System

Abstract

A system is provided.SOLUTION: The system includes a means for inputting selection conditions of a commodity desired by a user, a communication means for collecting data related to the commodity based on the inputted selection conditions, an artificial intelligence means for analyzing the collected data and evaluating and ranking the commodity, a means for presenting the evaluated and ranked commodity list to the user, and a means for attaching additional information including'a caution point at purchase','a lowest price site', and'a recommendation function' related to each commodity to the presented commodity list.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] Conventional online shopping systems have the problem that it is difficult for users to choose the right product due to the large number of similar products and the unreliable reviews. Furthermore, there is a risk that users will purchase the wrong product due to false product descriptions and exaggerated advertising. There is a need for a system that solves these problems and allows users to more easily select the best product based on reliable information. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for a user to input selection criteria for a desired product, a communication means for collecting data related to the products based on the input selection criteria, an artificial intelligence means for analyzing the collected data and evaluating and ranking the products, and a means for presenting a list of evaluated and ranked products to the user. Furthermore, the presented product list includes additional information about each product, including "purchase precautions," "cheapest sites," and "recommended features." The present invention allows users to easily input detailed criteria and efficiently select the optimal product with the help of AI.

[0006] "User" refers to a person who searches for and selects products using this system.

[0007] "Selection conditions" refer to the criteria or conditions that a user inputs regarding the characteristics or specifications of the product that he or she desires.

[0008] "Communication means" refers to the technological means for collecting data over a network or exchanging information with other devices.

[0009] "Artificial intelligence means" refers to AI engines and algorithms that analyze collected data and evaluate and rank the most suitable products based on user selection criteria.

[0010] "Product list" refers to a collection of information that displays rated and ranked products in a list format.

[0011] "Purchase precautions" refers to important information and risk-related notes that should be considered when purchasing a product.

[0012] The "cheapest site" refers to the website that sells the searched product at the lowest price.

[0013] "Recommended features" refers to information about product features or convenience that AI has determined to be particularly noteworthy.

[0014] A "review site" refers to a website where consumers post reviews and opinions of products they have purchased.

[0015] "E-commerce Site" means a website that allows you to purchase products online.

[0016] "Product review site" refers to a website where users post reviews and ratings of products.

[0017] "Natural language processing means" refers to technical means for analyzing text data such as word-of-mouth and reviews and extracting information. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

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

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

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

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0033] 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.

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

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This invention is a system that allows users to select the most suitable product when shopping online. It uses AI to analyze the selection criteria of the product desired by the user and presents the most suitable product. This reduces the difficulty of product selection in conventional online shopping and the risk of mistaken purchases caused by false labeling and exaggerated advertising.

[0040] System Configuration

[0041] The system of the present invention is composed of a user terminal, a server, and a communication means. The role and operation of each component will be explained in detail below.

[0042] User's device

[0043] 1. User: Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.).

[0044] 2. Terminal: Displays the interface and allows the user to select a product category.

[0045] 3. User: Select a product category (e.g., air purifier).

[0046] 4. Terminal: Based on the selected category, a detailed selection criteria input form will be displayed.

[0047] 5. User: Enter detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.).

[0048] server

[0049] 6. Terminal: Sends the entered selection criteria data to the server.

[0050] 7. Server: Receives the selection conditions and starts the AI ​​engine.

[0051] 8. Server: The AI ​​engine collects relevant product data from multiple data sources (word-of-mouth sites, e-commerce sites, product review sites, etc.) based on the selection criteria.

[0052] 9. Server:

[0053] Natural language processing (NLP) technology is used to analyze collected word-of-mouth and review text data.

[0054] Products are scored based on the analysis results and a ranking is generated.

[0055] Product list presentation

[0056] 10. Server: Generates a scored and ranked product list and adds additional information for each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features."

[0057] 11. Server: Sends the generated product list and additional information to the terminal.

[0058] 12. Terminal: Displays the product list and additional information in a user interface.

[0059] 13. User: Check the presented products and select and purchase the most suitable product.

[0060] Specific examples

[0061] For air purifiers

[0062] Starting the system

[0063] 1. User: Open "EC Sensei" in a web browser.

[0064] 2. Device: Display the homepage.

[0065] Condition Input Phase

[0066] 3. User: Select the Air Purifier category.

[0067] 4. Device: Display the detailed conditions input form for the air purifier.

[0068] 5. User: Enter the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[0069] Product selection phase by AI

[0070] 6. Terminal: Sends condition data to the server.

[0071] 7. Server: Sends condition data to the AI ​​engine and begins collecting and analyzing product information.

[0072] 8. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites, and analyzes and scores it using NLP technology.

[0073] Optimal product presentation phase

[0074] 9. Server: Generates a list of optimal products and adds features such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[0075] 10. Server: Sends the product list to the terminal.

[0076] 11. Terminal: Displays product list and additional information.

[0077] 12. User: Selects the best product and decides to purchase.

[0078] This allows users to easily select the most suitable product based on reliable information. This specific embodiment supports the claims and clarifies the technical scope of the invention.

[0079] The processing flow will be explained below.

[0080] Step 1:

[0081] User: Open the "EC Sensei" application or website on your device.

[0082] Launch a web browser and enter the specified URL or tap the application icon.

[0083] Step 2:

[0084] Server: Receives user requests, generates HTML / CSS / JavaScript resources for the homepage, and sends them to the terminal.

[0085] Based on user requests, homepage data is dynamically generated and transmitted.

[0086] Step 3:

[0087] User: Select a product category (e.g., air purifier).

[0088] Click on the drop-down menu or icon to select the product category you want.

[0089] Step 4:

[0090] Server: Based on the selected category, a related detailed selection criteria input form is generated and sent to the terminal.

[0091] The input form corresponding to the product category is retrieved from the database, and the data required for displaying it is generated and sent.

[0092] Step 5:

[0093] User: Enter detailed selection criteria (e.g. price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[0094] Enter the condition in the input field and select an option.

[0095] Step 6:

[0096] Terminal: Organizes the entered selection criteria data and sends a request to the server in JSON format.

[0097] Converts form data into JSON format and sends a request to the specified API endpoint.

[0098] Step 7:

[0099] Server: Passes the received selection criteria data to the AI ​​engine and starts the data collection process.

[0100] Based on the conditions, it triggers an AI module to collect product-related information from multiple data sources.

[0101] Step 8:

[0102] Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[0103] Use APIs and scraping techniques to collect product information from designated data sources.

[0104] Step 9:

[0105] Server: Uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[0106] The NLP engine is activated to analyze the text data and extract important keywords and evaluation points.

[0107] Step 10:

[0108] Server: Based on the analysis results, the products are scored and a ranking is generated.

[0109] A scoring algorithm is applied to rank the products that best match the criteria.

[0110] Step 11:

[0111] Server: Generates a list of optimal products and adds additional information for each product, such as "things to note when purchasing," "cheapest site," and "recommended features."

[0112] Generate data in JSON format that includes relevant information in the product list.

[0113] Step 12:

[0114] Server: Sends the generated product list and additional information to the terminal.

[0115] The product list and related information are sent to the terminal and prepared for display.

[0116] Step 13:

[0117] Terminal: Analyzes the received product list and additional information and displays it on the user interface.

[0118] Convert the JSON data into HTML and display the information to the user.

[0119] Step 14:

[0120] User: Check the presented products, select the most suitable product and purchase it.

[0121] Based on the product information provided, select the desired product and proceed with the purchase.

[0122] This allows users to input detailed product selection criteria and efficiently select the most suitable products with the help of AI.

[0123] Example 1

[0124] 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."

[0125] Today's consumers often find it difficult to select the best product from the numerous product options available when shopping online. There is also the risk of making a mistaken purchase due to false and exaggerated advertising. Furthermore, checking a large number of customer testimonials and reviews one by one is extremely time-consuming and labor-intensive. These issues often make it difficult for consumers to choose the right product.

[0126] 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.

[0127] In this invention, the server includes a means for inputting selection criteria for products desired by the user, a communication means for collecting information about the products based on the input selection criteria, and an artificial intelligence means for analyzing the collected information and evaluating and ranking the products. This reduces the difficulty of product selection and the risk of making an erroneous purchase, and enables users to easily select the most suitable product based on reliable information.

[0128] "Means for users to input selection criteria for desired products" refers to means for providing an interface that allows users to input the characteristics and requirements of desired products using devices such as PCs or smartphones.

[0129] "Communication means for collecting information about products based on input selection criteria" refers to a network communication device and protocol for collecting information about products from various data sources on the Internet based on criteria specified by the user.

[0130] "Artificial intelligence means for analyzing collected information and evaluating and ranking products" refers to an AI system that includes machine learning algorithms and natural language processing technology to automatically analyze collected data and statistically analyze the characteristics and evaluations of each product to set a rank.

[0131] A "means for presenting a rated and ranked product list to a user" is a display device or interface that displays the AI-ranked product list in a user-friendly format, allowing the user to easily select the most suitable product.

[0132] "A means for adding additional information to the presented product list, including 'points to note when purchasing,' 'lowest price information,' and 'recommended features' for each product" refers to an information processing system that automatically generates and adds to the evaluated product list information such as points to note when purchasing each product, price comparison information with other sales sites, and features that are particularly superior in comparison with other products.

[0133] The "means for allowing a user to select a category" is a means for providing an interface for the user to select a category of a product to be searched for.

[0134] The "means for displaying related product selection conditions based on the selected category" is a means for providing an interface for inputting detailed selection conditions for the relevant product according to the category selected by the user.

[0135] "Means for collecting data from review sites, e-commerce sites, and product rating sites" refers to a data acquisition mechanism using crawling technology and APIs to efficiently collect detailed product data from multiple sources on the Internet.

[0136] "Natural language processing means for analyzing collected data" refers to an analysis system that includes natural language processing technology for analyzing collected text data (word of mouth, reviews, etc.) and extracting and structuring meaning from the data.

[0137] This invention is a system that allows users to select the most suitable product when shopping online. Specifically, the system inputs the selection criteria for the desired product, analyzes them using AI, and presents the most suitable product. This system is composed of a user terminal, a server, and communication means.

[0138] User's device

[0139] Device behavior

[0140] Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.). The user interface will be displayed, prompting the user to select a product category and displaying a form for entering detailed selection criteria. When the user enters detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.), the data will be sent to the server.

[0141] server

[0142] Server Operation

[0143] The server receives the selection criteria data sent from the device and activates the AI ​​engine. The AI ​​engine collects data from multiple data sources (e.g., word-of-mouth sites, e-commerce sites, product review sites) based on the selection criteria. The collected data is analyzed using natural language processing (NLP) technology to score and rank each product.

[0144] Product list presentation

[0145] Product proposals

[0146] The server generates a scored and ranked product list and adds additional information for each product, including "points to note when purchasing," "lowest price information," and "recommended features." This generated product list and additional information are sent to the terminal, which displays the product list and additional information on the user interface. The user can review the presented products and select the most suitable one.

[0147] Specific examples

[0148] For air purifiers

[0149] Starting the system

[0150] 1. The user opens "EC Sensei" in a web browser.

[0151] 2. The device displays the homepage.

[0152] Condition Input Phase

[0153] 3. The user selects the Air Purifier category.

[0154] 4. The device will display a form to input detailed conditions for the air purifier.

[0155] 5. The user enters the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[0156] Product selection phase by AI

[0157] 6. The device sends the condition data to the server.

[0158] 7. The server sends the condition data to the AI ​​engine and begins collecting and analyzing product information.

[0159] 8. The server collects data from word-of-mouth sites, e-commerce sites, and product review sites, and analyzes and scores it using NLP technology.

[0160] Optimal product presentation phase

[0161] 9. The server generates a list of optimal products and adds information such as "points to note when purchasing," "lowest price information," and "recommended features."

[0162] 10. The server sends the product list to the terminal.

[0163] 11. The device will display a list of products and additional information.

[0164] 12. The user selects the best product and decides to purchase.

[0165] Example prompts for generative AI models

[0166] Prompt statement:

[0167] Please describe the process by which a user would use the "EC Sensei" system to select the best air purifier based on the following selection criteria: price (up to ¥30,000), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (available), smartphone connectivity (available)

[0168] By inputting this prompt into a generative AI model, users can efficiently select the most suitable product.

[0169] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0170] Step 1:

[0171] The user opens the "EC Sensei" application or website on a device such as a PC or smartphone.

[0172] Input: Device launch and application or browser access.

[0173] Output: Application or browser homepage display.

[0174] Specific action: The user taps the application icon or enters the URL in the browser to open the site.

[0175] Step 2:

[0176] The terminal displays a home page and prompts the user to select a product category.

[0177] Input: The user's access request.

[0178] Output: Display of product category selection screen.

[0179] Specific operation: The device renders the "EC Sensei" homepage and offers product category selection.

[0180] Step 3:

[0181] The user selects a product category (e.g., air purifiers).

[0182] Input: A category selected by the user.

[0183] Output: Save selected category information.

[0184] Specific Action: User clicks on the Air Purifiers category.

[0185] Step 4:

[0186] The device will display a detailed selection criteria input form based on the selected category.

[0187] Input: Selected product category information.

[0188] Output: Display of detailed selection criteria input form.

[0189] Specific operation: The device renders and displays a detailed input form (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.) according to the selected category.

[0190] Step 5:

[0191] The user enters detailed selection criteria.

[0192] Input: Detailed selection criteria (e.g. price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), smartphone connectivity (yes)).

[0193] Output: Saves the entered selection criteria data.

[0194] Specific operation: The user enters values ​​or options for each condition item and presses the submit button.

[0195] Step 6:

[0196] The terminal transmits the input condition data to the server.

[0197] Input: Detailed selection criteria data.

[0198] Output: Sending data to the server.

[0199] Specific operation: The terminal generates an HTTP request and sends the condition data in JSON format to the server.

[0200] Step 7:

[0201] The server supplies the received selection condition data to the AI ​​engine.

[0202] Input: The received selection criteria data.

[0203] Output: Data feed to the AI ​​engine.

[0204] Specific operation: The server stores data in a database and provides that data as input to the AI ​​engine.

[0205] Step 8:

[0206] The server's AI engine collects data from multiple data sources (e.g., word-of-mouth sites, e-commerce sites, product review sites) based on selection criteria.

[0207] Input: Selection criteria data.

[0208] Output: Collected product data.

[0209] What it does: The AI ​​engine uses APIs and web scraping technology to collect relevant product data from designated sites.

[0210] Step 9:

[0211] The server uses natural language processing (NLP) techniques to analyze the collected data and score and rank the products.

[0212] Input: Collected text data (word of mouth, reviews, etc.).

[0213] Output: Analysis results and scored product list.

[0214] Specific operation: Text data is input into the NLP model, analyzed, and product characteristics and evaluation scores are calculated and ranked.

[0215] Step 10:

[0216] The server generates a list of rated and ranked products and adds additional information such as "things to note when purchasing," "lowest price information," and "recommended features."

[0217] Input: Scored product list.

[0218] Output: Final product list with additional information added.

[0219] Specific operation: The server generates information about each product, such as warnings, features, and price comparisons, and adds it to the scored list.

[0220] Step 11:

[0221] The server transmits the generated product list and additional information to the terminal.

[0222] Input: Final product list.

[0223] Output: Sending data to the terminal.

[0224] Specific operation: Generates an HTTP response to send the product list and additional information in JSON format to the terminal.

[0225] Step 12:

[0226] The terminal displays a list of products and additional information.

[0227] Input: Product list and additional information sent from the server.

[0228] Output: Display to the user interface.

[0229] What happens: The device renders the product list and additional information and displays it on the screen.

[0230] Step 13:

[0231] The user checks the products presented and selects and purchases the most suitable product.

[0232] Input: Displayed product list and additional information.

[0233] Output: Product selection and purchase confirmation.

[0234] Specific operation: The user checks the product list, clicks on the product they want to purchase, and completes the purchase process.

[0235] (Application example 1)

[0236] 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."

[0237] In conventional online shopping, users often face an overwhelming number of options when selecting the products they need, and are often misled by exaggerated advertising and false representations, making it difficult to select the optimal product. Furthermore, collecting and analyzing reliable information from multiple data sources requires a great deal of effort. There is an urgent need to provide a system that can solve these problems and enable users to quickly and reliably select the optimal product.

[0238] 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.

[0239] In this invention, the server includes: means for inputting selection criteria for a desired product by a user; communication means for collecting data on the products based on the input selection criteria; artificial intelligence means for analyzing the collected data and rating and ranking the products; means for presenting a list of rated and ranked products to the user; means for adding additional information to the presented product list, including "points to note when purchasing," "cheapest sites," and "recommended features," for each product; means for transmitting the product selection criteria input by the user via the user interface to the server; means for an artificial intelligence engine within the server to collect and analyze product information from a data source based on the user's input criteria; and means for displaying the analysis results on the user interface. This enables users to quickly and accurately select optimal products based on reliable data.

