtain product information from various websites and databases on the Internet.

[0731] "Means for converting and organizing into a unified format" refers to techniques and methods for converting product information collected in different formats into a consistent format and organizing it in an orderly manner.

[0732] A "product comparison table" is data in a table format that displays multiple product information in a list format that makes it easy to compare them.

[0733] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate text, and is used to generate product descriptions, etc.

[0734] A "purchase link" is a hyperlink to a web page that allows a user to purchase a product.

[0735] "Filtering" is the process of selecting data based on specific conditions.

[0736] "Sorting" is the operation of changing the order of data based on specific criteria.

[0737] An "interface" refers to the means or techniques by which a user interacts with a system, including graphical user interfaces (GUIs).

[0738] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet. The system is composed of a server, terminals, and users, and is described in detail below.

[0739] Server configuration and processing

[0740] The server automatically collects product information from multiple websites and databases using API calls and web scraping techniques, such as issuing HTTP requests and parsing the HTML files or JSON data received as responses to extract product information.

[0741] The server then converts the collected data into a unified format. This conversion process involves normalizing the data, such as unifying different JSON key names and converting price information into a uniform currency unit. For example, all price information obtained from multiple websites can be managed under a unified key called "price" and currency conversion can be performed.

[0742] Based on the organized data, the server generates a product comparison table, which includes product names, prices, key specifications, user reviews, etc. To display the table in a tabular format, an appropriate data structure such as a data frame is used.

[0743] Next, the server uses the generative AI model to generate a product description. By inputting the following prompt into the generative AI model, the server generates a sentence that describes the product's features and benefits.

[0744] Example prompt sentence:

[0745] "Collect and organize smartphone product information, and generate a comparison chart and compelling product descriptions. Required information includes product name, price, specifications, user reviews, and images. Include the features and benefits of each product in the description."

[0746] The generated content, such as a description, a product comparison chart, and a purchase link, is sent to the terminal by the server.

[0747] Terminal configuration and handling

[0748] When a user accesses the system, the terminal receives the data sent from the server. This terminal is the user's browser or application, and displays the received product comparison chart and testimonials in an easy-to-read format.

[0749] Specifically, it uses HTML and CSS to organize the display and provides functions for sorting and filtering products for easy viewing. For example, if a user selects "Price: Ascending," the device will sort the displayed product list from lowest to highest price.

[0750] User operations

[0751] Users can browse, filter, and sort product information through their devices. For example, by filtering by specific specifications, they can display only products that meet their needs. This allows users to quickly find the perfect product.

[0752] Furthermore, the user can click on the displayed purchase link to directly access the purchase page and proceed with the purchase process.

[0753] Specific examples

[0754] For example, when collecting smartphone information, the server retrieves it from each manufacturer's official website and major e-commerce platforms. The collected information is converted into a unified format and a comparison table is compiled of information such as screen size, battery capacity, and camera resolution. The generative AI model is then used to generate a description such as, "This smartphone is equipped with a high-resolution camera and can take professional-quality photos." The server then generates a purchase link for each product and associates it with each target product.

[0755] This system automates the entire process from collecting product information to purchasing, improving user convenience and enabling the prompt provision of the latest information.

[0756] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0757] Step 1: Data collection

[0758] The server automatically collects product information from multiple websites and databases. It uses a list of URLs from each website and database as input. Specifically, the server issues an HTTP request and extracts product information by parsing the HTML file or JSON data received as a response. This process obtains data such as product name, price, specifications, user reviews, and images. The collected raw data is generated as output.

[0759] Step 2: Cleanse and transform the data

[0760] The server converts the collected raw data into a unified format. The raw data obtained in step 1 is used as input. Specific operations include normalizing the data by unifying different JSON key names and converting price information into a single currency unit. For example, "price_usd" and "price_euro" are unified into "price" and converted to USD. Data in a unified format is generated as output.

[0761] Step 3: Generate a product comparison table

[0762] The server generates a product comparison table based on the unified format data. The unified format data generated in step 2 is used as input. Specifically, it organizes product names, prices, key specifications, user review ratings, etc. in a table format. Using an appropriate data structure such as a data frame format makes table generation easy. A product comparison table is generated as output.

[0763] Step 4: Generate a testimonial

[0764] The server uses a generative AI model to generate product descriptions. The input is the data for each product listed in the product comparison chart and a prompt. Specifically, the prompt is input into the generative AI model to generate a description that explains the product's features and benefits. For example, the prompt could be "This smartphone is equipped with a high-resolution camera, allowing you to take professional-quality photos." The output is a description of each product.

[0765] Step 5: Generate a purchase link

[0766] The server automatically generates a purchase link for each product based on links from the collected website or e-commerce platform. The input is the data for each product and the URL template for the purchase page. Specifically, the purchase link is generated by embedding the product ID and parameters in the URL template. For example, a link is generated by embedding the ID "12345" in the template "https: / / example.com / product / {product_id}". The output is a purchase link for each product.

[0767] Step 6: View the data

[0768] When a user accesses the system, the terminal receives the product comparison table, testimonials, and purchase links sent from the server. The data from the server is used as input. Specifically, the terminal uses HTML and CSS to display the received data in an easy-to-read format. For example, the product comparison table is displayed in a table format, with testimonials and purchase links appropriately arranged. As output, the information is displayed on the user's screen.

[0769] Step 7: Filtering and Sorting

[0770] The user can filter and sort product information through the terminal. The filter and sort conditions selected by the user are used as input. Specifically, the terminal dynamically updates the displayed product list using JavaScript or other methods. For example, if the user selects "Price: Ascending", the terminal sorts and displays products in ascending order of price. The output displays a product list filtered and sorted according to the user's selection.

[0771] (Application example 1)

[0772] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0773] There is a need to efficiently collect and organize product information on the Internet and provide users with fast and accurate product comparisons and introductions. With current systems, collecting, organizing, comparing, and introducing this information takes a lot of time and effort, and it is difficult for users to find the information they are looking for. For this reason, it is necessary to automate the process from collecting product information to purchasing, thereby improving user convenience.

[0774] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0775] In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and generating a product comparison table, means for generating text introducing the features and advantages of the products using a generative AI model, means for displaying content including the generated text and purchase links, and means for providing filtering and sorting functions. This allows users to efficiently collect product information and browse the organized product comparison table to quickly compare and select products and choose the most suitable product.

[0776] "On the Internet" refers to websites and online databases accessible via the Internet.

[0777] "Product information" refers to information necessary for consumers to evaluate a product, such as product name, price, specifications, user reviews, images, and purchase links.

[0778] "Automatic collection means" refers to the process of using programs or scripts to obtain product information without human intervention through API calls or web scraping technology.

[0779] "Means for organizing and generating a product comparison table" refers to the process of converting collected product information into a unified format and compiling it into a form that allows the features of multiple products to be compared.

[0780] A "generative AI model" refers to a type of artificial intelligence that uses machine learning techniques to generate text.

[0781] "Means for generating text introducing product features and benefits" refers to the process of using a generative AI model to automatically generate text describing the features and benefits of each product.

[0782] "Generated Text" refers to text describing product features and benefits created using a generative AI model.

[0783] "Content with a purchase link" refers to information that includes a link for users to purchase the product along with generated text and detailed product information.

[0784] "Means for displaying" refers to the method for displaying the collected and organized product information and generated text on the user's device.

[0785] "Means for providing filtering and sorting functionality" refers to functionality that allows users to narrow down product information by criteria such as price or specifications, or sort it in a specific order.

[0786] This invention is a system for automating the collection, organization, comparison, and introduction of product information from the Internet. This system consists of three elements: a server, a terminal, and a user. Each element is described in detail below.

[0787] Users access the system mainly using terminals such as smartphones and personal computers. When a user accesses the system, the terminal sends a request for product information to the server. The server automatically collects product information from various websites and online databases on the Internet.

[0788] The server primarily uses the following hardware and software:

[0789] Hardware: Regular servers (on-premise or cloud-based)

[0790] Software: Node.js, axios, generative AI model (e.g., OpenAI's GPT-3)

[0791] First, the server uses programs and scripts to call APIs and web scraping techniques to collect information such as product names, prices, specifications, user reviews, images, and purchase links. The collected product information is then converted into a unified format within the server. Next, a product comparison table is generated based on this data.

[0792] The server then uses the generative AI model to generate sentences that explain the features and benefits of each product. Specifically, the server provides the following prompt sentences as input to the generative AI model:

[0793] Product name: [Product name]

[0794] Price: [Price]

[0795] Specs: [Specs]

[0796] Review: [Review]

[0797] Image URL: [Image URL]

[0798] Purchase link: [Purchase link]

[0799] Generate a testimonial about the features and benefits of this product.

[0800] For example, a description such as "This smartphone is equipped with a high-resolution camera and can take professional-quality photos" is generated based on the smartphone's information. The generated content, including the purchase link, is then sent to the device.

[0801] The terminal displays the product comparison chart and product descriptions sent from the server to the user. The user can filter and sort products based on the displayed information. This filtering and sorting function allows the user to sort products by lowest price or narrow down products by specific specifications.

[0802] Through the above process, users can efficiently and quickly compare and select products, and choose the most suitable one. This system can greatly improve user convenience by automating the entire process from collecting product information to purchasing.

[0803] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0804] Step 1:

[0805] The server receives product information requests from users. The input is the product information request sent by the user through the terminal. The output is the preparation of product information collection on the Internet based on the request.

[0806] Step 2:

[0807] The server automatically collects product information from various websites and online databases on the Internet. Specifically, it uses programs and scripts to call APIs and web scraping techniques. The input is the URL of the website or database to be collected. The output is the collected raw product information data.

[0808] Step 3:

[0809] The server converts the collected product information into a unified format. Specifically, it organizes the data into the form of product name, price, specifications, user reviews, image URL, purchase link, etc. The input is the collected raw product information data. The output is the product information converted into a unified format.

[0810] Step 4:

[0811] The server generates a product comparison table based on the product information converted into a unified format. The input is formatted product information data. The output is a product comparison table in a format that allows multiple products to be compared.

[0812] Step 5:

[0813] The server uses a generative AI model to generate text that describes the features and benefits of each product. Specific prompts are input to the generative AI model to generate the text. The inputs are detailed information about each product and the following prompts:

[0814] Product name: [Product name]

[0815] Price: [Price]

[0816] Specs: [Specs]

[0817] Review: [Review]

[0818] Image URL: [Image URL]

[0819] Purchase link: [Purchase link]

[0820] Generate a testimonial about the features and benefits of this product.

[0821] The output is a description of the features and benefits of the generated product.

[0822] Step 6:

[0823] The server integrates the generated testimonials and purchase links into a product comparison table and prepares it for transmission to the terminal. The input is the product comparison table, testimonials, and purchase links. The output is the integrated content to be transmitted to the terminal.

[0824] Step 7:

[0825] The terminal displays the product comparison table and product introductions sent from the server to the user. The input is the integrated content sent from the server. The output is the product comparison table and product introductions that the user can view.

[0826] Step 8:

[0827] Users can filter and sort the product information displayed through their devices. The input is the filtering and sorting conditions set by the user. The output is a product comparison table updated based on the conditions.

[0828] Step 9:

[0829] The user can select the most suitable product and proceed with the purchase procedure directly from the purchase link of the selected product. The input is the purchase link of the product selected by the user. The output is a transition to an external site where the purchase procedure is carried out.

[0830] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0831] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet, and aims to realize personalized product recommendations by combining it with an emotion engine that recognizes user emotions. This system is composed of a server, terminals, and users.

[0832] The server automatically collects product information from multiple websites and databases. Specifically, it uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images. The server then converts the collected information into a unified format and generates a product comparison table.

[0833] Next, the server uses the generative AI model to generate text describing the features and benefits of each product, highlighting the product's appeal to users. Furthermore, the server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase the product they're interested in.

[0834] When combined with an emotion engine, the server analyzes the user's facial expressions, voice, input text, etc. to recognize the user's emotions in real time. For example, if the user uses a webcam or microphone, the emotion engine obtains emotional data from the user's facial expressions and tone of voice. It also extracts and analyzes emotions from the text entered by the user. Product information and product descriptions are optimized based on the emotional data recognized by the emotion engine. For example, if the user is excited, it generates text that emphasizes the product's positive features. The emotion engine also integrates the user's purchase history with emotional data to recommend appropriate products.

[0835] The device receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application UI. The device also accepts user operations (filtering and sorting instructions) and performs corresponding data processing. For example, if the user selects "sort by price," the device sorts the product data by price and redisplays it. Furthermore, the device displays product recommendations suitable for the user based on the emotion data acquired by the emotion engine.

[0836] Users can view a product comparison chart displayed on their device to select the product that best suits them. They can also review the product details to understand the product's features and benefits. Recommendations based on the user's emotions allow for more personalized product selection. Finally, they can quickly purchase the product by clicking the purchase link.

[0837] As a specific example, when a user uses this system on a device with a webcam, the emotion engine recognizes emotions such as joy, excitement, and interest from the user's facial expressions. For example, if the user is smiling while browsing a product, the system generates a description that emphasizes the product's positive features. Conversely, if the user looks confused, the system displays detailed specifications and FAQ links to resolve the user's questions. This provides users with appropriate information tailored to their emotional state, making it easier for them to select the most suitable product.

[0838] This system not only automates the entire process from collecting product information to purchasing, but also takes user emotions into account to provide a richer and more personalized purchasing experience.

[0839] The processing flow will be explained below.

[0840] Program processing steps

[0841] Server-side processing steps

[0842] Step 1:

[0843] The server uses designated API endpoints and web scraping technology to collect product information from multiple sources on the Internet, including product names, prices, specifications, user reviews, and images.

[0844] Step 2:

[0845] The server converts the collected product information into a unified format, which includes data cleaning and normalization to ensure data from different sources is in a consistent format.

[0846] Step 3:

[0847] The server uses the organized product information to generate a product comparison table, which includes product names, prices, key specifications, and user reviews, and is organized to allow users to easily compare products.

[0848] Step 4:

[0849] The server uses the generative AI model to generate text that explains the features and benefits of each product. Specifically, it inputs product data into the AI ​​model and automatically generates an introductory text that conveys the product's appeal.

[0850] Step 5:

[0851] The server integrates the generated product description text into the data for each product, thereby adding the description text to the product data as detailed product information.

[0852] Step 6:

[0853] The server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase products they are interested in.

[0854] Step 7:

[0855] The server uses an emotion engine to analyze the user's facial expressions, voice, input text, etc. to recognize the user's emotions in real time, and optimizes product information and introductory text based on the emotion data.

[0856] Terminal processing steps

[0857] Step 1:

[0858] The device (user's browser or application) receives the product comparison chart, detailed descriptions, and purchase links sent from the server, analyzes the received data, and converts it into the format required for display.

[0859] Step 2:

[0860] The device displays product comparison tables and detailed descriptions as the UI of a web page or application. Specifically, it uses HTML and CSS to present product information to the user in a table or list format.

[0861] Step 3:

[0862] The terminal accepts user operations (filtering and sorting instructions) and performs the corresponding data processing. For example, if the user selects "sort by price," the terminal sorts the product data by price and redisplays it.

[0863] Step 4:

[0864] The device transmits the user's facial expressions and voice to an emotion engine that analyzes the user's emotions in real time. For example, it analyzes data acquired through a webcam or microphone to recognize the user's emotional state.

[0865] Step 5:

[0866] The device will then display appropriate product recommendations based on the recognized emotion data, emphasizing the positive aspects if the user is excited and providing detailed explanations if the user is confused.

[0867] User processing steps

[0868] Step 1:

[0869] Users can view a product comparison chart displayed on their device, compare the prices, specifications, and user reviews of each product, and consider which product best suits their needs.

[0870] Step 2:

[0871] The user checks the detailed product description displayed on the device to deepen their understanding of the product's features and advantages, for example, by referring to the product's advantages and unique features.

[0872] Step 3:

[0873] The user clicks on the purchase link and is taken to the e-commerce site, where they can proceed with the purchase. The purchase link takes the user directly to the purchase page, allowing for quick purchases.

[0874] Step 4:

[0875] Users can continue to check the details of the products they are interested in and, if necessary, refer to additional information and product recommendations provided by the emotion engine. The emotion engine analyzes the user's real-time emotional state and provides personalized information, making the purchasing experience richer and more efficient.

[0876] This system automates the entire process from collecting product information to making a purchase, and by taking into account the user's emotions, it is possible to provide a more personalized purchasing experience.

[0877] Example 2

[0878] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0879] Conventional online shopping systems have limitations in their functionality for aggregating and comparing information on products that users are interested in. In addition, product descriptions are standardized and lack personalization based on individual users' preferences and emotions. This has led to problems such as users being unable to select the most suitable product, which reduces their motivation to purchase.