[0240] "Users" are individuals or groups who search for products through online shopping and consider purchasing them.

[0241] "Choice criteria" are the specific features or criteria that a user seeks when purchasing a product, such as price, functionality, or quality.

[0242] "Communication means" refers to the technology and infrastructure for sending and receiving data between the user's device and the server, including the Internet and wireless communications.

[0243] "Artificial intelligence tools" refer to algorithms and techniques used to analyze collected data and evaluate and rank products. Machine learning and deep learning techniques are primarily used.

[0244] "Rating and ranking" refers to scoring products based on user selection criteria and sorting them in an appropriate order. This process includes analyzing word-of-mouth and reviews.

[0245] "Presenting" is the act of showing a user a rated and ranked product list and its additional information.

[0246] "Purchase precautions" is information that indicates important points that users should consider when purchasing a product. For example, it includes product-specific drawbacks and usage precautions.

[0247] A "cheapest site" is a sales site where you can purchase a particular product at the lowest price.

[0248] "Recommended features" refer to the particularly outstanding functions or features of a particular product.

[0249] "User interface" refers to the screens and operating methods that allow users to directly interact with systems and applications.

[0250] "Data source" refers to an online source of information from which product information is collected, such as a word-of-mouth site, an e-commerce site, or a product review site.

[0251] "Natural language processing" is a technology that analyzes collected text data such as word-of-mouth and reviews and converts it into meaningful information. It mainly uses machine learning algorithms.

[0252] The system for carrying out this invention is composed of a user terminal, a server, and an infrastructure that connects these via communication means. Specifically, the system provides a user interface for users to select products, collects and analyzes data on the server side based on the selection criteria, and presents the most suitable products.

[0253] User's device

[0254] The terminal is an electronic device such as a smartphone, personal computer, or tablet, and provides an interface for users to input selection criteria for their desired products. The user uses this interface to input product categories and detailed selection criteria.

[0255] Specific example of input procedure

[0256] 1. User: Launch the EC Sensei application on their smartphone.

[0257] 2. Device: View product categories on the app homepage.

[0258] 3. User: Select the Air Purifier category.

[0259] 4. Device: Display the detailed conditions input form for the air purifier.

[0260] 5. User: Enter the desired price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity conditions.

[0261] Server Processing

[0262] The server activates an AI engine based on each user's input and collects product information from multiple data sources. It then uses natural language processing (NLP) technology to analyze text data from user reviews and scores products. Furthermore, the product list, which is scored based on the analysis results, includes additional information such as "things to note when purchasing," "the site with the lowest price," and "recommended features."

[0263] Software Configuration

[0264] AI Engine: Analyzes customer testimonials and reviews using deep learning frameworks such as TENSORFLOW® or PyTorch.

[0265] Framework: Uses Flask to manage communication between the server and the user interface.

[0266] Communication library: Uses the Python Requests library to send and receive data.

[0267] Specific examples of processing procedures

[0268] 1. Terminal: The selection criteria entered by the user are sent to the server.

[0269] 2. Server: Sends condition data to the AI ​​engine and begins collecting and analyzing product information.

[0270] 3. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites.

[0271] 4. Server: Analyzes data using natural language processing and scores products.

[0272] 5. Server: Generates a list of optimal products and adds features such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[0273] 6. Server: Sends the product list to the terminal.

[0274] 7. Terminal: Displays product list and additional information.

[0275] 8. User: Selects the best product and decides to purchase.

[0276] Prompt Sentence Examples

[0277] Conditions for purchase: The user opens the smartphone app "EC Sensei" and enters the details of the air purifier they require. The desired conditions are "price under 30,000 yen," "applicable area up to 20 tatami mats," "filter replacement frequency once a year," "humidification function," and "smartphone connectivity."

[0278] Input: Enter "air purifier," "under 30,000 yen," "20 tatami mats," "once a year," "humidifier function," and "smartphone connectivity" into the user interface.

[0279] Output: After AI analysis, a list of the "best air purifiers" is presented, along with reviews for each product, the lowest price store, and details of recommended features.

[0280] The above is a mode for carrying out the invention, and enables users to quickly and accurately select the most suitable product based on reliable data.

[0281] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0282] Step 1:

[0283] The user launches the EC Sensei application on their smartphone and selects a product category.

[0284] Input: A user launches the application and selects "Air Purifier" as the product category.

[0285] Output: A form for entering detailed conditions for the air purifier will be displayed on the terminal.

[0286] Step 2:

[0287] The user enters detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[0288] Input: The user enters conditions such as "price under 30,000 yen," "applicable area up to 20 tatami mats," "filter replacement frequency once a year," "humidification function included," and "smartphone connectivity available."

[0289] Output: The entered selection criteria are displayed on the terminal and are ready to be sent to the server.

[0290] Step 3:

[0291] The terminal transmits the input selection condition data to the server.

[0292] Input: Selection criteria data entered by the user.

[0293] Output: The condition data is sent to the server.

[0294] Step 4:

[0295] The server receives the condition data and starts the AI ​​engine.

[0296] Input: The submitted selection criteria data.

[0297] Output: The AI ​​engine is now up and running, ready to start collecting and analyzing product information from data sources.

[0298] Step 5:

[0299] The server collects product information from multiple data sources (word-of-mouth sites, e-commerce sites, product review sites).

[0300] Input: Product selection criteria specified by the AI ​​engine.

[0301] Output: Collected product information data. For example, text data of word-of-mouth and reviews.

[0302] Step 6:

[0303] The server analyzes the collected data using natural language processing (NLP) and scores the products.

[0304] Input: Collected text data of word-of-mouth and reviews.

[0305] The analysis involves extracting evaluation scores and important features from text data.

[0306] Output: Rating score and ranking for each product.

[0307] Step 7:

[0308] The server generates a list of rated and ranked products and attaches additional information including "things to note when purchasing," "cheapest sites," and "recommended features."

[0309] Input: Scoring results and additional information.

[0310] Output: A detailed product list.

[0311] Step 8:

[0312] The server transmits the generated product list and additional information to the terminal.

[0313] Input: A rated and ranked list of products and their additional information.

[0314] Output: The product list and additional information are sent to the terminal.

[0315] Step 9:

[0316] The terminal displays the product list and additional information on a user interface.

[0317] Input: Product list and additional information received from the server.

[0318] Output: A user interface with a list of products and their details.

[0319] Step 10:

[0320] The user checks the presented product list, selects the most suitable product, and decides to purchase it.

[0321] Input: Proposed product list and additional information.

[0322] Output: The product selected by the user and a purchase decision is made.

[0323] The above are the processing steps of the system program that realizes the application example.

[0324] 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.

[0325] The present invention relates to a system that allows users to efficiently select optimal products when shopping online. In particular, it aims to solve the problems of conventional systems by combining the user's selection criteria and emotional data to suggest optimal products. The present invention is realized using a user's terminal, a server, an artificial intelligence engine, and an emotional engine.

[0326] System Configuration and Operation

[0327] This system has the following configuration and operation.

[0328] User's device

[0329] 1. User: Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.).

[0330] 2. Terminal: Displays the interface and allows the user to select a product category.

[0331] 3. User: Select a product category (e.g., air purifier).

[0332] 4. Terminal: Based on the selected category, a detailed selection criteria input form will be displayed.

[0333] 5. User: Enter detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.).

[0334] Emotion Engine Operation

[0335] 1. Terminal: Collects the user's emotion data along with the input selection criteria and sends it to the server. Emotion data is extracted from sensor data such as camera, microphone, and touch input.

[0336] 2. Server: Analyzes the received emotional data and determines the user's emotional state.

[0337] Server and AI engine

[0338] 1. Server: Passes the selection criteria data and emotion data to the AI ​​engine and begins data collection and analysis.

[0339] 2. Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[0340] 3. Server: Using natural language processing (NLP) technology, the collected text data of user comments and reviews is analyzed, and product scores and rankings are generated taking into account sentiment data.

[0341] Product list presentation

[0342] 1. Server: Generates a scored and ranked product list and adds additional information for each product, including "Points to Note When Purchasing," "Lowest Price Site," and "Recommended Features." It also adjusts the priority and content of the information presented based on emotional data.

[0343] 2. Server: Sends the generated product list and additional information to the terminal.

[0344] 3. Terminal: displays the product list and additional information in a user interface.

[0345] 4. User: Check the presented products and select and purchase the most suitable product.

[0346] Specific examples

[0347] For air purifiers

[0348] Starting the system

[0349] 1. User: Open "EC Sensei" in a web browser.

[0350] 2. Device: Display the homepage.

[0351] Condition input and emotion recognition phase

[0352] 1. User: Select the Air Purifier category.

[0353] 2. Device: Display the detailed conditions input form for the air purifier.

[0354] 3. User: Enter the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[0355] 4. Device: Analyzes the user's facial expressions and voice using a camera and microphone to obtain emotional data. The obtained emotional data and selection criteria are sent to the server.

[0356] Product selection phase by AI

[0357] 1. Server: Sends condition data and emotion data to the AI ​​engine and begins collecting and analyzing product information.

[0358] 2. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites, analyzes and scores it using NLP technology, and ranks products taking into account emotional data.

[0359] Optimal product presentation phase

[0360] 1. Server: Generates a list of optimal products and adds information such as "Points to note when purchasing," "Lowest price site," and "Recommended features." Adjusts the information presented based on emotional data.

[0361] 2. Server: Sends the product list and related information to the terminal.

[0362] 3. Terminal: Displays product list and additional information.

[0363] 4. User: Selects the best product and decides to purchase.

[0364] This makes it possible to significantly reduce the difficulty of selection and the risk of making a mistaken purchase in conventional online shopping by analyzing the user's detailed selection criteria and emotional data. This specific embodiment supports the claims and clarifies the technical scope of the invention.

[0365] The processing flow will be explained below.

[0366] Step 1:

[0367] User: Open the "EC Sensei" application or website on your device.

[0368] Launch a web browser and enter the specified URL or tap the application icon.

[0369] Step 2:

[0370] Server: Receives the user's request, generates the HTML / CSS / JavaScript resources for the homepage, and sends them to the terminal.

[0371] Based on user requests, homepage data is dynamically generated and transmitted.

[0372] Step 3:

[0373] User: Select a product category (e.g., air purifier).

[0374] Click on the drop-down menu or icon to select the product category you want.

[0375] Step 4:

[0376] Server: Based on the selected category, a related detailed selection criteria input form is generated and sent to the terminal.

[0377] The input form corresponding to the product category is retrieved from the database, and the data required for displaying it is generated and sent.

[0378] Step 5:

[0379] User: Enter detailed selection criteria (e.g. price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[0380] Enter the condition in the input field and select an option.

[0381] Step 6:

[0382] Terminal: Organizes the input selection criteria data and emotion data and sends a request in JSON format to the server.

[0383] Form data and emotion data obtained from the camera, microphone, etc. are converted into JSON format and sent to the specified API endpoint.

[0384] Step 7:

[0385] Server: Passes the received selection criteria data and emotion data to the AI ​​engine and starts the data collection process.

[0386] Based on the conditions and sentiment data, it activates an AI module to collect product-related information from multiple data sources.

[0387] Step 8:

[0388] Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[0389] Use APIs and scraping techniques to collect product information from designated data sources.

[0390] Step 9:

[0391] Server: Uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[0392] The NLP engine is activated to analyze the text data and extract important keywords and evaluation points, taking into account sentiment data.

[0393] Step 10:

[0394] Server: Based on the analysis results, the products are scored and a ranking is generated.

[0395] A scoring algorithm is applied to rank the products that best match the criteria and the user's emotional state.

[0396] Step 11:

[0397] Server: Generates a list of optimal products and adds additional information for each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features." Adjusts the priority and content of information based on emotional data.

[0398] Generate data in JSON format that includes relevant information in the product list.

[0399] Step 12:

[0400] Server: Sends the generated product list and additional information to the terminal.

[0401] The product list and related information are sent to the terminal and prepared for display.

[0402] Step 13:

[0403] Terminal: Analyzes the received product list and additional information and displays it on the user interface.

[0404] Convert the JSON data into HTML and display the information to the user.

[0405] Step 14:

[0406] User: Check the presented products, select the most suitable product and purchase it.

[0407] Based on the product information provided, select the desired product and proceed with the purchase.

[0408] This allows users to input detailed product selection criteria and emotional data, and with the help of AI, efficiently select the most suitable product.

[0409] Example 2

[0410] 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."

[0411] In conventional online shopping systems, users must manually compare and judge a large amount of information when selecting products based on their desired product selection criteria, which leads to a lack of efficiency and a high risk of making the wrong purchase. Furthermore, products are suggested without taking into account the user's emotional state, which can lead to problems in which the system does not adequately reflect the user's purchasing intentions. Furthermore, the collected data is fragmented, making it difficult to make a comprehensive evaluation. There is a need for a system that can solve these issues and enable users to select the optimal product in a short amount of time.

[0412] 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.

[0413] In this invention, the server includes a communication means for collecting selection criteria and emotional data for products desired by the user, a means for analyzing the collected selection criteria and emotional data and determining the emotional state, and an artificial intelligence means for collecting and analyzing data related to the products based on the determined emotional state and selection criteria. This makes it possible to evaluate and rank products and present an optimal product list after taking into account the user's detailed selection criteria and emotional data. This significantly reduces the difficulty of selection and the risk of purchasing the wrong product in conventional systems, improving the user's purchasing experience.

[0414] "User" refers to a person who uses the system or service to select and purchase products.

[0415] "Selection criteria" refers to specific requirements such as price, functionality, size, etc. that a user considers when selecting a product.

[0416] "Emotional data" refers to data that indicates the emotional state of a user analyzed from facial expressions, voice, operating behavior, etc.

[0417] "Communication means" refers to the technical elements used to send and receive data between a user's terminal and a server.

[0418] "Emotional state" refers to the psychological state determined by analyzing the user's emotional data.

[0419] "Artificial Intelligence Means" refers to the artificial intelligence technologies used to analyze, evaluate, and rank the collected data.

[0420] "Product List" refers to a list of information about analyzed and ranked products.

[0421] "Additional information" refers to supplementary information related to a product, such as "Points to note when purchasing," "Lowest price site," and "Recommended features," that is added to the product list.

[0422] "Sensor device" refers to hardware such as a camera, microphone, or touch sensor used to collect a user's emotional data.

[0423] "Natural language processing means" refers to natural language processing technology for mechanically understanding and analyzing text data of word-of-mouth and reviews.

[0424] This invention is a system that allows users to efficiently select the most suitable product when shopping online. Specifically, it aims to solve the problems of conventional systems by combining the user's selection criteria and emotional data to suggest the most suitable product. This system is realized using a user's terminal, a server, an artificial intelligence engine, and an emotional engine.

[0425] User's device

[0426] The user opens the "EC Sensei" application or website on their device, such as a PC, smartphone, or tablet. The device displays the application or website interface and allows the user to select a product category. Once the user selects the desired product category (e.g., air purifier), a form for entering detailed selection criteria is displayed. Here, the user enters detailed selection criteria such as price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity.

[0427] Emotion Engine Operation

[0428] The device collects the user's emotional data, along with detailed selection conditions, using sensor devices such as a camera, microphone, and touch sensor. This emotional data is extracted from the user's facial expressions, voice, and the speed and strength of touch operations. The collected emotional data and selection condition data are sent from the device to the server.

[0429] Server and AI engine

[0430] The server receives the selection criteria data and emotion data sent by the user and supplies them to the AI ​​engine to begin the analysis process. The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites (e.g., Amazon, Rakuten, Yahoo! Shopping). It then uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews, scoring and ranking products while also taking into account the user's emotional state.

[0431] Product list presentation

[0432] The server generates a rated and ranked product list based on the analysis and scoring results. This product list includes additional information such as "things to note when purchasing," "cheapest sites," and "recommended features," and the presentation priority and content of this information are adjusted based on the emotional data. The generated product list and additional information are sent from the server to the terminal, which displays them on the user interface. The user can review the presented product list, select the most suitable product, and purchase it.

[0433] Specific examples

[0434] For air purifiers

[0435] The user opens "EC Sensei" in a web browser on their PC. The homepage is displayed, and the user selects the air purifier category. A form for entering detailed conditions for the air purifier is then displayed. The user enters the following conditions: price (up to 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (available), and smartphone connectivity (available). The device uses a camera and microphone to analyze the user's facial expressions and voice, and obtains emotional data. This emotional data and the selection conditions are then sent to the server.

[0436] The server sends this data to an AI engine, which begins collecting and analyzing product information. Data is collected from word-of-mouth sites, e-commerce sites, and product review sites, and analyzed and scored using NLP technology. Products are ranked taking emotional data into consideration. As a result, an optimal product list is generated, and additional information such as "things to note when purchasing," "cheapest site," and "recommended features" is added. The server then sends the generated product list and related information to the device, which displays it. The user selects the optimal product and decides to purchase.

[0437] Example of input prompt for generative AI model

[0438] "Please find and recommend the best air purifier based on user feedback and reviews, with a maximum price of ¥30,000, an applicable area of ​​up to 20 tatami mats, filter replacement frequency of once a year, humidification function, and smartphone connectivity. Please also take into account user sentiment data."

[0439] By analyzing users' detailed selection criteria and emotional data, this system can significantly reduce the difficulty of selection and the risk of making the wrong purchase that are associated with traditional online shopping, thereby improving the user's purchasing experience.

[0440] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0441] Step 1:

[0442] The user opens the "EC Sensei" application or website on their device, such as a PC, smartphone, or tablet.

[0443] Specific operation: The user launches a web browser and enters the URL of "EC Sensei" to access it. Input: Target URL. Output: The homepage is displayed.

[0444] Step 2:

[0445] The terminal displays the interface of the application or website and prompts the user to select a product category.

[0446] Specific operation: The terminal renders and displays the homepage according to the user's access. Input: User access. Output: A product category selection screen is displayed.

[0447] Step 3:

[0448] The user selects a product category (e.g., air purifier).

[0449] Specific operation: The user taps or clicks on a category from the options on the screen. Input: The user's selection. Output: The selected category information.

[0450] Step 4:

[0451] The device will display a detailed selection criteria input form based on the selected category.

[0452] Specific operation: The terminal dynamically generates and displays a detailed condition input form for products corresponding to the selected category. Input: Selected category information. Output: Display of detailed condition input form.

[0453] Step 5:

[0454] The user enters detailed selection criteria (e.g., maximum price 30,000 yen, applicable area 20 tatami mats, filter replacement frequency once a year, humidification function, smartphone connectivity).

[0455] Specific operation: The user enters the selection criteria in the displayed form and presses the submit button. Input: User inputs the selection criteria. Output: Selection criteria data.

[0456] Step 6:

[0457] The device collects the user's emotional data using a camera, microphone, and touch sensor, along with detailed selection criteria.

[0458] Specific operation: The device captures facial expressions with a camera, records audio with a microphone, and obtains touch sensor operation data. Input: User selection criteria and emotion data. Output: Collected selection criteria data and emotion data.

[0459] Step 7:

[0460] The terminal transmits the collected selection condition data and emotion data to the server.

[0461] Specific operation: The device sends an HTTP request to the server, sending selection criteria data and emotion data via the API. Input: Selection criteria data and emotion data. Output: Data transmission to the server completed.

[0462] Step 8:

[0463] The server feeds the received data to the AI ​​engine, which starts the analysis process.

[0464] Specific operation: The server saves the data in the database and supplies it to the AI ​​engine. Input: Selection criteria data and emotion data. Output: Start of the analysis process.

[0465] Step 9:

[0466] The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[0467] Specific operation: The server uses scraping technology or API to obtain product data from external sites. Input: Selection criteria. Output: Collected product data.

[0468] Step 10:

[0469] The server uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[0470] Specific operation: The NLP engine extracts keywords and performs sentiment analysis on text data to extract influential reviews. Input: Collected product data. Output: Analysis result data.

[0471] Step 11:

[0472] The server scores and ranks products, taking into account emotional data.

[0473] Specific operation: The AI ​​engine integrates emotion data and analysis results to calculate product scores and create rankings. Input: Analysis result data, emotion data. Output: Scoring and ranking data.

[0474] Step 12:

[0475] The server generates a list of rated and ranked products and adds additional information such as "things to note when purchasing," "cheapest site," and "recommended features."

[0476] Specific operation: The server generates a product list based on the ranking data and adds supplementary information. Input: Scoring and ranking data. Output: Generated product list.

[0477] Step 13:

[0478] The server transmits the generated product list and additional information to the terminal.

[0479] Specific operation: The server sends data to the terminal as an HTTP response. Input: Generated product list. Output: Data sent to the terminal completed.

[0480] Step 14:

[0481] The terminal displays the product list and additional information on a user interface.

[0482] Specific operation: The terminal parses the display data and displays it on the interface. Input: Product list data. Output: Information is presented to the user.

[0483] Step 15:

[0484] The user checks the presented product list and selects and purchases the most suitable product.

[0485] Specific operation: The user scrolls through the displayed product list, selects the most suitable product, and presses the purchase button. Input: Product list. Output: Selection and purchase completed.

[0486] (Application example 2)

[0487] 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."

[0488] Conventional online shopping systems make it difficult for users to efficiently select the most suitable product from a vast selection of products. Furthermore, because they do not take into account the user's emotional state, the selected product may not meet the user's expectations, resulting in a dissatisfying shopping experience.

[0489] 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 inputting selection conditions for products desired by the user, means including a sensor for collecting user emotional data, communication means for collecting data related to the products based on the input selection conditions and emotional data, artificial intelligence means for analyzing the collected data and evaluating and ranking the products, means for presenting a list of evaluated and ranked products to the user, and means for attaching additional information to the presented product list, including "points to note when purchasing," "cheapest site," and "recommended features" for each product. This makes it possible to analyze the user's detailed selection conditions and emotional data and efficiently select and provide optimal products.

[0490] "User" refers to an individual who selects and purchases a particular product or service.

[0491] "Emotional data" is data that indicates the user's emotional state and is collected through sensors such as cameras and microphones.

[0492] A "sensor" refers to a device that senses an external physical or chemical phenomenon and outputs it as an electrical signal.

[0493] "Artificial intelligence means" refers to a system that includes algorithms and programs for collecting and analyzing data and proposing optimal products based on the results.

[0494] "Natural language processing means" refers to technology and software that understands, analyzes, and extracts meaning from human language.

[0495] "Communication means" refers to the technology and protocols used to transmit and receive data between multiple devices or systems.

[0496] A "product list" is a list of multiple products that have been rated and ranked, and includes detailed information about each product.

[0497] "Additional information" is information attached to the product list, and includes such things as "things to note when purchasing," "cheapest site," and "recommended features."

[0498] A "product category" refers to a classification item that groups together a group of products with similar characteristics.

[0499] "Conditions" means any specific requirements or constraints specified by a User when selecting a Product.

[0500] A "word-of-mouth site" is a website where consumers can post ratings and reviews of products they have used.

[0501] "E-commerce site" refers to an online platform through which goods and services are bought and sold on a web-based basis.

[0502] A "product review site" refers to a website where consumers can post product ratings and comments and other consumers can view that information.

[0503] The present invention relates to an online shopping system that enables users to efficiently select the most suitable product. This system is realized with the following configuration.

[0504] System Configuration

[0505] User's device

[0506] Hardware: Smartphones, tablets, PCs, smart glasses

[0507] Software: "Shopping Assistant" application or website

[0508] First, the user opens the "Shopping Assistant" application on their device and selects the category of product they are looking for (e.g., home appliances). Next, they enter detailed selection criteria such as price, features, and brand. To collect emotion data, the device's built-in camera and microphone are used to collect the user's facial and voice data. This data is then sent to the server.

[0509] server

[0510] The server performs the following process:

[0511] Data collection: The server collects data about the product based on the received selection criteria and emotion data. For example, it collects product ratings and reviews from word-of-mouth sites, e-commerce sites, and product review sites. This data is acquired using communication methods.

[0512] Data analysis: Using artificial intelligence and natural language processing, we analyze the collected text and sentiment data. We score products and generate rankings taking into account the sentiment data.

[0513] Generate a list of rated products: Generate a list of rated and ranked products, and add additional information to each product, such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[0514] Product list presentation

[0515] Presentation method: The product list and additional information sent from the server are displayed on the user's device. The user can select the most suitable product based on the presented information and decide to purchase it.

[0516] Specific examples

[0517] For example, suppose a user is looking for an air purifier. In this case, the user puts on the smart glasses and operates the "Shopping Assistant" app by voice, inputting detailed requirements for the air purifier (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.). The camera and microphone collect facial and voice data, which is then sent to a server. The server collects and analyzes product data based on the selection criteria and emotion data, and generates an optimal product list. This list is displayed on the smart glasses' display, allowing the user to select the most suitable product.

[0518] Prompt Sentence Examples

[0519] Let's say a user is looking for an air purifier, and they input the following criteria: price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity, and then we created an application that suggests the most suitable product based on sentiment analysis.

[0520] In this way, the online shopping system of the present invention can provide a high level of satisfaction by taking into consideration the user's feelings and selection conditions.

[0521] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0522] Step 1:

[0523] The user opens the "Shopping Assistant" application on the device. The user selects the desired product category (e.g., home appliances) and enters detailed selection criteria (price, features, brand, etc.). The entered selection criteria are retrieved by the device.

[0524] Step 2:

[0525] The device uses a camera and microphone to collect facial and voice data from the user, and generates input data for analyzing emotional data based on the collected sensor data.

[0526] Step 3:

[0527] The terminal transmits the input selection conditions and analyzed emotion data to the server, which receives this data and prepares to start collecting data about the product.

[0528] Step 4:

[0529] The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites based on the selection criteria and emotion data. The collected data is passed to the next analysis step.

[0530] Step 5:

[0531] The server uses natural language processing to analyze the collected text data of word-of-mouth and reviews, and the analyzed text data becomes input data for rating and ranking products.

[0532] Step 6:

[0533] The server uses artificial intelligence means to score products taking into account the selection criteria and emotion data, and the scored data serves as input data for generating a product list.

[0534] Step 7:

[0535] The server generates a list of rated and ranked products, and adds additional information to each product, such as "points to note when purchasing," "cheapest site," and "recommended features." The generated product list is generated as output data.

[0536] Step 8:

[0537] The server sends the generated product list and additional information to the terminal, which receives it and displays it on the user's interface.

[0538] Step 9:

[0539] The user reviews the presented product list and additional information, selects the most suitable product, and then proceeds to purchase the selected product.

[0540] In this way, by processing input data and generating output data at each step, users can efficiently select the most suitable product taking into account their emotional data.

[0541] 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.

[0542] 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.

[0543] 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.

[0544] [Second embodiment]

[0545] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0546] 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.

[0547] 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).

[0548] 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.

[0549] 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.

[0550] 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).

[0551] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0552] 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.

[0553] 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.

[0554] 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.

[0555] 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.

[0556] 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."

[0557] This invention is a system that allows users to select the most suitable product when shopping online. It uses AI to analyze the selection criteria of the product desired by the user and presents the most suitable product. This reduces the difficulty of product selection in conventional online shopping and the risk of mistaken purchases caused by false labeling and exaggerated advertising.

[0558] System Configuration

[0559] The system of the present invention is composed of a user terminal, a server, and a communication means. The role and operation of each component will be explained in detail below.

[0560] User's device

[0561] 1. User: Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.).

[0562] 2. Terminal: Displays the interface and allows the user to select a product category.

[0563] 3. User: Select a product category (e.g., air purifier).

[0564] 4. Terminal: Based on the selected category, a detailed selection criteria input form will be displayed.

[0565] 5. User: Enter detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.).

[0566] server

[0567] 6. Terminal: Sends the entered selection criteria data to the server.

[0568] 7. Server: Receives the selection conditions and starts the AI ​​engine.

[0569] 8. Server: The AI ​​engine collects relevant product data from multiple data sources (word-of-mouth sites, e-commerce sites, product review sites, etc.) based on the selection criteria.

[0570] 9. Server:

[0571] Natural language processing (NLP) technology is used to analyze collected word-of-mouth and review text data.

[0572] Products are scored based on the analysis results and a ranking is generated.

[0573] Product list presentation

[0574] 10. Server: Generates a scored and ranked product list and adds additional information for each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features."

[0575] 11. Server: Sends the generated product list and additional information to the terminal.

[0576] 12. Terminal: Displays the product list and additional information in a user interface.

[0577] 13. User: Check the presented products and select and purchase the most suitable product.

[0578] Specific examples

[0579] For air purifiers

[0580] Starting the system

[0581] 1. User: Open "EC Sensei" in a web browser.

[0582] 2. Device: Display the homepage.

[0583] Condition Input Phase

[0584] 3. User: Select the Air Purifier category.

[0585] 4. Device: Display the detailed conditions input form for the air purifier.

[0586] 5. User: Enter the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[0587] Product selection phase by AI

[0588] 6. Terminal: Sends condition data to the server.

[0589] 7. Server: Sends condition data to the AI ​​engine and begins collecting and analyzing product information.

[0590] 8. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites, and analyzes and scores it using NLP technology.

[0591] Optimal product presentation phase

[0592] 9. Server: Generates a list of optimal products and adds features such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[0593] 10. Server: Sends the product list to the terminal.

[0594] 11. Terminal: Displays product list and additional information.

[0595] 12. User: Selects the best product and decides to purchase.

[0596] This allows users to easily select the most suitable product based on reliable information. This specific embodiment supports the claims and clarifies the technical scope of the invention.

[0597] The processing flow will be explained below.

[0598] Step 1:

[0599] User: Open the "EC Sensei" application or website on your device.

[0600] Launch a web browser and enter the specified URL or tap the application icon.

[0601] Step 2:

[0602] Server: Receives the user's request, generates the HTML / CSS / JavaScript resources for the homepage, and sends them to the terminal.

[0603] Based on user requests, homepage data is dynamically generated and transmitted.

[0604] Step 3:

[0605] User: Select a product category (e.g., air purifier).

[0606] Click on the drop-down menu or icon to select the product category you want.

[0607] Step 4:

[0608] Server: Based on the selected category, a related detailed selection criteria input form is generated and sent to the terminal.

[0609] The input form corresponding to the product category is retrieved from the database, and the data required for displaying it is generated and sent.

[0610] Step 5:

[0611] User: Enter detailed selection criteria (e.g. price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[0612] Enter the condition in the input field and select an option.

[0613] Step 6:

[0614] Terminal: Organizes the entered selection criteria data and sends a request to the server in JSON format.

[0615] Converts form data into JSON format and sends a request to the specified API endpoint.

[0616] Step 7:

[0617] Server: Passes the received selection criteria data to the AI ​​engine and starts the data collection process.

[0618] Based on the conditions, it triggers an AI module to collect product-related information from multiple data sources.

[0619] Step 8:

[0620] Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[0621] Use APIs and scraping techniques to collect product information from designated data sources.

[0622] Step 9:

[0623] Server: Uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[0624] The NLP engine is activated to analyze the text data and extract important keywords and evaluation points.

[0625] Step 10:

[0626] Server: Based on the analysis results, the products are scored and a ranking is generated.

[0627] A scoring algorithm is applied to rank the products that best match the criteria.

[0628] Step 11:

[0629] Server: Generates a list of optimal products and adds additional information for each product, such as "things to note when purchasing," "cheapest site," and "recommended features."

[0630] Generate data in JSON format that includes relevant information in the product list.

[0631] Step 12:

[0632] Server: Sends the generated product list and additional information to the terminal.

[0633] The product list and related information are sent to the terminal and prepared for display.

[0634] Step 13:

[0635] Terminal: Analyzes the received product list and additional information and displays it on the user interface.

[0636] Convert the JSON data into HTML and display the information to the user.

[0637] Step 14:

[0638] User: Check the presented products, select the most suitable product and purchase it.

[0639] Based on the product information provided, select the desired product and proceed with the purchase.

[0640] This allows users to input detailed product selection criteria and efficiently select the most suitable products with the help of AI.

[0641] Example 1

[0642] 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."

[0643] Today's consumers often find it difficult to select the best product from the numerous product options available when shopping online. There is also the risk of making a mistaken purchase due to false and exaggerated advertising. Furthermore, checking a large number of customer testimonials and reviews one by one is extremely time-consuming and labor-intensive. These issues often make it difficult for consumers to choose the right product.

[0644] 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.

[0645] In this invention, the server includes a means for inputting selection criteria for products desired by the user, a communication means for collecting information about the products based on the input selection criteria, and an artificial intelligence means for analyzing the collected information and evaluating and ranking the products. This reduces the difficulty of product selection and the risk of making an erroneous purchase, and enables users to easily select the most suitable product based on reliable information.

[0646] "Means for users to input selection criteria for desired products" refers to means for providing an interface that allows users to input the characteristics and requirements of desired products using devices such as PCs or smartphones.

[0647] "Communication means for collecting information about products based on input selection criteria" refers to a network communication device and protocol for collecting information about products from various data sources on the Internet based on criteria specified by the user.

[0648] "Artificial intelligence means for analyzing collected information and evaluating and ranking products" refers to an AI system that includes machine learning algorithms and natural language processing technology to automatically analyze collected data and statistically analyze the characteristics and evaluations of each product to set a rank.

[0649] A "means for presenting a rated and ranked product list to a user" is a display device or interface that displays the AI-ranked product list in a user-friendly format, allowing the user to easily select the most suitable product.

[0650] "A means for adding additional information to the presented product list, including 'points to note when purchasing,' 'lowest price information,' and 'recommended features' for each product" refers to an information processing system that automatically generates and adds to the evaluated product list information such as points to note when purchasing each product, price comparison information with other sales sites, and features that are particularly superior in comparison with other products.