[0880] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0881] In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and converting it into a unified format, means for generating a product comparison table, means for generating text introducing the features and advantages of products using a generative AI model, means for displaying content including the generated text and purchase links, means for analyzing user emotions in real time, and means for presenting optimal product information based on the emotion data, thereby enabling the provision of personalized product information for users and efficient product selection.

[0882] The "Internet" is a global information and communications network that connects computer networks around the world.

[0883] "Product information" refers to data about the characteristics and features of a product, such as the product name, price, specifications, user reviews, and images.

[0884] "Collection" is the process of obtaining and gathering specific information.

[0885] "Organization" is the process of arranging acquired data based on certain rules and standards to make it easier to view and use.

[0886] A "uniform format" is a method for aligning information into a certain format or structure.

[0887] A "product comparison table" is a table that displays the characteristics of multiple products in a list format to make it easier to compare them.

[0888] A "generative AI model" is a computational method or model that uses artificial intelligence techniques to automatically perform specific tasks.

[0889] "Sentence generation" is the process by which a computer automatically creates text using natural language.

[0890] A "purchase link" is a web link that a user can click to purchase an item.

[0891] "Content" is a general term for information displayed on a web page or application.

[0892] "Display" is the process of visually presenting information to a user.

[0893] "Real-time emotion analysis" is the process of analyzing a user's facial expressions, voice, text, etc. in real time to detect their emotional state.

[0894] "Emotion data" is information relating to the user's emotional state.

[0895] "Presenting optimal product information" is the process of suggesting the most suitable product information for the user based on the user's emotional state and other data.

[0896] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet. Furthermore, by combining it with an emotion engine that recognizes user emotions, it aims to realize personalized product recommendations. This system consists of a server, a terminal, and a user.

[0897] The server automatically collects product information from multiple websites and databases. Specifically, it uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images. For example, when collecting product information from Amazon or Rakuten Ichiba, the server uses those APIs. The collected information is converted into a unified format on the server side. This unifies the different data formats from each site and ensures data consistency.

[0898] Next, the server generates a product comparison table based on the product information converted into a unified format. This comparison table displays each product's price, specifications, user reviews, and other information in a list format. The server then uses a generative AI model to generate text that explains the features and benefits of each product. To do this, it issues a prompt to the generative AI model. As a concrete example, the prompt used is, "Generate a text that introduces the benefits of the latest smartphone."

[0899] In addition, the server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase products they are interested in. Using an emotion engine, the server analyzes the user's facial expressions, voice, and input text to obtain emotional data in real time. If the user is using a webcam or microphone, the emotion engine analyzes emotions from the user's facial expressions and tone of voice. Based on this emotional data, the server presents optimal product information.

[0900] The terminal receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application user interface. Furthermore, the terminal can redisplay the product data in response to user operations (filtering or sorting instructions). For example, if the user selects "sort by price," the terminal sorts and redisplays the product data in price order. In addition, the terminal displays recommended products that are most suitable for the user based on the emotion data acquired by the emotion engine.

[0901] Users can view a product comparison chart displayed on their device to select the product that best suits them. They can then review the product details to understand the product's features and benefits. Recommendation information based on emotional data is provided, enabling a more personalized product selection. Finally, users can quickly purchase the product by clicking the purchase link for the product that interests them.

[0902] As a concrete example, when a user uses this system with a device equipped with a webcam, the emotion engine recognizes the user's emotions from their facial expressions. For example, if the user is smiling while browsing a product, the system generates a description that emphasizes the product's positive features. Conversely, if the user looks confused, the system displays detailed specifications and FAQ links to resolve the user's questions.

[0903] This system automates the entire process from collecting product information to purchasing, and makes it possible to provide a personalized purchasing experience that takes user emotions into consideration.

[0904] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0905] Step 1:

[0906] The server collects product information from multiple websites and databases on the Internet. Specifically, it uses API calls and web scraping technology. For example, the server retrieves data such as product names, prices, specifications, user reviews, and images from specific websites. The input is raw data from websites and databases, and the output is the collected raw product information data.

[0907] Step 2:

[0908] The server organizes the collected product information and converts it into a unified format. Specifically, it parses different data formats (e.g., JSON, HTML) and converts them into a consistent format (e.g., CSV, database entries). It also cleans up missing values ​​and duplicate data. The input is the raw data of the collected product information, and the output is the product information converted into a unified format.

[0909] Step 3:

[0910] The server generates a product comparison table based on the product information converted into a unified format. Specifically, it creates a table that displays information such as the price, specifications, and user reviews of each product in a list format. This table is generated in Excel file or HTML format. The input is the product information converted into a unified format, and the output is a product comparison table.

[0911] Step 4:

[0912] The server uses the generative AI model to generate sentences that explain the features and benefits of each product. Specifically, it issues a prompt to the generative AI model: "Generate a sentence that introduces the benefits of the latest smartphone." The generated sentences are saved in JSON format. The inputs are the prompt and product information, and the output is the generated product description sentence.

[0913] Step 5:

[0914] The server uses an affiliate program to automatically generate a purchase link for each product. Specifically, it accesses the affiliate programs of Amazon and Rakuten Ichiba and obtains the URL for each product. This is then added to the product data. The input is product information and data from the affiliate program, and the output is the product data with the product purchase link added.

[0915] Step 6:

[0916] The server uses the emotion engine to analyze the user's facial expressions, voice, and input text to obtain emotion data. Specifically, when the user uses a webcam or microphone, the emotion engine analyzes the user's facial expressions and tone of voice in real time. The input is the user's facial expressions, voice, and input text, and the output is emotion data.

[0917] Step 7:

[0918] The device receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application user interface. Furthermore, the device redisplays the product data in response to user operations (filtering and sorting instructions). The input is data from the server and user operations, and the output is the product data displayed in the updated UI.

[0919] Step 8:

[0920] The user looks at the product comparison table displayed on the device and selects the product that best suits them. They check the product details and understand the product's features and benefits. They click on the purchase link for the product that interests them and quickly purchase the product. The input is the displayed product data, and the output is the user's selection and purchase operation.

[0921] (Application example 2)

[0922] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0923] Conventional online shopping sites and advertising systems provide uniform information without considering the user's feelings, making it difficult to recommend optimal products for the user and failing to fully stimulate purchasing motivation. In addition, providing a large amount of information at once confuses the user, making it take a long time to find the optimal product.

[0924] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and generating a product comparison table, means for generating text introducing product features and advantages using a generative AI model, means for recognizing user emotions and optimizing product information and introduction text based on the emotions, and means for displaying content including the generated text and purchase links. This allows users to receive personalized product recommendations in a more emotionally satisfying manner, increasing their desire to purchase and enabling them to find the best product efficiently and quickly.

[0925] "Means for automatically collecting product information from the Internet" refers to a function that uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images from multiple websites and databases.

[0926] The "means for organizing collected product information and generating a product comparison table" is a function that converts collected product information into a unified format and creates a product comparison table organized in an easy-to-compare format.

[0927] "Means for generating text introducing the features and benefits of a product using a generative AI model" refers to a function that uses a generative AI model to generate natural language text to explain the features and benefits of a product based on collected and organized product information.

[0928] "Means for recognizing the user's emotions and optimizing product information and descriptions based on those emotions" refers to a function that analyzes emotions from the user's facial expressions, voice, input text, etc., and optimizes product information and descriptions based on that emotional data.

[0929] The "means for displaying the content including the generated text and the purchase link" is an interface having a function for displaying the content including the generated text and the purchase link to the user.

[0930] This invention is a system that automatically collects product information from the Internet and provides personalized product recommendations using an emotion engine. This system is composed of a server, terminals, and users.

[0931] Server Roles

[0932] The server has the following main functions:

[0933] 1. Collecting product information:

[0934] The server uses API calls and web scraping technology to automatically collect data such as product names, prices, specifications, user reviews, and images from multiple websites and databases.

[0935] The collected information is stored in a database.

[0936] 2. Organizing product information and generating product comparison tables:

[0937] The collected product information is converted into a unified format and a product comparison table is generated.

[0938] 3. Generating introductory text using a generative AI model:

[0939] Using a generative AI model, text introducing product features and benefits is generated based on collected and organized data.

[0940] The generated text is automatically integrated with the data for each product.

[0941] 4. Use of Emotion Engine:

[0942] The server analyzes the user's facial expressions, voice, input text, etc., and recognizes the user's emotions in real time.

[0943] If the user is excited, it generates text that emphasizes the product's positive features, and if the user is confused, it displays detailed specifications and FAQ links.

[0944] Device Role

[0945] The device provides the user with the information sent by the server:

[0946] 1. Displaying information:

[0947] Show users a product comparison chart, detailed descriptions, and purchase links.