[0651] The "means for allowing a user to select a category" is a means for providing an interface for the user to select a category of a product to be searched for.

[0652] The "means for displaying related product selection conditions based on the selected category" is a means for providing an interface for inputting detailed selection conditions for the relevant product according to the category selected by the user.

[0653] "Means for collecting data from review sites, e-commerce sites, and product rating sites" refers to a data acquisition mechanism using crawling technology and APIs to efficiently collect detailed product data from multiple sources on the Internet.

[0654] "Natural language processing means for analyzing collected data" refers to an analysis system that includes natural language processing technology for analyzing collected text data (word of mouth, reviews, etc.) and extracting and structuring meaning from the data.

[0655] This invention is a system that allows users to select the most suitable product when shopping online. Specifically, the system inputs the selection criteria for the desired product, analyzes them using AI, and presents the most suitable product. This system is composed of a user terminal, a server, and communication means.

[0656] User's device

[0657] Device behavior

[0658] Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.). The user interface will be displayed, prompting the user to select a product category and displaying a form for entering detailed selection criteria. When the user enters detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.), the data will be sent to the server.

[0659] server

[0660] Server Operation

[0661] The server receives the selection criteria data sent from the device and activates the AI ​​engine. The AI ​​engine collects data from multiple data sources (e.g., word-of-mouth sites, e-commerce sites, product review sites) based on the selection criteria. The collected data is analyzed using natural language processing (NLP) technology to score and rank each product.

[0662] Product list presentation

[0663] Product proposals

[0664] The server generates a scored and ranked product list and adds additional information for each product, including "points to note when purchasing," "lowest price information," and "recommended features." This generated product list and additional information are sent to the terminal, which displays the product list and additional information on the user interface. The user can review the presented products and select the most suitable one.

[0665] Specific examples

[0666] For air purifiers

[0667] Starting the system

[0668] 1. The user opens "EC Sensei" in a web browser.

[0669] 2. The device displays the homepage.

[0670] Condition Input Phase

[0671] 3. The user selects the Air Purifier category.

[0672] 4. The device will display a form to input detailed conditions for the air purifier.

[0673] 5. The user enters the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[0674] Product selection phase by AI

[0675] 6. The device sends the condition data to the server.

[0676] 7. The server sends the condition data to the AI ​​engine and begins collecting and analyzing product information.

[0677] 8. The server collects data from word-of-mouth sites, e-commerce sites, and product review sites, and analyzes and scores it using NLP technology.

[0678] Optimal product presentation phase

[0679] 9. The server generates a list of optimal products and adds information such as "points to note when purchasing," "lowest price information," and "recommended features."

[0680] 10. The server sends the product list to the terminal.

[0681] 11. The device will display a list of products and additional information.

[0682] 12. The user selects the best product and decides to purchase.

[0683] Example prompts for generative AI models

[0684] Prompt statement:

[0685] Please describe the process by which a user would use the "EC Sensei" system to select the best air purifier based on the following selection criteria: price (up to ¥30,000), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (available), smartphone connectivity (available)

[0686] By inputting this prompt into a generative AI model, users can efficiently select the most suitable product.

[0687] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0688] Step 1:

[0689] The user opens the "EC Sensei" application or website on a device such as a PC or smartphone.

[0690] Input: Device launch and application or browser access.

[0691] Output: Application or browser homepage display.

[0692] Specific action: The user taps the application icon or enters the URL in the browser to open the site.

[0693] Step 2:

[0694] The terminal displays a home page and prompts the user to select a product category.

[0695] Input: The user's access request.

[0696] Output: Display of product category selection screen.

[0697] Specific operation: The device renders the "EC Sensei" homepage and offers product category selection.

[0698] Step 3:

[0699] The user selects a product category (e.g., air purifiers).

[0700] Input: A category selected by the user.

[0701] Output: Save selected category information.

[0702] Specific Action: User clicks on the Air Purifiers category.

[0703] Step 4:

[0704] The device will display a detailed selection criteria input form based on the selected category.

[0705] Input: Selected product category information.

[0706] Output: Display of detailed selection criteria input form.

[0707] Specific operation: The device renders and displays a detailed input form (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.) according to the selected category.

[0708] Step 5:

[0709] The user enters detailed selection criteria.

[0710] Input: Detailed selection criteria (e.g. price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), smartphone connectivity (yes)).

[0711] Output: Saves the entered selection criteria data.

[0712] Specific operation: The user enters values ​​or options for each condition item and presses the submit button.

[0713] Step 6:

[0714] The terminal transmits the input condition data to the server.

[0715] Input: Detailed selection criteria data.

[0716] Output: Sending data to the server.

[0717] Specific operation: The terminal generates an HTTP request and sends the condition data in JSON format to the server.

[0718] Step 7:

[0719] The server supplies the received selection condition data to the AI ​​engine.

[0720] Input: The received selection criteria data.

[0721] Output: Data feed to the AI ​​engine.

[0722] Specific operation: The server stores data in a database and provides that data as input to the AI ​​engine.

[0723] Step 8:

[0724] The server's AI engine collects data from multiple data sources (e.g., word-of-mouth sites, e-commerce sites, product review sites) based on selection criteria.

[0725] Input: Selection criteria data.

[0726] Output: Collected product data.

[0727] What it does: The AI ​​engine uses APIs and web scraping technology to collect relevant product data from designated sites.

[0728] Step 9:

[0729] The server uses natural language processing (NLP) techniques to analyze the collected data and score and rank the products.

[0730] Input: Collected text data (word of mouth, reviews, etc.).

[0731] Output: Analysis results and scored product list.

[0732] Specific operation: Text data is input into the NLP model, analyzed, and product characteristics and evaluation scores are calculated and ranked.

[0733] Step 10:

[0734] The server generates a list of rated and ranked products and adds additional information such as "things to note when purchasing," "lowest price information," and "recommended features."

[0735] Input: Scored product list.

[0736] Output: Final product list with additional information added.

[0737] Specific operation: The server generates information about each product, such as warnings, features, and price comparisons, and adds it to the scored list.

[0738] Step 11:

[0739] The server transmits the generated product list and additional information to the terminal.

[0740] Input: Final product list.

[0741] Output: Sending data to the terminal.

[0742] Specific operation: Generates an HTTP response to send the product list and additional information in JSON format to the terminal.

[0743] Step 12:

[0744] The terminal displays a list of products and additional information.

[0745] Input: Product list and additional information sent from the server.

[0746] Output: Display to the user interface.

[0747] What happens: The device renders the product list and additional information and displays it on the screen.

[0748] Step 13:

[0749] The user checks the products presented and selects and purchases the most suitable product.

[0750] Input: Displayed product list and additional information.

[0751] Output: Product selection and purchase confirmation.

[0752] Specific operation: The user checks the product list, clicks on the product they want to purchase, and completes the purchase process.

[0753] (Application example 1)

[0754] 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."

[0755] In conventional online shopping, users often face an overwhelming number of options when selecting the products they need, and are often misled by exaggerated advertising and false representations, making it difficult to select the optimal product. Furthermore, collecting and analyzing reliable information from multiple data sources requires a great deal of effort. There is an urgent need to provide a system that can solve these problems and enable users to quickly and reliably select the optimal product.

[0756] 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.

[0757] In this invention, the server includes: means for inputting selection criteria for a desired product by a user; communication means for collecting data on the products based on the input selection criteria; artificial intelligence means for analyzing the collected data and rating and ranking the products; means for presenting a list of rated and ranked products to the user; means for adding additional information to the presented product list, including "points to note when purchasing," "cheapest sites," and "recommended features," for each product; means for transmitting the product selection criteria input by the user via the user interface to the server; means for an artificial intelligence engine within the server to collect and analyze product information from a data source based on the user's input criteria; and means for displaying the analysis results on the user interface. This enables users to quickly and accurately select optimal products based on reliable data.

[0758] "Users" are individuals or groups who search for products through online shopping and consider purchasing them.

[0759] "Choice criteria" are the specific features or criteria that a user seeks when purchasing a product, such as price, functionality, or quality.

[0760] "Communication means" refers to the technology and infrastructure for sending and receiving data between the user's device and the server, including the Internet and wireless communications.

[0761] "Artificial intelligence tools" refer to algorithms and techniques used to analyze collected data and evaluate and rank products. Machine learning and deep learning techniques are primarily used.

[0762] "Rating and ranking" refers to scoring products based on user selection criteria and sorting them in an appropriate order. This process includes analyzing word-of-mouth and reviews.

[0763] "Presenting" is the act of showing a user a rated and ranked product list and its additional information.

[0764] "Purchase precautions" is information that indicates important points that users should consider when purchasing a product. For example, it includes product-specific drawbacks and usage precautions.

[0765] A "cheapest site" is a sales site where you can purchase a particular product at the lowest price.

[0766] "Recommended features" refer to the particularly outstanding functions or features of a particular product.

[0767] "User interface" refers to the screens and operating methods that allow users to directly interact with systems and applications.

[0768] "Data source" refers to an online source of information from which product information is collected, such as a word-of-mouth site, an e-commerce site, or a product review site.

[0769] "Natural language processing" is a technology that analyzes collected text data such as word-of-mouth and reviews and converts it into meaningful information. It mainly uses machine learning algorithms.

[0770] The system for carrying out this invention is composed of a user terminal, a server, and an infrastructure that connects these via communication means. Specifically, the system provides a user interface for users to select products, collects and analyzes data on the server side based on the selection criteria, and presents the most suitable products.

[0771] User's device

[0772] The terminal is an electronic device such as a smartphone, personal computer, or tablet, and provides an interface for users to input selection criteria for their desired products. The user uses this interface to input product categories and detailed selection criteria.

[0773] Specific example of input procedure

[0774] 1. User: Launch the EC Sensei application on their smartphone.

[0775] 2. Device: View product categories on the app homepage.

[0776] 3. User: Select the Air Purifier category.

[0777] 4. Device: Display the detailed conditions input form for the air purifier.

[0778] 5. User: Enter the desired price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity conditions.

[0779] Server Processing

[0780] The server activates an AI engine based on each user's input and collects product information from multiple data sources. It then uses natural language processing (NLP) technology to analyze text data from user reviews and scores products. Furthermore, the product list, which is scored based on the analysis results, includes additional information such as "things to note when purchasing," "the site with the lowest price," and "recommended features."

[0781] Software Configuration

[0782] AI Engine: Analyzes customer testimonials and reviews using deep learning frameworks like TensorFlow or PyTorch.

[0783] Framework: Uses Flask to manage communication between the server and the user interface.

[0784] Communication library: Uses the Python Requests library to send and receive data.

[0785] Specific examples of processing procedures

[0786] 1. Terminal: The selection criteria entered by the user are sent to the server.

[0787] 2. Server: Sends condition data to the AI ​​engine and begins collecting and analyzing product information.

[0788] 3. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites.

[0789] 4. Server: Analyzes data using natural language processing and scores products.

[0790] 5. Server: Generates a list of optimal products and adds features such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[0791] 6. Server: Sends the product list to the terminal.

[0792] 7. Terminal: Displays product list and additional information.

[0793] 8. User: Selects the best product and decides to purchase.

[0794] Prompt Sentence Examples

[0795] Conditions for purchase: The user opens the smartphone app "EC Sensei" and enters the details of the air purifier they require. The desired conditions are "price under 30,000 yen," "applicable area up to 20 tatami mats," "filter replacement frequency once a year," "humidification function," and "smartphone connectivity."

[0796] Input: Enter "air purifier," "under 30,000 yen," "20 tatami mats," "once a year," "humidifier function," and "smartphone connectivity" into the user interface.

[0797] Output: After AI analysis, a list of the "best air purifiers" is presented, along with reviews for each product, the lowest price store, and details of recommended features.

[0798] The above is a mode for carrying out the invention, and enables users to quickly and accurately select the most suitable product based on reliable data.

[0799] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0800] Step 1:

[0801] The user launches the EC Sensei application on their smartphone and selects a product category.

[0802] Input: A user launches the application and selects "Air Purifier" as the product category.

[0803] Output: A form for entering detailed conditions for the air purifier will be displayed on the terminal.

[0804] Step 2:

[0805] The user enters detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[0806] Input: The user enters conditions such as "price under 30,000 yen," "applicable area up to 20 tatami mats," "filter replacement frequency once a year," "humidification function included," and "smartphone connectivity available."

[0807] Output: The entered selection criteria are displayed on the terminal and are ready to be sent to the server.

[0808] Step 3:

[0809] The terminal transmits the input selection condition data to the server.

[0810] Input: Selection criteria data entered by the user.

[0811] Output: The condition data is sent to the server.

[0812] Step 4:

[0813] The server receives the condition data and starts the AI ​​engine.

[0814] Input: The submitted selection criteria data.

[0815] Output: The AI ​​engine is now up and running, ready to start collecting and analyzing product information from data sources.

[0816] Step 5:

[0817] The server collects product information from multiple data sources (word-of-mouth sites, e-commerce sites, product review sites).

[0818] Input: Product selection criteria specified by the AI ​​engine.

[0819] Output: Collected product information data. For example, text data of word-of-mouth and reviews.

[0820] Step 6:

[0821] The server analyzes the collected data using natural language processing (NLP) and scores the products.

[0822] Input: Collected text data of word-of-mouth and reviews.

[0823] The analysis involves extracting evaluation scores and important features from text data.

[0824] Output: Rating score and ranking for each product.

[0825] Step 7:

[0826] The server generates a list of rated and ranked products and attaches additional information including "things to note when purchasing," "cheapest sites," and "recommended features."

[0827] Input: Scoring results and additional information.

[0828] Output: A detailed product list.

[0829] Step 8:

[0830] The server transmits the generated product list and additional information to the terminal.

[0831] Input: A rated and ranked list of products and their additional information.

[0832] Output: The product list and additional information are sent to the terminal.

[0833] Step 9:

[0834] The terminal displays the product list and additional information on a user interface.

[0835] Input: Product list and additional information received from the server.

[0836] Output: A user interface with a list of products and their details.

[0837] Step 10:

[0838] The user checks the presented product list, selects the most suitable product, and decides to purchase it.

[0839] Input: Proposed product list and additional information.

[0840] Output: The product selected by the user and a purchase decision is made.

[0841] The above are the processing steps of the system program that realizes the application example.

[0842] 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.

[0843] The present invention relates to a system that allows users to efficiently select optimal products when shopping online. In particular, it aims to solve the problems of conventional systems by combining the user's selection criteria and emotional data to suggest optimal products. The present invention is realized using a user's terminal, a server, an artificial intelligence engine, and an emotional engine.

[0844] System Configuration and Operation

[0845] This system has the following configuration and operation.

[0846] User's device

[0847] 1. User: Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.).

[0848] 2. Terminal: Displays the interface and allows the user to select a product category.

[0849] 3. User: Select a product category (e.g., air purifier).

[0850] 4. Terminal: Based on the selected category, a detailed selection criteria input form will be displayed.

[0851] 5. User: Enter detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.).

[0852] Emotion Engine Operation

[0853] 1. Terminal: Collects the user's emotion data along with the input selection criteria and sends it to the server. Emotion data is extracted from sensor data such as camera, microphone, and touch input.

[0854] 2. Server: Analyzes the received emotional data and determines the user's emotional state.

[0855] Server and AI engine

[0856] 1. Server: Passes the selection criteria data and emotion data to the AI ​​engine and begins data collection and analysis.

[0857] 2. Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[0858] 3. Server: Using natural language processing (NLP) technology, the collected text data of user comments and reviews is analyzed, and product scores and rankings are generated taking into account sentiment data.

[0859] Product list presentation

[0860] 1. Server: Generates a scored and ranked product list and adds additional information for each product, including "Points to Note When Purchasing," "Lowest Price Site," and "Recommended Features." It also adjusts the priority and content of the information presented based on emotional data.

[0861] 2. Server: Sends the generated product list and additional information to the terminal.

[0862] 3. Terminal: displays the product list and additional information in a user interface.

[0863] 4. User: Check the presented products and select and purchase the most suitable product.

[0864] Specific examples

[0865] For air purifiers

[0866] Starting the system

[0867] 1. User: Open "EC Sensei" in a web browser.

[0868] 2. Device: Display the homepage.

[0869] Condition input and emotion recognition phase

[0870] 1. User: Select the Air Purifier category.

[0871] 2. Device: Display the detailed conditions input form for the air purifier.

[0872] 3. User: Enter the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[0873] 4. Device: Analyzes the user's facial expressions and voice using a camera and microphone to obtain emotional data. The obtained emotional data and selection criteria are sent to the server.

[0874] Product selection phase by AI

[0875] 1. Server: Sends condition data and emotion data to the AI ​​engine and begins collecting and analyzing product information.

[0876] 2. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites, analyzes and scores it using NLP technology, and ranks products taking into account emotional data.

[0877] Optimal product presentation phase

[0878] 1. Server: Generates a list of optimal products and adds information such as "Points to note when purchasing," "Lowest price site," and "Recommended features." Adjusts the information presented based on emotional data.

[0879] 2. Server: Sends the product list and related information to the terminal.

[0880] 3. Terminal: Displays product list and additional information.

[0881] 4. User: Selects the best product and decides to purchase.

[0882] This makes it possible to significantly reduce the difficulty of selection and the risk of making a mistaken purchase in conventional online shopping by analyzing the user's detailed selection criteria and emotional data. This specific embodiment supports the claims and clarifies the technical scope of the invention.

[0883] The processing flow will be explained below.

[0884] Step 1:

[0885] User: Open the "EC Sensei" application or website on your device.

[0886] Launch a web browser and enter the specified URL or tap the application icon.

[0887] Step 2:

[0888] Server: Receives the user's request, generates the HTML / CSS / JavaScript resources for the homepage, and sends them to the terminal.

[0889] Based on user requests, homepage data is dynamically generated and transmitted.

[0890] Step 3:

[0891] User: Select a product category (e.g., air purifier).

[0892] Click on the drop-down menu or icon to select the product category you want.

[0893] Step 4:

[0894] Server: Based on the selected category, a related detailed selection criteria input form is generated and sent to the terminal.

[0895] The input form corresponding to the product category is retrieved from the database, and the data required for displaying it is generated and sent.

[0896] Step 5:

[0897] User: Enter detailed selection criteria (e.g. price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[0898] Enter the condition in the input field and select an option.

[0899] Step 6:

[0900] Terminal: Organizes the input selection criteria data and emotion data and sends a request in JSON format to the server.

[0901] Form data and emotion data obtained from the camera, microphone, etc. are converted into JSON format and sent to the specified API endpoint.

[0902] Step 7:

[0903] Server: Passes the received selection criteria data and emotion data to the AI ​​engine and starts the data collection process.

[0904] Based on the conditions and sentiment data, it activates an AI module to collect product-related information from multiple data sources.

[0905] Step 8:

[0906] Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[0907] Use APIs and scraping techniques to collect product information from designated data sources.

[0908] Step 9:

[0909] Server: Uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[0910] The NLP engine is activated to analyze the text data and extract important keywords and evaluation points, taking into account sentiment data.

[0911] Step 10:

[0912] Server: Based on the analysis results, the products are scored and a ranking is generated.

[0913] A scoring algorithm is applied to rank the products that best match the criteria and the user's emotional state.

[0914] Step 11:

[0915] Server: Generates a list of optimal products and adds additional information for each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features." Adjusts the priority and content of information based on emotional data.

[0916] Generate data in JSON format that includes relevant information in the product list.

[0917] Step 12:

[0918] Server: Sends the generated product list and additional information to the terminal.

[0919] The product list and related information are sent to the terminal and prepared for display.

[0920] Step 13:

[0921] Terminal: Analyzes the received product list and additional information and displays it on the user interface.

[0922] Convert the JSON data into HTML and display the information to the user.

[0923] Step 14:

[0924] User: Check the presented products, select the most suitable product and purchase it.

[0925] Based on the product information provided, select the desired product and proceed with the purchase.

[0926] This allows users to input detailed product selection criteria and emotional data, and with the help of AI, efficiently select the most suitable product.

[0927] Example 2

[0928] 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."

[0929] In conventional online shopping systems, users must manually compare and judge a large amount of information when selecting products based on their desired product selection criteria, which leads to a lack of efficiency and a high risk of making the wrong purchase. Furthermore, products are suggested without taking into account the user's emotional state, which can lead to problems in which the system does not adequately reflect the user's purchasing intentions. Furthermore, the collected data is fragmented, making it difficult to make a comprehensive evaluation. There is a need for a system that can solve these issues and enable users to select the optimal product in a short amount of time.

[0930] 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.

[0931] In this invention, the server includes a communication means for collecting selection criteria and emotional data for products desired by the user, a means for analyzing the collected selection criteria and emotional data and determining the emotional state, and an artificial intelligence means for collecting and analyzing data related to the products based on the determined emotional state and selection criteria. This makes it possible to evaluate and rank products and present an optimal product list after taking into account the user's detailed selection criteria and emotional data. This significantly reduces the difficulty of selection and the risk of purchasing the wrong product in conventional systems, improving the user's purchasing experience.

[0932] "User" refers to a person who uses the system or service to select and purchase products.

[0933] "Selection criteria" refers to specific requirements such as price, functionality, size, etc. that a user considers when selecting a product.

[0934] "Emotional data" refers to data that indicates the emotional state of a user analyzed from facial expressions, voice, operating behavior, etc.

[0935] "Communication means" refers to the technical elements used to send and receive data between a user's terminal and a server.

[0936] "Emotional state" refers to the psychological state determined by analyzing the user's emotional data.

[0937] "Artificial Intelligence Means" refers to the artificial intelligence technologies used to analyze, evaluate, and rank the collected data.

[0938] "Product List" refers to a list of information about analyzed and ranked products.

[0939] "Additional information" refers to supplementary information related to a product, such as "Points to note when purchasing," "Lowest price site," and "Recommended features," that is added to the product list.

[0940] "Sensor device" refers to hardware such as a camera, microphone, or touch sensor used to collect a user's emotional data.

[0941] "Natural language processing means" refers to natural language processing technology for mechanically understanding and analyzing text data of word-of-mouth and reviews.

[0942] This invention is a system that allows users to efficiently select the most suitable product when shopping online. Specifically, it aims to solve the problems of conventional systems by combining the user's selection criteria and emotional data to suggest the most suitable product. This system is realized using a user's terminal, a server, an artificial intelligence engine, and an emotional engine.

[0943] User's device

[0944] The user opens the "EC Sensei" application or website on their device, such as a PC, smartphone, or tablet. The device displays the application or website interface and allows the user to select a product category. Once the user selects the desired product category (e.g., air purifier), a form for entering detailed selection criteria is displayed. Here, the user enters detailed selection criteria such as price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity.

[0945] Emotion Engine Operation

[0946] The device collects the user's emotional data, along with detailed selection conditions, using sensor devices such as a camera, microphone, and touch sensor. This emotional data is extracted from the user's facial expressions, voice, and the speed and strength of touch operations. The collected emotional data and selection condition data are sent from the device to the server.

[0947] Server and AI engine

[0948] The server receives the selection criteria data and emotion data sent by the user and supplies them to the AI ​​engine to begin the analysis process. The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites (e.g., Amazon, Rakuten, Yahoo! Shopping). It then uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews, scoring and ranking products while also taking into account the user's emotional state.

[0949] Product list presentation

[0950] The server generates a rated and ranked product list based on the analysis and scoring results. This product list includes additional information such as "things to note when purchasing," "cheapest sites," and "recommended features," and the presentation priority and content of this information are adjusted based on the emotional data. The generated product list and additional information are sent from the server to the terminal, which displays them on the user interface. The user can review the presented product list, select the most suitable product, and purchase it.

[0951] Specific examples

[0952] For air purifiers

[0953] The user opens "EC Sensei" in a web browser on their PC. The homepage is displayed, and the user selects the air purifier category. A form for entering detailed conditions for the air purifier is then displayed. The user enters the following conditions: price (up to 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (available), and smartphone connectivity (available). The device uses a camera and microphone to analyze the user's facial expressions and voice, and obtains emotional data. This emotional data and the selection conditions are then sent to the server.

[0954] The server sends this data to an AI engine, which begins collecting and analyzing product information. Data is collected from word-of-mouth sites, e-commerce sites, and product review sites, and analyzed and scored using NLP technology. Products are ranked taking emotional data into consideration. As a result, an optimal product list is generated, and additional information such as "things to note when purchasing," "cheapest site," and "recommended features" is added. The server then sends the generated product list and related information to the device, which displays it. The user selects the optimal product and decides to purchase.

[0955] Example of input prompt for generative AI model

[0956] "Please find and recommend the best air purifier based on user feedback and reviews, with a maximum price of ¥30,000, an applicable area of ​​up to 20 tatami mats, filter replacement frequency of once a year, humidification function, and smartphone connectivity. Please also take into account user sentiment data."

[0957] By analyzing users' detailed selection criteria and emotional data, this system can significantly reduce the difficulty of selection and the risk of making the wrong purchase that are associated with traditional online shopping, thereby improving the user's purchasing experience.

[0958] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0959] Step 1:

[0960] The user opens the "EC Sensei" application or website on their device, such as a PC, smartphone, or tablet.

[0961] Specific operation: The user launches a web browser and enters the URL of "EC Sensei" to access it. Input: Target URL. Output: The homepage is displayed.

[0962] Step 2:

[0963] The terminal displays the interface of the application or website and prompts the user to select a product category.

[0964] Specific operation: The terminal renders and displays the homepage according to the user's access. Input: User access. Output: A product category selection screen is displayed.

[0965] Step 3:

[0966] The user selects a product category (e.g., air purifier).

[0967] Specific operation: The user taps or clicks on a category from the options on the screen. Input: The user's selection. Output: The selected category information.

[0968] Step 4:

[0969] The device will display a detailed selection criteria input form based on the selected category.

[0970] Specific operation: The terminal dynamically generates and displays a detailed condition input form for products corresponding to the selected category. Input: Selected category information. Output: Display of detailed condition input form.

[0971] Step 5:

[0972] The user enters detailed selection criteria (e.g., maximum price 30,000 yen, applicable area 20 tatami mats, filter replacement frequency once a year, humidification function, smartphone connectivity).

[0973] Specific operation: The user enters the selection criteria in the displayed form and presses the submit button. Input: User inputs the selection criteria. Output: Selection criteria data.

[0974] Step 6:

[0975] The device collects the user's emotional data using a camera, microphone, and touch sensor, along with detailed selection criteria.

[0976] Specific operation: The device captures facial expressions with a camera, records audio with a microphone, and obtains touch sensor operation data. Input: User selection criteria and emotion data. Output: Collected selection criteria data and emotion data.

[0977] Step 7:

[0978] The terminal transmits the collected selection condition data and emotion data to the server.

[0979] Specific operation: The device sends an HTTP request to the server, sending selection criteria data and emotion data via the API. Input: Selection criteria data and emotion data. Output: Data transmission to the server completed.

[0980] Step 8:

[0981] The server feeds the received data to the AI ​​engine, which starts the analysis process.

[0982] Specific operation: The server saves the data in the database and supplies it to the AI ​​engine. Input: Selection criteria data and emotion data. Output: Start of the analysis process.

[0983] Step 9:

[0984] The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[0985] Specific operation: The server uses scraping technology or API to obtain product data from external sites. Input: Selection criteria. Output: Collected product data.

[0986] Step 10:

[0987] The server uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[0988] Specific operation: The NLP engine extracts keywords and performs sentiment analysis on text data to extract influential reviews. Input: Collected product data. Output: Analysis result data.

[0989] Step 11:

[0990] The server scores and ranks products, taking into account emotional data.

[0991] Specific operation: The AI ​​engine integrates emotion data and analysis results to calculate product scores and create rankings. Input: Analysis result data, emotion data. Output: Scoring and ranking data.

[0992] Step 12:

[0993] The server generates a list of rated and ranked products and adds additional information such as "things to note when purchasing," "cheapest site," and "recommended features."

[0994] Specific operation: The server generates a product list based on the ranking data and adds supplementary information. Input: Scoring and ranking data. Output: Generated product list.

[0995] Step 13:

[0996] The server transmits the generated product list and additional information to the terminal.

[0997] Specific operation: The server sends data to the terminal as an HTTP response. Input: Generated product list. Output: Data sent to the terminal completed.

[0998] Step 14:

[0999] The terminal displays the product list and additional information on a user interface.

[1000] Specific operation: The terminal parses the display data and displays it on the interface. Input: Product list data. Output: Information is presented to the user.

[1001] Step 15:

[1002] The user checks the presented product list and selects and purchases the most suitable product.

[1003] Specific operation: The user scrolls through the displayed product list, selects the most suitable product, and presses the purchase button. Input: Product list. Output: Selection and purchase completed.

[1004] (Application example 2)

[1005] 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."

[1006] Conventional online shopping systems make it difficult for users to efficiently select the most suitable product from a vast selection of products. Furthermore, because they do not take into account the user's emotional state, the selected product may not meet the user's expectations, resulting in a dissatisfying shopping experience.

[1007] 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 inputting selection conditions for products desired by the user, means including a sensor for collecting user emotional data, communication means for collecting data related to the products based on the input selection conditions and emotional data, artificial intelligence means for analyzing the collected data and evaluating and ranking the products, means for presenting a list of evaluated and ranked products to the user, and means for attaching additional information to the presented product list, including "points to note when purchasing," "cheapest site," and "recommended features" for each product. This makes it possible to analyze the user's detailed selection conditions and emotional data and efficiently select and provide optimal products.

[1008] "User" refers to an individual who selects and purchases a particular product or service.

[1009] "Emotional data" is data that indicates the user's emotional state and is collected through sensors such as cameras and microphones.

[1010] A "sensor" refers to a device that senses an external physical or chemical phenomenon and outputs it as an electrical signal.

[1011] "Artificial intelligence means" refers to a system that includes algorithms and programs for collecting and analyzing data and proposing optimal products based on the results.

[1012] "Natural language processing means" refers to technology and software that understands, analyzes, and extracts meaning from human language.

[1013] "Communication means" refers to the technology and protocols used to transmit and receive data between multiple devices or systems.

[1014] A "product list" is a list of multiple products that have been rated and ranked, and includes detailed information about each product.

[1015] "Additional information" is information attached to the product list, and includes such things as "things to note when purchasing," "cheapest site," and "recommended features."

[1016] A "product category" refers to a classification item that groups together a group of products with similar characteristics.

[1017] "Conditions" means any specific requirements or constraints specified by a User when selecting a Product.

[1018] A "word-of-mouth site" is a website where consumers can post ratings and reviews of products they have used.

[1019] "E-commerce site" refers to an online platform through which goods and services are bought and sold on a web-based basis.

[1020] A "product review site" refers to a website where consumers can post product ratings and comments and other consumers can view that information.

[1021] The present invention relates to an online shopping system that enables users to efficiently select the most suitable product. This system is realized with the following configuration.

[1022] System Configuration

[1023] User's device

[1024] Hardware: Smartphones, tablets, PCs, smart glasses

[1025] Software: "Shopping Assistant" application or website

[1026] First, the user opens the "Shopping Assistant" application on their device and selects the category of product they are looking for (e.g., home appliances). Next, they enter detailed selection criteria such as price, features, and brand. To collect emotion data, the device's built-in camera and microphone are used to collect the user's facial and voice data. This data is then sent to the server.

[1027] server

[1028] The server performs the following process:

[1029] Data collection: The server collects data about the product based on the received selection criteria and emotion data. For example, it collects product ratings and reviews from word-of-mouth sites, e-commerce sites, and product review sites. This data is acquired using communication methods.

[1030] Data analysis: Using artificial intelligence and natural language processing, we analyze the collected text and sentiment data. We score products and generate rankings taking into account the sentiment data.

[1031] Generate a list of rated products: Generate a list of rated and ranked products, and add additional information to each product, such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[1032] Product list presentation

[1033] Presentation method: The product list and additional information sent from the server are displayed on the user's device. The user can select the most suitable product based on the presented information and decide to purchase it.

[1034] Specific examples

[1035] For example, suppose a user is looking for an air purifier. In this case, the user puts on the smart glasses and operates the "Shopping Assistant" app by voice, inputting detailed requirements for the air purifier (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.). The camera and microphone collect facial and voice data, which is then sent to a server. The server collects and analyzes product data based on the selection criteria and emotion data, and generates an optimal product list. This list is displayed on the smart glasses' display, allowing the user to select the most suitable product.

[1036] Prompt Sentence Examples

[1037] Let's say a user is looking for an air purifier, and they input the following criteria: price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity, and then we created an application that suggests the most suitable product based on sentiment analysis.

[1038] In this way, the online shopping system of the present invention can provide a high level of satisfaction by taking into consideration the user's feelings and selection conditions.

[1039] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1040] Step 1:

[1041] The user opens the "Shopping Assistant" application on the device. The user selects the desired product category (e.g., home appliances) and enters detailed selection criteria (price, features, brand, etc.). The entered selection criteria are retrieved by the device.

[1042] Step 2:

[1043] The device uses a camera and microphone to collect facial and voice data from the user, and generates input data for analyzing emotional data based on the collected sensor data.

[1044] Step 3:

[1045] The terminal transmits the input selection conditions and analyzed emotion data to the server, which receives this data and prepares to start collecting data about the product.

[1046] Step 4:

[1047] The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites based on the selection criteria and emotion data. The collected data is passed to the next analysis step.

[1048] Step 5:

[1049] The server uses natural language processing to analyze the collected text data of word-of-mouth and reviews, and the analyzed text data becomes input data for rating and ranking products.