[0948] To display product recommendation information optimized based on a user's emotions.

[0949] 2. Accepting user operations:

[0950] It provides an interface for users to filter and sort product information and responds to user actions.

[0951] User Roles

[0952] Users receive information based on their emotions and make purchasing decisions:

[0953] 1. Check and compare information:

[0954] The user checks the product comparison chart displayed on the device and understands the features and advantages of the products.

[0955] 2. Purchasing behavior:

[0956] The user selects the most suitable product and purchases it by clicking the purchase link.

[0957] Hardware and software used

[0958] Hardware:

[0959] Smartphone (with camera and microphone)

[0960] software:

[0961] Frontend: React Native

[0962] Backend: Node.js + Express

[0963] Database: MongoDB

[0964] Emotion Recognition API: General facial recognition and voice analysis API

[0965] Generative AI Model: A general generative AI model

[0966] Specific examples

[0967] If a user smiles excitedly while browsing products in the gadget category, the emotion engine recognizes this smile and sends it to the server as an "excited" state. The server then receives this data and generates a prompt for the generative AI model, which then generates a positive description such as, "This gadget is equipped with the latest technology, has amazing performance, and is especially recommended for game enthusiasts!" and displays it on the device.

[0968] Prompt Sentence Examples

[0969] The user is browsing products in the Gadgets category. Their current emotion is "Excited." Generate a description that highlights the positive features of the following product:

[0970] Product Name: Smart Watch Pro

[0971] Price: 25,000 yen

[0972] Specifications: Built-in GPS, waterproof, long battery life

[0973] User review: "Very easy to use!"

[0974] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0975] Step 1: Gather product information

[0976] The server automatically collects data such as product name, price, specifications, user reviews, and images from multiple websites and databases on the Internet using API calls and web scraping technology. This data is then temporarily stored in a database on the server. The input is the website URL or API endpoint, and the output is the raw data of the retrieved product information.

[0977] Step 2: Organize product information and generate a product comparison table

[0978] The server converts the collected product information into a unified format and generates a product comparison table. Here, data cleansing and normalization are performed to make it easier for users to compare. The input is the collected raw product information data, and the output is a comparison table in a unified format.

[0979] Step 3: Generate an introduction

[0980] The server uses a generative AI model to generate text introducing the product's features and benefits based on the collected and organized data. The generated text is automatically integrated with the data for each product. The input is organized product information and a product comparison table, and the output is a text created by the generative AI model that explains the product's features.

[0981] Step 4: Real-time emotion recognition

[0982] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice. The emotion recognition API analyzes the user's emotions from this data and obtains emotional data in real time. The input is the captured image and audio, and the output is the analyzed emotional data.

[0983] Step 5: Optimize your text based on sentiment

[0984] The server uses the emotion data obtained from the emotion recognition API to optimize the generated product description. For example, if the user is excited, it generates a description that emphasizes the product's positive features. The input is the emotion data and the generated description, and the output is the optimized description.

[0985] Step 6: Displaying Content

[0986] The terminal displays the generated content to the user, such as a product comparison chart, detailed descriptions, and purchase links. The input is the optimized text and other product data sent from the server, and the output is the content displayed on the user's screen.

[0987] Step 7: Accepting user actions

[0988] The terminal provides an interface for users to filter and sort product information, accepts user operations, and updates the display based on the user operations. The input is the filter and sort conditions provided by the user, and the output is the updated product information after filtering and sorting.

[0989] Step 8: Making a purchase

[0990] Based on the optimized information displayed on the device, the user clicks on the purchase link to purchase the product. The input is the displayed product information and the purchase link, and the output is the user's purchasing behavior after going through the purchasing process.

[0991] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0992] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0993] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0994] [Fourth embodiment]

[0995] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0996] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0997] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0998] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0999] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1000] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1001] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1002] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1003] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1004] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1005] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1006] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1007] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1008] This invention relates to a system for automating the collection, organization, comparison, and introduction of product information from the Internet. This system is composed of a server, terminals, and users.

[1009] The server automatically collects product information from multiple websites and databases, using API calls and web scraping techniques to obtain information such as product names, prices, specifications, user reviews, and images. The server then converts the collected data into a unified format and generates a product comparison table.

[1010] The generated product comparison chart includes product names, prices, key specifications, and user review ratings. The server then uses the generative AI model to generate text that explains the features and benefits of each product, providing users with information in a way that clearly conveys the product's appeal.

[1011] The system uses a device (the user's browser or application) to display information in a way that is easily accessible to the user. The device receives data sent from the server and displays product comparison tables and detailed descriptions. The user can filter and sort the displayed information through the device. For example, they can sort by lowest price or filter by specific specifications.

[1012] As a concrete example, consider the case where a server collects smartphone product information. The server obtains smartphone information from each manufacturer's official website and major e-commerce platforms. Next, it organizes the collected information and compiles a comparison table of smartphone prices, screen sizes, battery capacities, camera resolutions, etc. Then, it uses a generative AI model to generate a description such as, "This smartphone is equipped with a high-resolution camera and can take professional-level photos." Finally, the server automatically generates a purchase link for each product and associates it with each target product.

[1013] When a user accesses the system through a browser, the device displays a comparison chart and introductions of smartphones sent from the server. The user can then select the most suitable smartphone based on this and proceed with the purchase process directly from the displayed purchase link. This process allows users to compare and select products efficiently and quickly, improving the experience leading up to the purchase.

[1014] This system automates the entire process from collecting product information to purchasing, improving user convenience and enabling the rapid provision of the latest information.

[1015] The processing flow will be explained below.

[1016] Program processing steps

[1017] Server-side processing steps

[1018] Step 1:

[1019] The server automatically collects product information from multiple websites and databases on the Internet, specifically using API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images.

[1020] Step 2:

[1021] The server converts the collected product information into a unified format, which involves a data cleaning and normalization process to organize and consolidate data from different sources into a common format.

[1022] Step 3:

[1023] The server generates a product comparison table based on the organized product information. The comparison table includes product names, prices, main specifications, and user reviews, and is organized to allow users to easily compare products.

[1024] Step 4:

[1025] The server uses a generative AI model to generate text that explains the features and benefits of each product. Specifically, product data is input into the AI ​​model, and the model automatically generates text that conveys the product's appeal.

[1026] Step 5:

[1027] The server then integrates the generated product descriptions into the data for each product, thereby creating detailed product information including the descriptions.

[1028] Step 6:

[1029] The server automatically generates a purchase link for each product and adds it to the product data. The purchase link is designed to enable users to quickly purchase the product they are interested in.

[1030] Terminal processing steps

[1031] Step 1:

[1032] The device (user's browser or application) receives the product comparison chart and detailed descriptions sent from the server, parses (analyzes) the received data, and converts it into the format required for display.

[1033] Step 2:

[1034] The device displays product comparison tables and detailed descriptions on web pages and app UIs. Specifically, it uses HTML and CSS to present product information to users in table or list format.

[1035] Step 3:

[1036] The terminal receives user operations (filtering and sorting instructions) and processes the data accordingly. For example, if the user selects "sort by price," the terminal sorts the product data by price and redisplays it.

[1037] User processing steps

[1038] Step 1:

[1039] Users can view a product comparison chart displayed on their device, compare the prices, specifications, and user reviews of each product, and then select the product that best suits their needs.

[1040] Step 2:

[1041] Users check the detailed description of the product they are interested in to better understand its features and benefits. The description clearly describes the product's advantages, which helps them make a purchasing decision.

[1042] Step 3:

[1043] Users click the purchase link to go to the e-commerce site and proceed with the purchase. The purchase link allows users to quickly access the purchase page and smoothly purchase the product.

[1044] Example 1

[1045] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1046] Today, the internet is packed with a vast amount of product information, making it difficult to select the right product. Manually collecting and comparing information is time-consuming and labor-intensive, and there are concerns about the reliability and accuracy of the information. Furthermore, collecting data from diverse websites and converting it into a unified format is technically challenging, and generating appropriate product descriptions requires skill. There is a need for a system that can resolve these issues and provide users with convenient and fast product information.

[1047] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1048] In this invention, the server includes means for automatically collecting product information from the Internet, means for converting the collected product information into a unified format and organizing it, and means for generating a product comparison table, which makes it possible to efficiently compare and organize the collected product information and provide it as useful data to users.

[1049] The system further includes a means for generating text introducing the features and benefits of the product using a generative AI model, and a means for displaying content including the generated text and a purchase link, thereby enabling users to easily understand product information and quickly obtain information for selecting an appropriate product.

[1050] The system also includes a means for providing an interface for users to filter and sort the product information, allowing users to customize the product information to suit their needs and quickly find the products that best suit their needs.

[1051] The "Internet" is a global network for exchanging information, consisting of multiple interconnected computer networks.

[1052] "Product information" refers to detailed data about a specific product, such as the name, price, specifications, user reviews, and images.

[1053] "Means of collection" refers to the technologies and methods used to obtain product information from various websites and databases on the Internet.

[1054] "Means for converting and organizing into a unified format" refers to techniques and methods for converting product information collected in different formats into a consistent format and organizing it in an orderly manner.

[1055] A "product comparison table" is data in a table format that displays multiple product information in a list format that makes it easy to compare them.

[1056] A "generative AI model" is an algorithm or program that uses artificial intelligence technology to generate text, and is used to generate product descriptions, etc.

[1057] A "purchase link" is a hyperlink to a web page that allows a user to purchase a product.

[1058] "Filtering" is the process of selecting data based on specific conditions.

[1059] "Sorting" is the operation of changing the order of data based on specific criteria.

[1060] An "interface" refers to the means or techniques by which a user interacts with a system, including graphical user interfaces (GUIs).

[1061] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet. The system is composed of a server, terminals, and users, and is described in detail below.

[1062] Server configuration and processing

[1063] The server automatically collects product information from multiple websites and databases using API calls and web scraping techniques, such as issuing HTTP requests and parsing the HTML files or JSON data received as responses to extract product information.

[1064] The server then converts the collected data into a unified format. This conversion process involves normalizing the data, such as unifying different JSON key names and converting price information into a uniform currency unit. For example, all price information obtained from multiple websites can be managed under a unified key called "price" and currency conversion can be performed.

[1065] Based on the organized data, the server generates a product comparison table, which includes product names, prices, key specifications, user reviews, etc. To display the table in a tabular format, an appropriate data structure such as a data frame is used.

[1066] Next, the server uses the generative AI model to generate a product description. By inputting the following prompt into the generative AI model, the server generates a sentence that describes the product's features and benefits.

[1067] Example prompt sentence:

[1068] "Collect and organize smartphone product information, and generate a comparison chart and compelling product descriptions. Required information includes product name, price, specifications, user reviews, and images. Include the features and benefits of each product in the description."

[1069] The generated content, such as a description, a product comparison chart, and a purchase link, is sent to the terminal by the server.

[1070] Terminal configuration and handling

[1071] When a user accesses the system, the terminal receives the data sent from the server. This terminal is the user's browser or application, and displays the received product comparison chart and testimonials in an easy-to-read format.

[1072] Specifically, it uses HTML and CSS to organize the display and provides functions for sorting and filtering products for easy viewing. For example, if a user selects "Price: Ascending," the device will sort the displayed product list from lowest to highest price.

[1073] User operations

[1074] Users can browse, filter, and sort product information through their devices. For example, by filtering by specific specifications, they can display only products that meet their needs. This allows users to quickly find the perfect product.

[1075] Furthermore, the user can click on the displayed purchase link to directly access the purchase page and proceed with the purchase process.

[1076] Specific examples

[1077] For example, when collecting smartphone information, the server retrieves it from each manufacturer's official website and major e-commerce platforms. The collected information is converted into a unified format and a comparison table is compiled of information such as screen size, battery capacity, and camera resolution. The generative AI model is then used to generate a description such as, "This smartphone is equipped with a high-resolution camera and can take professional-quality photos." The server then generates a purchase link for each product and associates it with each target product.

[1078] This system automates the entire process from collecting product information to purchasing, improving user convenience and enabling the prompt provision of the latest information.

[1079] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1080] Step 1: Data collection

[1081] The server automatically collects product information from multiple websites and databases. It uses a list of URLs from each website and database as input. Specifically, the server issues an HTTP request and extracts product information by parsing the HTML file or JSON data received as a response. This process obtains data such as product name, price, specifications, user reviews, and images. The collected raw data is generated as output.

[1082] Step 2: Cleanse and transform the data

[1083] The server converts the collected raw data into a unified format. The raw data obtained in step 1 is used as input. Specific operations include normalizing the data by unifying different JSON key names and converting price information into a single currency unit. For example, "price_usd" and "price_euro" are unified into "price" and converted to USD. Data in a unified format is generated as output.

[1084] Step 3: Generate a product comparison table

[1085] The server generates a product comparison table based on the unified format data. The unified format data generated in step 2 is used as input. Specifically, it organizes product names, prices, key specifications, user review ratings, etc. in a table format. Using an appropriate data structure such as a data frame format makes table generation easy. A product comparison table is generated as output.

[1086] Step 4: Generate a testimonial

[1087] The server uses a generative AI model to generate product descriptions. The input is the data for each product listed in the product comparison chart and a prompt. Specifically, the prompt is input into the generative AI model to generate a description that explains the product's features and benefits. For example, the prompt could be "This smartphone is equipped with a high-resolution camera, allowing you to take professional-quality photos." The output is a description of each product.

[1088] Step 5: Generate a purchase link

[1089] The server automatically generates a purchase link for each product based on links from the collected website or e-commerce platform. The input is the data for each product and the URL template for the purchase page. Specifically, the purchase link is generated by embedding the product ID and parameters in the URL template. For example, a link is generated by embedding the ID "12345" in the template "https: / / example.com / product / {product_id}". The output is a purchase link for each product.

[1090] Step 6: View the data

[1091] When a user accesses the system, the terminal receives the product comparison table, testimonials, and purchase links sent from the server. The data from the server is used as input. Specifically, the terminal uses HTML and CSS to display the received data in an easy-to-read format. For example, the product comparison table is displayed in a table format, with testimonials and purchase links appropriately arranged. As output, the information is displayed on the user's screen.

[1092] Step 7: Filtering and Sorting

[1093] The user can filter and sort product information through the terminal. The filter and sort conditions selected by the user are used as input. Specifically, the terminal dynamically updates the displayed product list using JavaScript or other methods. For example, if the user selects "Price: Ascending", the terminal sorts and displays products in ascending order of price. The output displays a product list filtered and sorted according to the user's selection.

[1094] (Application example 1)

[1095] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1096] There is a need to efficiently collect and organize product information on the Internet and provide users with fast and accurate product comparisons and introductions. With current systems, collecting, organizing, comparing, and introducing this information takes a lot of time and effort, and it is difficult for users to find the information they are looking for. For this reason, it is necessary to automate the process from collecting product information to purchasing, thereby improving user convenience.

[1097] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1098] In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and generating a product comparison table, means for generating text introducing the features and advantages of the products using a generative AI model, means for displaying content including the generated text and purchase links, and means for providing filtering and sorting functions. This allows users to efficiently collect product information and browse the organized product comparison table to quickly compare and select products and choose the most suitable product.

[1099] "On the Internet" refers to websites and online databases accessible via the Internet.

[1100] "Product information" refers to information necessary for consumers to evaluate a product, such as product name, price, specifications, user reviews, images, and purchase links.

[1101] "Automatic collection means" refers to the process of using programs or scripts to obtain product information without human intervention through API calls or web scraping technology.

[1102] "Means for organizing and generating a product comparison table" refers to the process of converting collected product information into a unified format and compiling it into a form that allows the features of multiple products to be compared.

[1103] A "generative AI model" refers to a type of artificial intelligence that uses machine learning techniques to generate text.

[1104] "Means for generating text introducing product features and benefits" refers to the process of using a generative AI model to automatically generate text describing the features and benefits of each product.

[1105] "Generated Text" refers to text describing product features and benefits created using a generative AI model.

[1106] "Content with a purchase link" refers to information that includes a link for users to purchase the product along with generated text and detailed product information.

[1107] "Means for displaying" refers to the method for displaying the collected and organized product information and generated text on the user's device.

[1108] "Means for providing filtering and sorting functionality" refers to functionality that allows users to narrow down product information by criteria such as price or specifications, or sort it in a specific order.

[1109] This invention is a system for automating the collection, organization, comparison, and introduction of product information from the Internet. This system consists of three elements: a server, a terminal, and a user. Each element is described in detail below.

[1110] Users access the system mainly using terminals such as smartphones and personal computers. When a user accesses the system, the terminal sends a request for product information to the server. The server automatically collects product information from various websites and online databases on the Internet.

[1111] The server primarily uses the following hardware and software:

[1112] Hardware: Regular servers (on-premise or cloud-based)

[1113] Software: Node.js, axios, generative AI model (e.g., OpenAI's GPT-3)

[1114] First, the server uses programs and scripts to call APIs and web scraping techniques to collect information such as product names, prices, specifications, user reviews, images, and purchase links. The collected product information is then converted into a unified format within the server. Next, a product comparison table is generated based on this data.