[1050] Step 6:

[1051] The server uses artificial intelligence means to score products taking into account the selection criteria and emotion data, and the scored data serves as input data for generating a product list.

[1052] Step 7:

[1053] The server generates a list of rated and ranked products, and adds additional information to each product, such as "points to note when purchasing," "cheapest site," and "recommended features." The generated product list is generated as output data.

[1054] Step 8:

[1055] The server sends the generated product list and additional information to the terminal, which receives it and displays it on the user's interface.

[1056] Step 9:

[1057] The user reviews the presented product list and additional information, selects the most suitable product, and then proceeds to purchase the selected product.

[1058] In this way, by processing input data and generating output data at each step, users can efficiently select the most suitable product taking into account their emotional data.

[1059] 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.

[1060] 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.

[1061] 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.

[1062] [Third embodiment]

[1063] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1064] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1065] 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).

[1066] 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.

[1067] 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.

[1068] 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).

[1069] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1070] 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.

[1071] 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.

[1072] 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.

[1073] 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.

[1074] 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."

[1075] This invention is a system that allows users to select the most suitable product when shopping online. It uses AI to analyze the selection criteria of the product desired by the user and presents the most suitable product. This reduces the difficulty of product selection in conventional online shopping and the risk of mistaken purchases caused by false labeling and exaggerated advertising.

[1076] System Configuration

[1077] The system of the present invention is composed of a user terminal, a server, and a communication means. The role and operation of each component will be explained in detail below.

[1078] User's device

[1079] 1. User: Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.).

[1080] 2. Terminal: Displays the interface and allows the user to select a product category.

[1081] 3. User: Select a product category (e.g., air purifier).

[1082] 4. Terminal: Based on the selected category, a detailed selection criteria input form will be displayed.

[1083] 5. User: Enter detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.).

[1084] server

[1085] 6. Terminal: Sends the entered selection criteria data to the server.

[1086] 7. Server: Receives the selection conditions and starts the AI ​​engine.

[1087] 8. Server: The AI ​​engine collects relevant product data from multiple data sources (word-of-mouth sites, e-commerce sites, product review sites, etc.) based on the selection criteria.

[1088] 9. Server:

[1089] Natural language processing (NLP) technology is used to analyze collected word-of-mouth and review text data.

[1090] Products are scored based on the analysis results and a ranking is generated.

[1091] Product list presentation

[1092] 10. Server: Generates a scored and ranked product list and adds additional information for each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features."

[1093] 11. Server: Sends the generated product list and additional information to the terminal.

[1094] 12. Terminal: Displays the product list and additional information in a user interface.

[1095] 13. User: Check the presented products and select and purchase the most suitable product.

[1096] Specific examples

[1097] For air purifiers

[1098] Starting the system

[1099] 1. User: Open "EC Sensei" in a web browser.

[1100] 2. Device: Display the homepage.

[1101] Condition Input Phase

[1102] 3. User: Select the Air Purifier category.

[1103] 4. Device: Display the detailed conditions input form for the air purifier.

[1104] 5. User: Enter the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[1105] Product selection phase by AI

[1106] 6. Terminal: Sends condition data to the server.

[1107] 7. Server: Sends condition data to the AI ​​engine and begins collecting and analyzing product information.

[1108] 8. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites, and analyzes and scores it using NLP technology.

[1109] Optimal product presentation phase

[1110] 9. Server: Generates a list of optimal products and adds features such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[1111] 10. Server: Sends the product list to the terminal.

[1112] 11. Terminal: Displays product list and additional information.

[1113] 12. User: Selects the best product and decides to purchase.

[1114] This allows users to easily select the most suitable product based on reliable information. This specific embodiment supports the claims and clarifies the technical scope of the invention.

[1115] The processing flow will be explained below.

[1116] Step 1:

[1117] User: Open the "EC Sensei" application or website on your device.

[1118] Launch a web browser and enter the specified URL or tap the application icon.

[1119] Step 2:

[1120] Server: Receives the user's request, generates the HTML / CSS / JavaScript resources for the homepage, and sends them to the terminal.

[1121] Based on user requests, homepage data is dynamically generated and transmitted.

[1122] Step 3:

[1123] User: Select a product category (e.g., air purifier).

[1124] Click on the drop-down menu or icon to select the product category you want.

[1125] Step 4:

[1126] Server: Based on the selected category, a related detailed selection criteria input form is generated and sent to the terminal.

[1127] The input form corresponding to the product category is retrieved from the database, and the data required for displaying it is generated and sent.

[1128] Step 5:

[1129] User: Enter detailed selection criteria (e.g. price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[1130] Enter the condition in the input field and select an option.

[1131] Step 6:

[1132] Terminal: Organizes the entered selection criteria data and sends a request to the server in JSON format.

[1133] Converts form data into JSON format and sends a request to the specified API endpoint.

[1134] Step 7:

[1135] Server: Passes the received selection criteria data to the AI ​​engine and starts the data collection process.

[1136] Based on the conditions, it triggers an AI module to collect product-related information from multiple data sources.

[1137] Step 8:

[1138] Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[1139] Use APIs and scraping techniques to collect product information from designated data sources.

[1140] Step 9:

[1141] Server: Uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[1142] The NLP engine is activated to analyze the text data and extract important keywords and evaluation points.

[1143] Step 10:

[1144] Server: Based on the analysis results, the products are scored and a ranking is generated.

[1145] A scoring algorithm is applied to rank the products that best match the criteria.

[1146] Step 11:

[1147] Server: Generates a list of optimal products and adds additional information for each product, such as "things to note when purchasing," "cheapest site," and "recommended features."

[1148] Generate data in JSON format that includes relevant information in the product list.

[1149] Step 12:

[1150] Server: Sends the generated product list and additional information to the terminal.

[1151] The product list and related information are sent to the terminal and prepared for display.

[1152] Step 13:

[1153] Terminal: Analyzes the received product list and additional information and displays it on the user interface.

[1154] Convert the JSON data into HTML and display the information to the user.

[1155] Step 14:

[1156] User: Check the presented products, select the most suitable product and purchase it.

[1157] Based on the product information provided, select the desired product and proceed with the purchase.

[1158] This allows users to input detailed product selection criteria and efficiently select the most suitable products with the help of AI.

[1159] Example 1

[1160] 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."

[1161] Today's consumers often find it difficult to select the best product from the numerous product options available when shopping online. There is also the risk of making a mistaken purchase due to false and exaggerated advertising. Furthermore, checking a large number of customer testimonials and reviews one by one is extremely time-consuming and labor-intensive. These issues often make it difficult for consumers to choose the right product.

[1162] 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.

[1163] In this invention, the server includes a means for inputting selection criteria for products desired by the user, a communication means for collecting information about the products based on the input selection criteria, and an artificial intelligence means for analyzing the collected information and evaluating and ranking the products. This reduces the difficulty of product selection and the risk of making an erroneous purchase, and enables users to easily select the most suitable product based on reliable information.

[1164] "Means for users to input selection criteria for desired products" refers to means for providing an interface that allows users to input the characteristics and requirements of desired products using devices such as PCs or smartphones.

[1165] "Communication means for collecting information about products based on input selection criteria" refers to a network communication device and protocol for collecting information about products from various data sources on the Internet based on criteria specified by the user.

[1166] "Artificial intelligence means for analyzing collected information and evaluating and ranking products" refers to an AI system that includes machine learning algorithms and natural language processing technology to automatically analyze collected data and statistically analyze the characteristics and evaluations of each product to set a rank.

[1167] A "means for presenting a rated and ranked product list to a user" is a display device or interface that displays the AI-ranked product list in a user-friendly format, allowing the user to easily select the most suitable product.

[1168] "A means for adding additional information to the presented product list, including 'points to note when purchasing,' 'lowest price information,' and 'recommended features' for each product" refers to an information processing system that automatically generates and adds to the evaluated product list information such as points to note when purchasing each product, price comparison information with other sales sites, and features that are particularly superior in comparison with other products.

[1169] The "means for allowing a user to select a category" is a means for providing an interface for the user to select a category of a product to be searched for.

[1170] The "means for displaying related product selection conditions based on the selected category" is a means for providing an interface for inputting detailed selection conditions for the relevant product according to the category selected by the user.

[1171] "Means for collecting data from review sites, e-commerce sites, and product rating sites" refers to a data acquisition mechanism using crawling technology and APIs to efficiently collect detailed product data from multiple sources on the Internet.

[1172] "Natural language processing means for analyzing collected data" refers to an analysis system that includes natural language processing technology for analyzing collected text data (word of mouth, reviews, etc.) and extracting and structuring meaning from the data.

[1173] This invention is a system that allows users to select the most suitable product when shopping online. Specifically, the system inputs the selection criteria for the desired product, analyzes them using AI, and presents the most suitable product. This system is composed of a user terminal, a server, and communication means.

[1174] User's device

[1175] Device behavior

[1176] Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.). The user interface will be displayed, prompting the user to select a product category and displaying a form for entering detailed selection criteria. When the user enters detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.), the data will be sent to the server.

[1177] server

[1178] Server Operation

[1179] The server receives the selection criteria data sent from the device and activates the AI ​​engine. The AI ​​engine collects data from multiple data sources (e.g., word-of-mouth sites, e-commerce sites, product review sites) based on the selection criteria. The collected data is analyzed using natural language processing (NLP) technology to score and rank each product.

[1180] Product list presentation

[1181] Product proposals

[1182] The server generates a scored and ranked product list and adds additional information for each product, including "points to note when purchasing," "lowest price information," and "recommended features." This generated product list and additional information are sent to the terminal, which displays the product list and additional information on the user interface. The user can review the presented products and select the most suitable one.

[1183] Specific examples

[1184] For air purifiers

[1185] Starting the system

[1186] 1. The user opens "EC Sensei" in a web browser.

[1187] 2. The device displays the homepage.

[1188] Condition Input Phase

[1189] 3. The user selects the Air Purifier category.

[1190] 4. The device will display a form to input detailed conditions for the air purifier.

[1191] 5. The user enters the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[1192] Product selection phase by AI

[1193] 6. The device sends the condition data to the server.

[1194] 7. The server sends the condition data to the AI ​​engine and begins collecting and analyzing product information.

[1195] 8. The server collects data from word-of-mouth sites, e-commerce sites, and product review sites, and analyzes and scores it using NLP technology.

[1196] Optimal product presentation phase

[1197] 9. The server generates a list of optimal products and adds information such as "points to note when purchasing," "lowest price information," and "recommended features."

[1198] 10. The server sends the product list to the terminal.

[1199] 11. The device will display a list of products and additional information.

[1200] 12. The user selects the best product and decides to purchase.

[1201] Example prompts for generative AI models

[1202] Prompt statement:

[1203] Please describe the process by which a user would use the "EC Sensei" system to select the best air purifier based on the following selection criteria: price (up to ¥30,000), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (available), smartphone connectivity (available)

[1204] By inputting this prompt into a generative AI model, users can efficiently select the most suitable product.

[1205] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1206] Step 1:

[1207] The user opens the "EC Sensei" application or website on a device such as a PC or smartphone.

[1208] Input: Device launch and application or browser access.

[1209] Output: Application or browser homepage display.

[1210] Specific action: The user taps the application icon or enters the URL in the browser to open the site.

[1211] Step 2:

[1212] The terminal displays a home page and prompts the user to select a product category.

[1213] Input: The user's access request.

[1214] Output: Display of product category selection screen.

[1215] Specific operation: The device renders the "EC Sensei" homepage and offers product category selection.

[1216] Step 3:

[1217] The user selects a product category (e.g., air purifiers).

[1218] Input: A category selected by the user.

[1219] Output: Save selected category information.

[1220] Specific Action: User clicks on the Air Purifiers category.

[1221] Step 4:

[1222] The device will display a detailed selection criteria input form based on the selected category.

[1223] Input: Selected product category information.

[1224] Output: Display of detailed selection criteria input form.

[1225] Specific operation: The device renders and displays a detailed input form (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.) according to the selected category.

[1226] Step 5:

[1227] The user enters detailed selection criteria.

[1228] Input: Detailed selection criteria (e.g. price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), smartphone connectivity (yes)).

[1229] Output: Saves the entered selection criteria data.

[1230] Specific operation: The user enters values ​​or options for each condition item and presses the submit button.

[1231] Step 6:

[1232] The terminal transmits the input condition data to the server.

[1233] Input: Detailed selection criteria data.

[1234] Output: Sending data to the server.

[1235] Specific operation: The terminal generates an HTTP request and sends the condition data in JSON format to the server.

[1236] Step 7:

[1237] The server supplies the received selection condition data to the AI ​​engine.

[1238] Input: The received selection criteria data.

[1239] Output: Data feed to the AI ​​engine.

[1240] Specific operation: The server stores data in a database and provides that data as input to the AI ​​engine.

[1241] Step 8:

[1242] The server's AI engine collects data from multiple data sources (e.g., word-of-mouth sites, e-commerce sites, product review sites) based on selection criteria.

[1243] Input: Selection criteria data.

[1244] Output: Collected product data.

[1245] What it does: The AI ​​engine uses APIs and web scraping technology to collect relevant product data from designated sites.

[1246] Step 9:

[1247] The server uses natural language processing (NLP) techniques to analyze the collected data and score and rank the products.

[1248] Input: Collected text data (word of mouth, reviews, etc.).

[1249] Output: Analysis results and scored product list.

[1250] Specific operation: Text data is input into the NLP model, analyzed, and product characteristics and evaluation scores are calculated and ranked.

[1251] Step 10:

[1252] The server generates a list of rated and ranked products and adds additional information such as "things to note when purchasing," "lowest price information," and "recommended features."

[1253] Input: Scored product list.

[1254] Output: Final product list with additional information added.

[1255] Specific operation: The server generates information about each product, such as warnings, features, and price comparisons, and adds it to the scored list.

[1256] Step 11:

[1257] The server transmits the generated product list and additional information to the terminal.

[1258] Input: Final product list.

[1259] Output: Sending data to the terminal.

[1260] Specific operation: Generates an HTTP response to send the product list and additional information in JSON format to the terminal.

[1261] Step 12:

[1262] The terminal displays a list of products and additional information.

[1263] Input: Product list and additional information sent from the server.

[1264] Output: Display to the user interface.

[1265] What happens: The device renders the product list and additional information and displays it on the screen.

[1266] Step 13:

[1267] The user checks the products presented and selects and purchases the most suitable product.

[1268] Input: Displayed product list and additional information.

[1269] Output: Product selection and purchase confirmation.

[1270] Specific operation: The user checks the product list, clicks on the product they want to purchase, and completes the purchase process.

[1271] (Application example 1)

[1272] 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."

[1273] In conventional online shopping, users often face an overwhelming number of options when selecting the products they need, and are often misled by exaggerated advertising and false representations, making it difficult to select the optimal product. Furthermore, collecting and analyzing reliable information from multiple data sources requires a great deal of effort. There is an urgent need to provide a system that can solve these problems and enable users to quickly and reliably select the optimal product.

[1274] 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.

[1275] In this invention, the server includes: means for inputting selection criteria for a desired product by a user; communication means for collecting data on the products based on the input selection criteria; artificial intelligence means for analyzing the collected data and rating and ranking the products; means for presenting a list of rated and ranked products to the user; means for adding additional information to the presented product list, including "points to note when purchasing," "cheapest sites," and "recommended features," for each product; means for transmitting the product selection criteria input by the user via the user interface to the server; means for an artificial intelligence engine within the server to collect and analyze product information from a data source based on the user's input criteria; and means for displaying the analysis results on the user interface. This enables users to quickly and accurately select optimal products based on reliable data.

[1276] "Users" are individuals or groups who search for products through online shopping and consider purchasing them.

[1277] "Choice criteria" are the specific features or criteria that a user seeks when purchasing a product, such as price, functionality, or quality.

[1278] "Communication means" refers to the technology and infrastructure for sending and receiving data between the user's device and the server, including the Internet and wireless communications.

[1279] "Artificial intelligence tools" refer to algorithms and techniques used to analyze collected data and evaluate and rank products. Machine learning and deep learning techniques are primarily used.

[1280] "Rating and ranking" refers to scoring products based on user selection criteria and sorting them in an appropriate order. This process includes analyzing word-of-mouth and reviews.

[1281] "Presenting" is the act of showing a user a rated and ranked product list and its additional information.

[1282] "Purchase precautions" is information that indicates important points that users should consider when purchasing a product. For example, it includes product-specific drawbacks and usage precautions.

[1283] A "cheapest site" is a sales site where you can purchase a particular product at the lowest price.

[1284] "Recommended features" refer to the particularly outstanding functions or features of a particular product.

[1285] "User interface" refers to the screens and operating methods that allow users to directly interact with systems and applications.

[1286] "Data source" refers to an online source of information from which product information is collected, such as a word-of-mouth site, an e-commerce site, or a product review site.