[1115] The server then uses the generative AI model to generate sentences that explain the features and benefits of each product. Specifically, the server provides the following prompt sentences as input to the generative AI model:

[1116] Product name: [Product name]

[1117] Price: [Price]

[1118] Specs: [Specs]

[1119] Review: [Review]

[1120] Image URL: [Image URL]

[1121] Purchase link: [Purchase link]

[1122] Generate a testimonial about the features and benefits of this product.

[1123] For example, a description such as "This smartphone is equipped with a high-resolution camera and can take professional-quality photos" is generated based on the smartphone's information. The generated content, including the purchase link, is then sent to the device.

[1124] The terminal displays the product comparison chart and product descriptions sent from the server to the user. The user can filter and sort products based on the displayed information. This filtering and sorting function allows the user to sort products by lowest price or narrow down products by specific specifications.

[1125] Through the above process, users can efficiently and quickly compare and select products, and choose the most suitable one. This system can greatly improve user convenience by automating the entire process from collecting product information to purchasing.

[1126] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1127] Step 1:

[1128] The server receives product information requests from users. The input is the product information request sent by the user through the terminal. The output is the preparation of product information collection on the Internet based on the request.

[1129] Step 2:

[1130] The server automatically collects product information from various websites and online databases on the Internet. Specifically, it uses programs and scripts to call APIs and web scraping techniques. The input is the URL of the website or database to be collected. The output is the collected raw product information data.

[1131] Step 3:

[1132] The server converts the collected product information into a unified format. Specifically, it organizes the data into the form of product name, price, specifications, user reviews, image URL, purchase link, etc. The input is the collected raw product information data. The output is the product information converted into a unified format.

[1133] Step 4:

[1134] The server generates a product comparison table based on the product information converted into a unified format. The input is formatted product information data. The output is a product comparison table in a format that allows multiple products to be compared.

[1135] Step 5:

[1136] The server uses a generative AI model to generate text that describes the features and benefits of each product. Specific prompts are input to the generative AI model to generate the text. The inputs are detailed information about each product and the following prompts:

[1137] Product name: [Product name]

[1138] Price: [Price]

[1139] Specs: [Specs]

[1140] Review: [Review]

[1141] Image URL: [Image URL]

[1142] Purchase link: [Purchase link]

[1143] Generate a testimonial about the features and benefits of this product.

[1144] The output is a description of the features and benefits of the generated product.

[1145] Step 6:

[1146] The server integrates the generated testimonials and purchase links into a product comparison table and prepares it for transmission to the terminal. The input is the product comparison table, testimonials, and purchase links. The output is the integrated content to be transmitted to the terminal.

[1147] Step 7:

[1148] The terminal displays the product comparison table and product introductions sent from the server to the user. The input is the integrated content sent from the server. The output is the product comparison table and product introductions that the user can view.

[1149] Step 8:

[1150] Users can filter and sort the product information displayed through their devices. The input is the filtering and sorting conditions set by the user. The output is a product comparison table updated based on the conditions.

[1151] Step 9:

[1152] The user can select the most suitable product and proceed with the purchase procedure directly from the purchase link of the selected product. The input is the purchase link of the product selected by the user. The output is a transition to an external site where the purchase procedure is carried out.

[1153] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1154] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet, and aims to realize personalized product recommendations by combining it with an emotion engine that recognizes user emotions. This system is composed of a server, terminals, and users.

[1155] The server automatically collects product information from multiple websites and databases. Specifically, it uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images. The server then converts the collected information into a unified format and generates a product comparison table.

[1156] Next, the server uses the generative AI model to generate text describing the features and benefits of each product, highlighting the product's appeal to users. Furthermore, the server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase the product they're interested in.

[1157] When combined with an emotion engine, the server analyzes the user's facial expressions, voice, input text, etc. to recognize the user's emotions in real time. For example, if the user uses a webcam or microphone, the emotion engine obtains emotional data from the user's facial expressions and tone of voice. It also extracts and analyzes emotions from the text entered by the user. Product information and product descriptions are optimized based on the emotional data recognized by the emotion engine. For example, if the user is excited, it generates text that emphasizes the product's positive features. The emotion engine also integrates the user's purchase history with emotional data to recommend appropriate products.

[1158] The device receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application UI. The device also accepts user operations (filtering and sorting instructions) and performs corresponding data processing. For example, if the user selects "sort by price," the device sorts the product data by price and redisplays it. Furthermore, the device displays product recommendations suitable for the user based on the emotion data acquired by the emotion engine.

[1159] Users can view a product comparison chart displayed on their device to select the product that best suits them. They can also review the product details to understand the product's features and benefits. Recommendations based on the user's emotions allow for more personalized product selection. Finally, they can quickly purchase the product by clicking the purchase link.

[1160] As a specific example, when a user uses this system on a device with a webcam, the emotion engine recognizes emotions such as joy, excitement, and interest from the user's facial expressions. For example, if the user is smiling while browsing a product, the system generates a description that emphasizes the product's positive features. Conversely, if the user looks confused, the system displays detailed specifications and FAQ links to resolve the user's questions. This provides users with appropriate information tailored to their emotional state, making it easier for them to select the most suitable product.

[1161] This system not only automates the entire process from collecting product information to purchasing, but also takes user emotions into account to provide a richer and more personalized purchasing experience.

[1162] The processing flow will be explained below.

[1163] Program processing steps

[1164] Server-side processing steps

[1165] Step 1:

[1166] The server uses designated API endpoints and web scraping technology to collect product information from multiple sources on the Internet, including product names, prices, specifications, user reviews, and images.

[1167] Step 2:

[1168] The server converts the collected product information into a unified format, which includes data cleaning and normalization to ensure data from different sources is in a consistent format.

[1169] Step 3:

[1170] The server uses the organized product information to generate a product comparison table, which includes product names, prices, key specifications, and user reviews, and is organized to allow users to easily compare products.

[1171] Step 4:

[1172] The server uses the generative AI model to generate text that explains the features and benefits of each product. Specifically, it inputs product data into the AI ​​model and automatically generates an introductory text that conveys the product's appeal.

[1173] Step 5:

[1174] The server integrates the generated product description text into the data for each product, thereby adding the description text to the product data as detailed product information.

[1175] Step 6:

[1176] The server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase products they are interested in.

[1177] Step 7:

[1178] The server uses an emotion engine to analyze the user's facial expressions, voice, input text, etc. to recognize the user's emotions in real time, and optimizes product information and introductory text based on the emotion data.

[1179] Terminal processing steps

[1180] Step 1:

[1181] The device (user's browser or application) receives the product comparison chart, detailed descriptions, and purchase links sent from the server, analyzes the received data, and converts it into the format required for display.

[1182] Step 2:

[1183] The device displays product comparison tables and detailed descriptions as the UI of a web page or application. Specifically, it uses HTML and CSS to present product information to the user in a table or list format.

[1184] Step 3:

[1185] The terminal accepts user operations (filtering and sorting instructions) and performs the corresponding data processing. For example, if the user selects "sort by price," the terminal sorts the product data by price and redisplays it.

[1186] Step 4:

[1187] The device transmits the user's facial expressions and voice to an emotion engine that analyzes the user's emotions in real time. For example, it analyzes data acquired through a webcam or microphone to recognize the user's emotional state.

[1188] Step 5:

[1189] The device will then display appropriate product recommendations based on the recognized emotion data, emphasizing the positive aspects if the user is excited and providing detailed explanations if the user is confused.

[1190] User processing steps

[1191] Step 1:

[1192] Users can view a product comparison chart displayed on their device, compare the prices, specifications, and user reviews of each product, and consider which product best suits their needs.

[1193] Step 2:

[1194] The user checks the detailed product description displayed on the device to deepen their understanding of the product's features and advantages, for example, by referring to the product's advantages and unique features.

[1195] Step 3:

[1196] The user clicks on the purchase link and is taken to the e-commerce site, where they can proceed with the purchase. The purchase link takes the user directly to the purchase page, allowing for quick purchases.

[1197] Step 4:

[1198] Users can continue to check the details of the products they are interested in and, if necessary, refer to additional information and product recommendations provided by the emotion engine. The emotion engine analyzes the user's real-time emotional state and provides personalized information, making the purchasing experience richer and more efficient.

[1199] This system automates the entire process from collecting product information to making a purchase, and by taking into account the user's emotions, it is possible to provide a more personalized purchasing experience.