[1287] "Natural language processing" is a technology that analyzes collected text data such as word-of-mouth and reviews and converts it into meaningful information. It mainly uses machine learning algorithms.

[1288] The system for carrying out this invention is composed of a user terminal, a server, and an infrastructure that connects these via communication means. Specifically, the system provides a user interface for users to select products, collects and analyzes data on the server side based on the selection criteria, and presents the most suitable products.

[1289] User's device

[1290] The terminal is an electronic device such as a smartphone, personal computer, or tablet, and provides an interface for users to input selection criteria for their desired products. The user uses this interface to input product categories and detailed selection criteria.

[1291] Specific example of input procedure

[1292] 1. User: Launch the EC Sensei application on their smartphone.

[1293] 2. Device: View product categories on the app homepage.

[1294] 3. User: Select the Air Purifier category.

[1295] 4. Device: Display the detailed conditions input form for the air purifier.

[1296] 5. User: Enter the desired price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity conditions.

[1297] Server Processing

[1298] The server activates an AI engine based on each user's input and collects product information from multiple data sources. It then uses natural language processing (NLP) technology to analyze text data from user reviews and scores products. Furthermore, the product list, which is scored based on the analysis results, includes additional information such as "things to note when purchasing," "the site with the lowest price," and "recommended features."

[1299] Software Configuration

[1300] AI Engine: Analyzes customer testimonials and reviews using deep learning frameworks like TensorFlow or PyTorch.

[1301] Framework: Uses Flask to manage communication between the server and the user interface.

[1302] Communication library: Uses the Python Requests library to send and receive data.

[1303] Specific examples of processing procedures

[1304] 1. Terminal: The selection criteria entered by the user are sent to the server.

[1305] 2. Server: Sends condition data to the AI ​​engine and begins collecting and analyzing product information.

[1306] 3. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites.

[1307] 4. Server: Analyzes data using natural language processing and scores products.

[1308] 5. Server: Generates a list of optimal products and adds features such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[1309] 6. Server: Sends the product list to the terminal.

[1310] 7. Terminal: Displays product list and additional information.

[1311] 8. User: Selects the best product and decides to purchase.

[1312] Prompt Sentence Examples

[1313] Conditions for purchase: The user opens the smartphone app "EC Sensei" and enters the details of the air purifier they require. The desired conditions are "price under 30,000 yen," "applicable area up to 20 tatami mats," "filter replacement frequency once a year," "humidification function," and "smartphone connectivity."

[1314] Input: Enter "air purifier," "under 30,000 yen," "20 tatami mats," "once a year," "humidifier function," and "smartphone connectivity" into the user interface.

[1315] Output: After AI analysis, a list of the "best air purifiers" is presented, along with reviews for each product, the lowest price store, and details of recommended features.

[1316] The above is a mode for carrying out the invention, and enables users to quickly and accurately select the most suitable product based on reliable data.

[1317] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1318] Step 1:

[1319] The user launches the EC Sensei application on their smartphone and selects a product category.

[1320] Input: A user launches the application and selects "Air Purifier" as the product category.

[1321] Output: A form for entering detailed conditions for the air purifier will be displayed on the terminal.

[1322] Step 2:

[1323] The user enters detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[1324] Input: The user enters conditions such as "price under 30,000 yen," "applicable area up to 20 tatami mats," "filter replacement frequency once a year," "humidification function included," and "smartphone connectivity available."

[1325] Output: The entered selection criteria are displayed on the terminal and are ready to be sent to the server.

[1326] Step 3:

[1327] The terminal transmits the input selection condition data to the server.

[1328] Input: Selection criteria data entered by the user.

[1329] Output: The condition data is sent to the server.

[1330] Step 4:

[1331] The server receives the condition data and starts the AI ​​engine.

[1332] Input: The submitted selection criteria data.

[1333] Output: The AI ​​engine is now up and running, ready to start collecting and analyzing product information from data sources.

[1334] Step 5:

[1335] The server collects product information from multiple data sources (word-of-mouth sites, e-commerce sites, product review sites).

[1336] Input: Product selection criteria specified by the AI ​​engine.

[1337] Output: Collected product information data. For example, text data of word-of-mouth and reviews.

[1338] Step 6:

[1339] The server analyzes the collected data using natural language processing (NLP) and scores the products.

[1340] Input: Collected text data of word-of-mouth and reviews.

[1341] The analysis involves extracting evaluation scores and important features from text data.

[1342] Output: Rating score and ranking for each product.

[1343] Step 7:

[1344] The server generates a list of rated and ranked products and attaches additional information including "things to note when purchasing," "cheapest sites," and "recommended features."

[1345] Input: Scoring results and additional information.

[1346] Output: A detailed product list.

[1347] Step 8:

[1348] The server transmits the generated product list and additional information to the terminal.

[1349] Input: A rated and ranked list of products and their additional information.

[1350] Output: The product list and additional information are sent to the terminal.

[1351] Step 9:

[1352] The terminal displays the product list and additional information on a user interface.

[1353] Input: Product list and additional information received from the server.

[1354] Output: A user interface with a list of products and their details.

[1355] Step 10:

[1356] The user checks the presented product list, selects the most suitable product, and decides to purchase it.

[1357] Input: Proposed product list and additional information.

[1358] Output: The product selected by the user and a purchase decision is made.

[1359] The above are the processing steps of the system program that realizes the application example.

[1360] 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.

[1361] The present invention relates to a system that allows users to efficiently select optimal products when shopping online. In particular, it aims to solve the problems of conventional systems by combining the user's selection criteria and emotional data to suggest optimal products. The present invention is realized using a user's terminal, a server, an artificial intelligence engine, and an emotional engine.

[1362] System Configuration and Operation

[1363] This system has the following configuration and operation.

[1364] User's device

[1365] 1. User: Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.).

[1366] 2. Terminal: Displays the interface and allows the user to select a product category.

[1367] 3. User: Select a product category (e.g., air purifier).

[1368] 4. Terminal: Based on the selected category, a detailed selection criteria input form will be displayed.

[1369] 5. User: Enter detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.).

[1370] Emotion Engine Operation

[1371] 1. Terminal: Collects the user's emotion data along with the input selection criteria and sends it to the server. Emotion data is extracted from sensor data such as camera, microphone, and touch input.

[1372] 2. Server: Analyzes the received emotional data and determines the user's emotional state.

[1373] Server and AI engine

[1374] 1. Server: Passes the selection criteria data and emotion data to the AI ​​engine and begins data collection and analysis.

[1375] 2. Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[1376] 3. Server: Using natural language processing (NLP) technology, the collected text data of user comments and reviews is analyzed, and product scores and rankings are generated taking into account sentiment data.

[1377] Product list presentation

[1378] 1. Server: Generates a scored and ranked product list and adds additional information for each product, including "Points to Note When Purchasing," "Lowest Price Site," and "Recommended Features." It also adjusts the priority and content of the information presented based on emotional data.

[1379] 2. Server: Sends the generated product list and additional information to the terminal.

[1380] 3. Terminal: displays the product list and additional information in a user interface.

[1381] 4. User: Check the presented products and select and purchase the most suitable product.

[1382] Specific examples

[1383] For air purifiers

[1384] Starting the system

[1385] 1. User: Open "EC Sensei" in a web browser.

[1386] 2. Device: Display the homepage.

[1387] Condition input and emotion recognition phase

[1388] 1. User: Select the Air Purifier category.

[1389] 2. Device: Display the detailed conditions input form for the air purifier.

[1390] 3. User: Enter the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[1391] 4. Device: Analyzes the user's facial expressions and voice using a camera and microphone to obtain emotional data. The obtained emotional data and selection criteria are sent to the server.

[1392] Product selection phase by AI

[1393] 1. Server: Sends condition data and emotion data to the AI ​​engine and begins collecting and analyzing product information.

[1394] 2. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites, analyzes and scores it using NLP technology, and ranks products taking into account emotional data.

[1395] Optimal product presentation phase

[1396] 1. Server: Generates a list of optimal products and adds information such as "Points to note when purchasing," "Lowest price site," and "Recommended features." Adjusts the information presented based on emotional data.

[1397] 2. Server: Sends the product list and related information to the terminal.

[1398] 3. Terminal: Displays product list and additional information.

[1399] 4. User: Selects the best product and decides to purchase.

[1400] This makes it possible to significantly reduce the difficulty of selection and the risk of making a mistaken purchase in conventional online shopping by analyzing the user's detailed selection criteria and emotional data. This specific embodiment supports the claims and clarifies the technical scope of the invention.

[1401] The processing flow will be explained below.

[1402] Step 1:

[1403] User: Open the "EC Sensei" application or website on your device.

[1404] Launch a web browser and enter the specified URL or tap the application icon.

[1405] Step 2:

[1406] Server: Receives the user's request, generates the HTML / CSS / JavaScript resources for the homepage, and sends them to the terminal.

[1407] Based on user requests, homepage data is dynamically generated and transmitted.

[1408] Step 3:

[1409] User: Select a product category (e.g., air purifier).

[1410] Click on the drop-down menu or icon to select the product category you want.

[1411] Step 4:

[1412] Server: Based on the selected category, a related detailed selection criteria input form is generated and sent to the terminal.

[1413] The input form corresponding to the product category is retrieved from the database, and the data required for displaying it is generated and sent.

[1414] Step 5:

[1415] User: Enter detailed selection criteria (e.g. price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[1416] Enter the condition in the input field and select an option.

[1417] Step 6:

[1418] Terminal: Organizes the input selection criteria data and emotion data and sends a request in JSON format to the server.

[1419] Form data and emotion data obtained from the camera, microphone, etc. are converted into JSON format and sent to the specified API endpoint.

[1420] Step 7:

[1421] Server: Passes the received selection criteria data and emotion data to the AI ​​engine and starts the data collection process.

[1422] Based on the conditions and sentiment data, it activates an AI module to collect product-related information from multiple data sources.

[1423] Step 8:

[1424] Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[1425] Use APIs and scraping techniques to collect product information from designated data sources.

[1426] Step 9:

[1427] Server: Uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[1428] The NLP engine is activated to analyze the text data and extract important keywords and evaluation points, taking into account sentiment data.

[1429] Step 10:

[1430] Server: Based on the analysis results, the products are scored and a ranking is generated.

[1431] A scoring algorithm is applied to rank the products that best match the criteria and the user's emotional state.

[1432] Step 11:

[1433] Server: Generates a list of optimal products and adds additional information for each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features." Adjusts the priority and content of information based on emotional data.

[1434] Generate data in JSON format that includes relevant information in the product list.

[1435] Step 12:

[1436] Server: Sends the generated product list and additional information to the terminal.

[1437] The product list and related information are sent to the terminal and prepared for display.

[1438] Step 13:

[1439] Terminal: Analyzes the received product list and additional information and displays it on the user interface.

[1440] Convert the JSON data into HTML and display the information to the user.

[1441] Step 14:

[1442] User: Check the presented products, select the most suitable product and purchase it.

[1443] Based on the product information provided, select the desired product and proceed with the purchase.

[1444] This allows users to input detailed product selection criteria and emotional data, and with the help of AI, efficiently select the most suitable product.

[1445] Example 2

[1446] 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."

[1447] In conventional online shopping systems, users must manually compare and judge a large amount of information when selecting products based on their desired product selection criteria, which leads to a lack of efficiency and a high risk of making the wrong purchase. Furthermore, products are suggested without taking into account the user's emotional state, which can lead to problems in which the system does not adequately reflect the user's purchasing intentions. Furthermore, the collected data is fragmented, making it difficult to make a comprehensive evaluation. There is a need for a system that can solve these issues and enable users to select the optimal product in a short amount of time.

[1448] 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.

[1449] In this invention, the server includes a communication means for collecting selection criteria and emotional data for products desired by the user, a means for analyzing the collected selection criteria and emotional data and determining the emotional state, and an artificial intelligence means for collecting and analyzing data related to the products based on the determined emotional state and selection criteria. This makes it possible to evaluate and rank products and present an optimal product list after taking into account the user's detailed selection criteria and emotional data. This significantly reduces the difficulty of selection and the risk of purchasing the wrong product in conventional systems, improving the user's purchasing experience.

[1450] "User" refers to a person who uses the system or service to select and purchase products.

[1451] "Selection criteria" refers to specific requirements such as price, functionality, size, etc. that a user considers when selecting a product.

[1452] "Emotional data" refers to data that indicates the emotional state of a user analyzed from facial expressions, voice, operating behavior, etc.

[1453] "Communication means" refers to the technical elements used to send and receive data between a user's terminal and a server.

[1454] "Emotional state" refers to the psychological state determined by analyzing the user's emotional data.

[1455] "Artificial Intelligence Means" refers to the artificial intelligence technologies used to analyze, evaluate, and rank the collected data.

[1456] "Product List" refers to a list of information about analyzed and ranked products.

[1457] "Additional information" refers to supplementary information related to a product, such as "Points to note when purchasing," "Lowest price site," and "Recommended features," that is added to the product list.

[1458] "Sensor device" refers to hardware such as a camera, microphone, or touch sensor used to collect a user's emotional data.

[1459] "Natural language processing means" refers to natural language processing technology for mechanically understanding and analyzing text data of word-of-mouth and reviews.

[1460] This invention is a system that allows users to efficiently select the most suitable product when shopping online. Specifically, it aims to solve the problems of conventional systems by combining the user's selection criteria and emotional data to suggest the most suitable product. This system is realized using a user's terminal, a server, an artificial intelligence engine, and an emotional engine.

[1461] User's device

[1462] The user opens the "EC Sensei" application or website on their device, such as a PC, smartphone, or tablet. The device displays the application or website interface and allows the user to select a product category. Once the user selects the desired product category (e.g., air purifier), a form for entering detailed selection criteria is displayed. Here, the user enters detailed selection criteria such as price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity.

[1463] Emotion Engine Operation

[1464] The device collects the user's emotional data, along with detailed selection conditions, using sensor devices such as a camera, microphone, and touch sensor. This emotional data is extracted from the user's facial expressions, voice, and the speed and strength of touch operations. The collected emotional data and selection condition data are sent from the device to the server.

[1465] Server and AI engine

[1466] The server receives the selection criteria data and emotion data sent by the user and supplies them to the AI ​​engine to begin the analysis process. The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites (e.g., Amazon, Rakuten, Yahoo! Shopping). It then uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews, scoring and ranking products while also taking into account the user's emotional state.

[1467] Product list presentation

[1468] The server generates a rated and ranked product list based on the analysis and scoring results. This product list includes additional information such as "things to note when purchasing," "cheapest sites," and "recommended features," and the presentation priority and content of this information are adjusted based on the emotional data. The generated product list and additional information are sent from the server to the terminal, which displays them on the user interface. The user can review the presented product list, select the most suitable product, and purchase it.

[1469] Specific examples

[1470] For air purifiers

[1471] The user opens "EC Sensei" in a web browser on their PC. The homepage is displayed, and the user selects the air purifier category. A form for entering detailed conditions for the air purifier is then displayed. The user enters the following conditions: price (up to 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (available), and smartphone connectivity (available). The device uses a camera and microphone to analyze the user's facial expressions and voice, and obtains emotional data. This emotional data and the selection conditions are then sent to the server.

[1472] The server sends this data to an AI engine, which begins collecting and analyzing product information. Data is collected from word-of-mouth sites, e-commerce sites, and product review sites, and analyzed and scored using NLP technology. Products are ranked taking emotional data into consideration. As a result, an optimal product list is generated, and additional information such as "things to note when purchasing," "cheapest site," and "recommended features" is added. The server then sends the generated product list and related information to the device, which displays it. The user selects the optimal product and decides to purchase.

[1473] Example of input prompt for generative AI model

[1474] "Please find and recommend the best air purifier based on user feedback and reviews, with a maximum price of ¥30,000, an applicable area of ​​up to 20 tatami mats, filter replacement frequency of once a year, humidification function, and smartphone connectivity. Please also take into account user sentiment data."

[1475] By analyzing users' detailed selection criteria and emotional data, this system can significantly reduce the difficulty of selection and the risk of making the wrong purchase that are associated with traditional online shopping, thereby improving the user's purchasing experience.

[1476] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1477] Step 1:

[1478] The user opens the "EC Sensei" application or website on their device, such as a PC, smartphone, or tablet.

[1479] Specific operation: The user launches a web browser and enters the URL of "EC Sensei" to access it. Input: Target URL. Output: The homepage is displayed.

[1480] Step 2:

[1481] The terminal displays the interface of the application or website and prompts the user to select a product category.

[1482] Specific operation: The terminal renders and displays the homepage according to the user's access. Input: User access. Output: A product category selection screen is displayed.

[1483] Step 3:

[1484] The user selects a product category (e.g., air purifier).

[1485] Specific operation: The user taps or clicks on a category from the options on the screen. Input: The user's selection. Output: The selected category information.

[1486] Step 4:

[1487] The device will display a detailed selection criteria input form based on the selected category.