[1200] Example 2

[1201] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1202] Conventional online shopping systems have limitations in their functionality for aggregating and comparing information on products that users are interested in. In addition, product descriptions are standardized and lack personalization based on individual users' preferences and emotions. This has led to problems such as users being unable to select the most suitable product, which reduces their motivation to purchase.

[1203] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1204] In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and converting it into a unified format, means for generating a product comparison table, means for generating text introducing the features and advantages of products using a generative AI model, means for displaying content including the generated text and purchase links, means for analyzing user emotions in real time, and means for presenting optimal product information based on the emotion data, thereby enabling the provision of personalized product information for users and efficient product selection.

[1205] The "Internet" is a global information and communications network that connects computer networks around the world.

[1206] "Product information" refers to data about the characteristics and features of a product, such as the product name, price, specifications, user reviews, and images.

[1207] "Collection" is the process of obtaining and gathering specific information.

[1208] "Organization" is the process of arranging acquired data based on certain rules and standards to make it easier to view and use.

[1209] A "uniform format" is a method for aligning information into a certain format or structure.

[1210] A "product comparison table" is a table that displays the characteristics of multiple products in a list format to make it easier to compare them.

[1211] A "generative AI model" is a computational method or model that uses artificial intelligence techniques to automatically perform specific tasks.

[1212] "Sentence generation" is the process by which a computer automatically creates text using natural language.

[1213] A "purchase link" is a web link that a user can click to purchase an item.

[1214] "Content" is a general term for information displayed on a web page or application.

[1215] "Display" is the process of visually presenting information to a user.

[1216] "Real-time emotion analysis" is the process of analyzing a user's facial expressions, voice, text, etc. in real time to detect their emotional state.

[1217] "Emotion data" is information relating to the user's emotional state.

[1218] "Presenting optimal product information" is the process of suggesting the most suitable product information for the user based on the user's emotional state and other data.

[1219] This invention relates to a system for automatically collecting, organizing, comparing, and introducing product information from the Internet. Furthermore, by combining it with an emotion engine that recognizes user emotions, it aims to realize personalized product recommendations. This system consists of a server, a terminal, and a user.

[1220] The server automatically collects product information from multiple websites and databases. Specifically, it uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images. For example, when collecting product information from Amazon or Rakuten Ichiba, the server uses those APIs. The collected information is converted into a unified format on the server side. This unifies the different data formats from each site and ensures data consistency.

[1221] Next, the server generates a product comparison table based on the product information converted into a unified format. This comparison table displays each product's price, specifications, user reviews, and other information in a list format. The server then uses a generative AI model to generate text that explains the features and benefits of each product. To do this, it issues a prompt to the generative AI model. As a concrete example, the prompt used is, "Generate a text that introduces the benefits of the latest smartphone."

[1222] In addition, the server automatically generates a purchase link for each product and adds it to the product data, allowing users to quickly purchase products they are interested in. Using an emotion engine, the server analyzes the user's facial expressions, voice, and input text to obtain emotional data in real time. If the user is using a webcam or microphone, the emotion engine analyzes emotions from the user's facial expressions and tone of voice. Based on this emotional data, the server presents optimal product information.

[1223] The terminal receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application user interface. Furthermore, the terminal can redisplay the product data in response to user operations (filtering or sorting instructions). For example, if the user selects "sort by price," the terminal sorts and redisplays the product data in price order. In addition, the terminal displays recommended products that are most suitable for the user based on the emotion data acquired by the emotion engine.

[1224] Users can view a product comparison chart displayed on their device to select the product that best suits them. They can then review the product details to understand the product's features and benefits. Recommendation information based on emotional data is provided, enabling a more personalized product selection. Finally, users can quickly purchase the product by clicking the purchase link for the product that interests them.

[1225] As a concrete example, when a user uses this system with a device equipped with a webcam, the emotion engine recognizes the user's emotions from their facial expressions. For example, if the user is smiling while browsing a product, the system generates a description that emphasizes the product's positive features. Conversely, if the user looks confused, the system displays detailed specifications and FAQ links to resolve the user's questions.

[1226] This system automates the entire process from collecting product information to purchasing, and makes it possible to provide a personalized purchasing experience that takes user emotions into consideration.

[1227] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1228] Step 1:

[1229] The server collects product information from multiple websites and databases on the Internet. Specifically, it uses API calls and web scraping technology. For example, the server retrieves data such as product names, prices, specifications, user reviews, and images from specific websites. The input is raw data from websites and databases, and the output is the collected raw product information data.

[1230] Step 2:

[1231] The server organizes the collected product information and converts it into a unified format. Specifically, it parses different data formats (e.g., JSON, HTML) and converts them into a consistent format (e.g., CSV, database entries). It also cleans up missing values ​​and duplicate data. The input is the raw data of the collected product information, and the output is the product information converted into a unified format.

[1232] Step 3:

[1233] The server generates a product comparison table based on the product information converted into a unified format. Specifically, it creates a table that displays information such as the price, specifications, and user reviews of each product in a list format. This table is generated in Excel file or HTML format. The input is the product information converted into a unified format, and the output is a product comparison table.

[1234] Step 4:

[1235] The server uses the generative AI model to generate sentences that explain the features and benefits of each product. Specifically, it issues a prompt to the generative AI model: "Generate a sentence that introduces the benefits of the latest smartphone." The generated sentences are saved in JSON format. The inputs are the prompt and product information, and the output is the generated product description sentence.

[1236] Step 5:

[1237] The server uses an affiliate program to automatically generate a purchase link for each product. Specifically, it accesses the affiliate programs of Amazon and Rakuten Ichiba and obtains the URL for each product. This is then added to the product data. The input is product information and data from the affiliate program, and the output is the product data with the product purchase link added.

[1238] Step 6:

[1239] The server uses the emotion engine to analyze the user's facial expressions, voice, and input text to obtain emotion data. Specifically, when the user uses a webcam or microphone, the emotion engine analyzes the user's facial expressions and tone of voice in real time. The input is the user's facial expressions, voice, and input text, and the output is emotion data.

[1240] Step 7:

[1241] The device receives the product comparison chart, detailed descriptions, and purchase links sent from the server and displays them as a web page or application user interface. Furthermore, the device redisplays the product data in response to user operations (filtering and sorting instructions). The input is data from the server and user operations, and the output is the product data displayed in the updated UI.

[1242] Step 8:

[1243] The user looks at the product comparison table displayed on the device and selects the product that best suits them. They check the product details and understand the product's features and benefits. They click on the purchase link for the product that interests them and quickly purchase the product. The input is the displayed product data, and the output is the user's selection and purchase operation.

[1244] (Application example 2)

[1245] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1246] Conventional online shopping sites and advertising systems provide uniform information without considering the user's feelings, making it difficult to recommend optimal products for the user and failing to fully stimulate purchasing motivation. In addition, providing a large amount of information at once confuses the user, making it take a long time to find the optimal product.

[1247] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for automatically collecting product information from the Internet, means for organizing the collected product information and generating a product comparison table, means for generating text introducing product features and advantages using a generative AI model, means for recognizing user emotions and optimizing product information and introduction text based on the emotions, and means for displaying content including the generated text and purchase links. This allows users to receive personalized product recommendations in a more emotionally satisfying manner, increasing their desire to purchase and enabling them to find the best product efficiently and quickly.

[1248] "Means for automatically collecting product information from the Internet" refers to a function that uses API calls and web scraping technology to obtain data such as product names, prices, specifications, user reviews, and images from multiple websites and databases.

[1249] The "means for organizing collected product information and generating a product comparison table" is a function that converts collected product information into a unified format and creates a product comparison table organized in an easy-to-compare format.

[1250] "Means for generating text introducing the features and benefits of a product using a generative AI model" refers to a function that uses a generative AI model to generate natural language text to explain the features and benefits of a product based on collected and organized product information.

[1251] "Means for recognizing the user's emotions and optimizing product information and descriptions based on those emotions" refers to a function that analyzes emotions from the user's facial expressions, voice, input text, etc., and optimizes product information and descriptions based on that emotional data.

[1252] The "means for displaying the content including the generated text and the purchase link" is an interface having a function for displaying the content including the generated text and the purchase link to the user.

[1253] This invention is a system that automatically collects product information from the Internet and provides personalized product recommendations using an emotion engine. This system is composed of a server, terminals, and users.

[1254] Server Roles

[1255] The server has the following main functions:

[1256] 1. Collecting product information:

[1257] The server uses API calls and web scraping technology to automatically collect data such as product names, prices, specifications, user reviews, and images from multiple websites and databases.

[1258] The collected information is stored in a database.

[1259] 2. Organizing product information and generating product comparison tables:

[1260] The collected product information is converted into a unified format and a product comparison table is generated.

[1261] 3. Generating introductory text using a generative AI model:

[1262] Using a generative AI model, text introducing product features and benefits is generated based on collected and organized data.

[1263] The generated text is automatically integrated with the data for each product.

[1264] 4. Use of Emotion Engine:

[1265] The server analyzes the user's facial expressions, voice, input text, etc., and recognizes the user's emotions in real time.

[1266] If the user is excited, it generates text that emphasizes the product's positive features, and if the user is confused, it displays detailed specifications and FAQ links.

[1267] Device Role

[1268] The device provides the user with the information sent by the server:

[1269] 1. Displaying information:

[1270] Show users a product comparison chart, detailed descriptions, and purchase links.

[1271] To display product recommendation information optimized based on a user's emotions.

[1272] 2. Accepting user operations:

[1273] It provides an interface for users to filter and sort product information and responds to user actions.

[1274] User Roles

[1275] Users receive information based on their emotions and make purchasing decisions:

[1276] 1. Check and compare information:

[1277] The user checks the product comparison chart displayed on the device and understands the features and advantages of the products.

[1278] 2. Purchasing behavior:

[1279] The user selects the most suitable product and purchases it by clicking the purchase link.

[1280] Hardware and software used

[1281] Hardware:

[1282] Smartphone (with camera and microphone)

[1283] software:

[1284] Frontend: React Native

[1285] Backend: Node.js + Express

[1286] Database: MongoDB

[1287] Emotion Recognition API: General facial recognition and voice analysis API

[1288] Generative AI Model: A general generative AI model

[1289] Specific examples

[1290] If a user smiles excitedly while browsing products in the gadget category, the emotion engine recognizes this smile and sends it to the server as an "excited" state. The server then receives this data and generates a prompt for the generative AI model, which then generates a positive description such as, "This gadget is equipped with the latest technology, has amazing performance, and is especially recommended for game enthusiasts!" and displays it on the device.

[1291] Prompt Sentence Examples

[1292] The user is browsing products in the Gadgets category. Their current emotion is "Excited." Generate a description that highlights the positive features of the following product:

[1293] Product Name: Smart Watch Pro

[1294] Price: 25,000 yen

[1295] Specifications: Built-in GPS, waterproof, long battery life

[1296] User review: "Very easy to use!"

[1297] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1298] Step 1: Gather product information

[1299] The server automatically collects data such as product name, price, specifications, user reviews, and images from multiple websites and databases on the Internet using API calls and web scraping technology. This data is then temporarily stored in a database on the server. The input is the website URL or API endpoint, and the output is the raw data of the retrieved product information.

[1300] Step 2: Organize product information and generate a product comparison table

[1301] The server converts the collected product information into a unified format and generates a product comparison table. Here, data cleansing and normalization are performed to make it easier for users to compare. The input is the collected raw product information data, and the output is a comparison table in a unified format.

[1302] Step 3: Generate an introduction

[1303] The server uses a generative AI model to generate text introducing the product's features and benefits based on the collected and organized data. The generated text is automatically integrated with the data for each product. The input is organized product information and a product comparison table, and the output is a text created by the generative AI model that explains the product's features.

[1304] Step 4: Real-time emotion recognition

[1305] The device uses the smartphone's camera and microphone to capture the user's facial expressions and voice. The emotion recognition API analyzes the user's emotions from this data and obtains emotional data in real time. The input is the captured image and audio, and the output is the analyzed emotional data.

[1306] Step 5: Optimize your text based on sentiment

[1307] The server uses the emotion data obtained from the emotion recognition API to optimize the generated product description. For example, if the user is excited, it generates a description that emphasizes the product's positive features. The input is the emotion data and the generated description, and the output is the optimized description.

[1308] Step 6: Displaying Content

[1309] The terminal displays the generated content to the user, such as a product comparison chart, detailed descriptions, and purchase links. The input is the optimized text and other product data sent from the server, and the output is the content displayed on the user's screen.

[1310] Step 7: Accepting user actions

[1311] The terminal provides an interface for users to filter and sort product information, accepts user operations, and updates the display based on the user operations. The input is the filter and sort conditions provided by the user, and the output is the updated product information after filtering and sorting.

[1312] Step 8: Making a purchase

[1313] Based on the optimized information displayed on the device, the user clicks on the purchase link to purchase the product. The input is the displayed product information and the purchase link, and the output is the user's purchasing behavior after going through the purchasing process.

[1314] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1315] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1316] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1317] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1318] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1319] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1320] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1321] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1322] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1323] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1324] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1325] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1326] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1327] 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.

[1328] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1329] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1330] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1331] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1332] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1333] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1334] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1335] The following is further disclosed regarding the above embodiment.

[1336] (Claim 1)

[1337] A means for automatically collecting product information from the Internet;

[1338] A means for organizing the collected product information and generating a product comparison table;

[1339] A means of generating text introducing product features and benefits using a generative AI model;

[1340] a means for displaying the generated content including the text and the purchase link;

[1341] A system including:

[1342] (Claim 2)

[1343] 10. The system of claim 1, further comprising means for automatically integrating product description text generated using the generative AI model into data for each product.

[1344] (Claim 3)

[1345] 10. The system of claim 1, further comprising means for providing an interface for a user to filter and sort the product information.

[1346] "Example 1"

[1347] (Claim 1)

[1348] A means for automatically collecting product information from the Internet;

[1349] A means of converting and organizing collected product information into a unified format;

[1350] A means for generating a product comparison table;

[1351] A means of generating text introducing product features and benefits using a generative AI model;

[1352] a means for displaying the generated content including the text and the purchase link;

[1353] A system including:

[1354] (Claim 2)

[1355] 10. The system of claim 1, further comprising means for automatically integrating product description text generated using the generative AI model into data for each product.

[1356] (Claim 3)

[1357] 10. The system of claim 1, further comprising means for providing an interface for a user to filter and sort the product information.

[1358] "Application Example 1"

[1359] (Claim 1)

[1360] A means for automatically collecting product information from the Internet;

[1361] A means for organizing the collected product information and generating a product comparison table;

[1362] A means of generating text introducing product features and benefits using a generative AI model;

[1363] a means for displaying the generated content including the text and the purchase link;

[1364] means for providing filtering and sorting functionality;

[1365] A system including:

[1366] (Claim 2)

[1367] 10. The system of claim 1, further comprising means for automatically integrating product description text generated using the generative AI model into data for each product.

[1368] (Claim 3)

[1369] 10. The system of claim 1, further comprising means for providing an interface for a user to filter and sort the product information.

[1370] "Example 2: Combining Emotion Engines"

[1371] (Claim 1)

[1372] A means for automatically collecting product information from the Internet;

[1373] A means of organizing collected product information and converting it into a unified format,

[1374] A means for generating a product comparison table;

[1375] A means of generating text introducing product features and benefits using a generative AI model;

[1376] a means for displaying the generated content including the text and the purchase link;

[1377] A means for analyzing user emotions in real time;

[1378] A means for presenting optimal product information based on emotion data;

[1379] A system including:

[1380] (Claim 2)

[1381] 10. The system of claim 1, further comprising means for automatically integrating product description text generated using the generative AI model into data for each product.

[1382] (Claim 3)

[1383] 10. The system of claim 1, further comprising means for providing an interface for a user to filter and sort the product information.

[1384] "Application example 2 when combining emotion engines"

[1385] (Claim 1)

[1386] A means for automatically collecting product information from the Internet;

[1387] A means for organizing the collected product information and generating a product comparison table;

[1388] A means of generating text introducing product features and benefits using a generative AI model;

[1389] A means for recognizing user emotions and optimizing product information and descriptions based on the emotions;

[1390] a means for displaying the generated content including the text and the purchase link;

[1391] A system including:

[1392] (Claim 2)

[1393] 10. The system of claim 1, further comprising means for automatically integrating product description text generated using the generative AI model into data for each product.

[1394] (Claim 3)

[1395] 10. The system of claim 1, further comprising means for providing an interface for a user to filter and sort the product information. [Explanation of symbols]

[1396] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for automatically collecting product information from the Internet; A means for organizing the collected product information and generating a product comparison table; A means of generating text introducing product features and benefits using a generative AI model; a means for displaying the generated content including the text and the purchase link; A system including:

2. The system of claim 1 , further comprising means for automatically integrating product description text generated using the generative AI model into data for each product.

3. 10. The system of claim 1, further comprising means for providing an interface for a user to filter and sort the product information.

Images