[1488] Specific operation: The terminal dynamically generates and displays a detailed condition input form for products corresponding to the selected category. Input: Selected category information. Output: Display of detailed condition input form.

[1489] Step 5:

[1490] The user enters detailed selection criteria (e.g., maximum price 30,000 yen, applicable area 20 tatami mats, filter replacement frequency once a year, humidification function, smartphone connectivity).

[1491] Specific operation: The user enters the selection criteria in the displayed form and presses the submit button. Input: User inputs the selection criteria. Output: Selection criteria data.

[1492] Step 6:

[1493] The device collects the user's emotional data using a camera, microphone, and touch sensor, along with detailed selection criteria.

[1494] Specific operation: The device captures facial expressions with a camera, records audio with a microphone, and obtains touch sensor operation data. Input: User selection criteria and emotion data. Output: Collected selection criteria data and emotion data.

[1495] Step 7:

[1496] The terminal transmits the collected selection condition data and emotion data to the server.

[1497] Specific operation: The device sends an HTTP request to the server, sending selection criteria data and emotion data via the API. Input: Selection criteria data and emotion data. Output: Data transmission to the server completed.

[1498] Step 8:

[1499] The server feeds the received data to the AI ​​engine, which starts the analysis process.

[1500] Specific operation: The server saves the data in the database and supplies it to the AI ​​engine. Input: Selection criteria data and emotion data. Output: Start of the analysis process.

[1501] Step 9:

[1502] The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[1503] Specific operation: The server uses scraping technology or API to obtain product data from external sites. Input: Selection criteria. Output: Collected product data.

[1504] Step 10:

[1505] The server uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[1506] Specific operation: The NLP engine extracts keywords and performs sentiment analysis on text data to extract influential reviews. Input: Collected product data. Output: Analysis result data.

[1507] Step 11:

[1508] The server scores and ranks products, taking into account emotional data.

[1509] Specific operation: The AI ​​engine integrates emotion data and analysis results to calculate product scores and create rankings. Input: Analysis result data, emotion data. Output: Scoring and ranking data.

[1510] Step 12:

[1511] The server generates a list of rated and ranked products and adds additional information such as "things to note when purchasing," "cheapest site," and "recommended features."

[1512] Specific operation: The server generates a product list based on the ranking data and adds supplementary information. Input: Scoring and ranking data. Output: Generated product list.

[1513] Step 13:

[1514] The server transmits the generated product list and additional information to the terminal.

[1515] Specific operation: The server sends data to the terminal as an HTTP response. Input: Generated product list. Output: Data sent to the terminal completed.

[1516] Step 14:

[1517] The terminal displays the product list and additional information on a user interface.

[1518] Specific operation: The terminal parses the display data and displays it on the interface. Input: Product list data. Output: Information is presented to the user.

[1519] Step 15:

[1520] The user checks the presented product list and selects and purchases the most suitable product.

[1521] Specific operation: The user scrolls through the displayed product list, selects the most suitable product, and presses the purchase button. Input: Product list. Output: Selection and purchase completed.

[1522] (Application example 2)

[1523] 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."

[1524] Conventional online shopping systems make it difficult for users to efficiently select the most suitable product from a vast selection of products. Furthermore, because they do not take into account the user's emotional state, the selected product may not meet the user's expectations, resulting in a dissatisfying shopping experience.

[1525] 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 inputting selection conditions for products desired by the user, means including a sensor for collecting user emotional data, communication means for collecting data related to the products based on the input selection conditions and emotional data, artificial intelligence means for analyzing the collected data and evaluating and ranking the products, means for presenting a list of evaluated and ranked products to the user, and means for attaching additional information to the presented product list, including "points to note when purchasing," "cheapest site," and "recommended features" for each product. This makes it possible to analyze the user's detailed selection conditions and emotional data and efficiently select and provide optimal products.

[1526] "User" refers to an individual who selects and purchases a particular product or service.

[1527] "Emotional data" is data that indicates the user's emotional state and is collected through sensors such as cameras and microphones.

[1528] A "sensor" refers to a device that senses an external physical or chemical phenomenon and outputs it as an electrical signal.

[1529] "Artificial intelligence means" refers to a system that includes algorithms and programs for collecting and analyzing data and proposing optimal products based on the results.

[1530] "Natural language processing means" refers to technology and software that understands, analyzes, and extracts meaning from human language.

[1531] "Communication means" refers to the technology and protocols used to transmit and receive data between multiple devices or systems.

[1532] A "product list" is a list of multiple products that have been rated and ranked, and includes detailed information about each product.

[1533] "Additional information" is information attached to the product list, and includes such things as "things to note when purchasing," "cheapest site," and "recommended features."

[1534] A "product category" refers to a classification item that groups together a group of products with similar characteristics.

[1535] "Conditions" means any specific requirements or constraints specified by a User when selecting a Product.

[1536] A "word-of-mouth site" is a website where consumers can post ratings and reviews of products they have used.

[1537] "E-commerce site" refers to an online platform through which goods and services are bought and sold on a web-based basis.

[1538] A "product review site" refers to a website where consumers can post product ratings and comments and other consumers can view that information.

[1539] The present invention relates to an online shopping system that enables users to efficiently select the most suitable product. This system is realized with the following configuration.

[1540] System Configuration

[1541] User's device

[1542] Hardware: Smartphones, tablets, PCs, smart glasses

[1543] Software: "Shopping Assistant" application or website

[1544] First, the user opens the "Shopping Assistant" application on their device and selects the category of product they are looking for (e.g., home appliances). Next, they enter detailed selection criteria such as price, features, and brand. To collect emotion data, the device's built-in camera and microphone are used to collect the user's facial and voice data. This data is then sent to the server.

[1545] server

[1546] The server performs the following process:

[1547] Data collection: The server collects data about the product based on the received selection criteria and emotion data. For example, it collects product ratings and reviews from word-of-mouth sites, e-commerce sites, and product review sites. This data is acquired using communication methods.

[1548] Data analysis: Using artificial intelligence and natural language processing, we analyze the collected text and sentiment data. We score products and generate rankings taking into account the sentiment data.

[1549] Generate a list of rated products: Generate a list of rated and ranked products, and add additional information to each product, such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[1550] Product list presentation

[1551] Presentation method: The product list and additional information sent from the server are displayed on the user's device. The user can select the most suitable product based on the presented information and decide to purchase it.

[1552] Specific examples

[1553] For example, suppose a user is looking for an air purifier. In this case, the user puts on the smart glasses and operates the "Shopping Assistant" app by voice, inputting detailed requirements for the air purifier (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.). The camera and microphone collect facial and voice data, which is then sent to a server. The server collects and analyzes product data based on the selection criteria and emotion data, and generates an optimal product list. This list is displayed on the smart glasses' display, allowing the user to select the most suitable product.

[1554] Prompt Sentence Examples

[1555] Let's say a user is looking for an air purifier, and they input the following criteria: price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity, and then we created an application that suggests the most suitable product based on sentiment analysis.

[1556] In this way, the online shopping system of the present invention can provide a high level of satisfaction by taking into consideration the user's feelings and selection conditions.

[1557] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1558] Step 1:

[1559] The user opens the "Shopping Assistant" application on the device. The user selects the desired product category (e.g., home appliances) and enters detailed selection criteria (price, features, brand, etc.). The entered selection criteria are retrieved by the device.

[1560] Step 2:

[1561] The device uses a camera and microphone to collect facial and voice data from the user, and generates input data for analyzing emotional data based on the collected sensor data.

[1562] Step 3:

[1563] The terminal transmits the input selection conditions and analyzed emotion data to the server, which receives this data and prepares to start collecting data about the product.

[1564] Step 4:

[1565] The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites based on the selection criteria and emotion data. The collected data is passed to the next analysis step.

[1566] Step 5:

[1567] The server uses natural language processing to analyze the collected text data of word-of-mouth and reviews, and the analyzed text data becomes input data for rating and ranking products.

[1568] Step 6:

[1569] The server uses artificial intelligence means to score products taking into account the selection criteria and emotion data, and the scored data serves as input data for generating a product list.

[1570] Step 7:

[1571] The server generates a list of rated and ranked products, and adds additional information to each product, such as "points to note when purchasing," "cheapest site," and "recommended features." The generated product list is generated as output data.

[1572] Step 8:

[1573] The server sends the generated product list and additional information to the terminal, which receives it and displays it on the user's interface.

[1574] Step 9:

[1575] The user reviews the presented product list and additional information, selects the most suitable product, and then proceeds to purchase the selected product.

[1576] In this way, by processing input data and generating output data at each step, users can efficiently select the most suitable product taking into account their emotional data.

[1577] 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.

[1578] 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.

[1579] 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.

[1580] [Fourth embodiment]

[1581] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1582] 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.

[1583] 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).

[1584] 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.

[1585] 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.

[1586] 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).

[1587] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1588] 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.

[1589] 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.

[1590] 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.

[1591] 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.

[1592] 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.

[1593] 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."

[1594] This invention is a system that allows users to select the most suitable product when shopping online. It uses AI to analyze the selection criteria of the product desired by the user and presents the most suitable product. This reduces the difficulty of product selection in conventional online shopping and the risk of mistaken purchases caused by false labeling and exaggerated advertising.

[1595] System Configuration

[1596] The system of the present invention is composed of a user terminal, a server, and a communication means. The role and operation of each component will be explained in detail below.

[1597] User's device

[1598] 1. User: Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.).

[1599] 2. Terminal: Displays the interface and allows the user to select a product category.

[1600] 3. User: Select a product category (e.g., air purifier).

[1601] 4. Terminal: Based on the selected category, a detailed selection criteria input form will be displayed.

[1602] 5. User: Enter detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.).

[1603] server

[1604] 6. Terminal: Sends the entered selection criteria data to the server.

[1605] 7. Server: Receives the selection conditions and starts the AI ​​engine.

[1606] 8. Server: The AI ​​engine collects relevant product data from multiple data sources (word-of-mouth sites, e-commerce sites, product review sites, etc.) based on the selection criteria.

[1607] 9. Server:

[1608] Natural language processing (NLP) technology is used to analyze collected word-of-mouth and review text data.

[1609] Products are scored based on the analysis results and a ranking is generated.

[1610] Product list presentation

[1611] 10. Server: Generates a scored and ranked product list and adds additional information for each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features."

[1612] 11. Server: Sends the generated product list and additional information to the terminal.

[1613] 12. Terminal: Displays the product list and additional information in a user interface.

[1614] 13. User: Check the presented products and select and purchase the most suitable product.

[1615] Specific examples

[1616] For air purifiers

[1617] Starting the system

[1618] 1. User: Open "EC Sensei" in a web browser.

[1619] 2. Device: Display the homepage.

[1620] Condition Input Phase

[1621] 3. User: Select the Air Purifier category.

[1622] 4. Device: Display the detailed conditions input form for the air purifier.

[1623] 5. User: Enter the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[1624] Product selection phase by AI

[1625] 6. Terminal: Sends condition data to the server.

[1626] 7. Server: Sends condition data to the AI ​​engine and begins collecting and analyzing product information.

[1627] 8. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites, and analyzes and scores it using NLP technology.

[1628] Optimal product presentation phase

[1629] 9. Server: Generates a list of optimal products and adds features such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[1630] 10. Server: Sends the product list to the terminal.

[1631] 11. Terminal: Displays product list and additional information.

[1632] 12. User: Selects the best product and decides to purchase.

[1633] This allows users to easily select the most suitable product based on reliable information. This specific embodiment supports the claims and clarifies the technical scope of the invention.

[1634] The processing flow will be explained below.

[1635] Step 1:

[1636] User: Open the "EC Sensei" application or website on your device.

[1637] Launch a web browser and enter the specified URL or tap the application icon.

[1638] Step 2:

[1639] Server: Receives the user's request, generates the HTML / CSS / JavaScript resources for the homepage, and sends them to the terminal.

[1640] Based on user requests, homepage data is dynamically generated and transmitted.

[1641] Step 3:

[1642] User: Select a product category (e.g., air purifier).

[1643] Click on the drop-down menu or icon to select the product category you want.

[1644] Step 4:

[1645] Server: Based on the selected category, a related detailed selection criteria input form is generated and sent to the terminal.

[1646] The input form corresponding to the product category is retrieved from the database, and the data required for displaying it is generated and sent.

[1647] Step 5:

[1648] User: Enter detailed selection criteria (e.g. price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[1649] Enter the condition in the input field and select an option.

[1650] Step 6:

[1651] Terminal: Organizes the entered selection criteria data and sends a request to the server in JSON format.

[1652] Converts form data into JSON format and sends a request to the specified API endpoint.

[1653] Step 7:

[1654] Server: Passes the received selection criteria data to the AI ​​engine and starts the data collection process.

[1655] Based on the conditions, it triggers an AI module to collect product-related information from multiple data sources.

[1656] Step 8:

[1657] Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[1658] Use APIs and scraping techniques to collect product information from designated data sources.

[1659] Step 9:

[1660] Server: Uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[1661] The NLP engine is activated to analyze the text data and extract important keywords and evaluation points.

[1662] Step 10:

[1663] Server: Based on the analysis results, the products are scored and a ranking is generated.

[1664] A scoring algorithm is applied to rank the products that best match the criteria.

[1665] Step 11:

[1666] Server: Generates a list of optimal products and adds additional information for each product, such as "things to note when purchasing," "cheapest site," and "recommended features."

[1667] Generate data in JSON format that includes relevant information in the product list.

[1668] Step 12:

[1669] Server: Sends the generated product list and additional information to the terminal.

[1670] The product list and related information are sent to the terminal and prepared for display.

[1671] Step 13:

[1672] Terminal: Analyzes the received product list and additional information and displays it on the user interface.

[1673] Convert the JSON data into HTML and display the information to the user.

[1674] Step 14:

[1675] User: Check the presented products, select the most suitable product and purchase it.

[1676] Based on the product information provided, select the desired product and proceed with the purchase.

[1677] This allows users to input detailed product selection criteria and efficiently select the most suitable products with the help of AI.

[1678] Example 1

[1679] 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."

[1680] Today's consumers often find it difficult to select the best product from the numerous product options available when shopping online. There is also the risk of making a mistaken purchase due to false and exaggerated advertising. Furthermore, checking a large number of customer testimonials and reviews one by one is extremely time-consuming and labor-intensive. These issues often make it difficult for consumers to choose the right product.

[1681] 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.

[1682] In this invention, the server includes a means for inputting selection criteria for products desired by the user, a communication means for collecting information about the products based on the input selection criteria, and an artificial intelligence means for analyzing the collected information and evaluating and ranking the products. This reduces the difficulty of product selection and the risk of making an erroneous purchase, and enables users to easily select the most suitable product based on reliable information.

[1683] "Means for users to input selection criteria for desired products" refers to means for providing an interface that allows users to input the characteristics and requirements of desired products using devices such as PCs or smartphones.

[1684] "Communication means for collecting information about products based on input selection criteria" refers to a network communication device and protocol for collecting information about products from various data sources on the Internet based on criteria specified by the user.

[1685] "Artificial intelligence means for analyzing collected information and evaluating and ranking products" refers to an AI system that includes machine learning algorithms and natural language processing technology to automatically analyze collected data and statistically analyze the characteristics and evaluations of each product to set a rank.

[1686] A "means for presenting a rated and ranked product list to a user" is a display device or interface that displays the AI-ranked product list in a user-friendly format, allowing the user to easily select the most suitable product.

[1687] "A means for adding additional information to the presented product list, including 'points to note when purchasing,' 'lowest price information,' and 'recommended features' for each product" refers to an information processing system that automatically generates and adds to the evaluated product list information such as points to note when purchasing each product, price comparison information with other sales sites, and features that are particularly superior in comparison with other products.

[1688] The "means for allowing a user to select a category" is a means for providing an interface for the user to select a category of a product to be searched for.

[1689] The "means for displaying related product selection conditions based on the selected category" is a means for providing an interface for inputting detailed selection conditions for the relevant product according to the category selected by the user.

[1690] "Means for collecting data from review sites, e-commerce sites, and product rating sites" refers to a data acquisition mechanism using crawling technology and APIs to efficiently collect detailed product data from multiple sources on the Internet.

[1691] "Natural language processing means for analyzing collected data" refers to an analysis system that includes natural language processing technology for analyzing collected text data (word of mouth, reviews, etc.) and extracting and structuring meaning from the data.

[1692] This invention is a system that allows users to select the most suitable product when shopping online. Specifically, the system inputs the selection criteria for the desired product, analyzes them using AI, and presents the most suitable product. This system is composed of a user terminal, a server, and communication means.

[1693] User's device

[1694] Device behavior

[1695] Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.). The user interface will be displayed, prompting the user to select a product category and displaying a form for entering detailed selection criteria. When the user enters detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.), the data will be sent to the server.

[1696] server

[1697] Server Operation

[1698] The server receives the selection criteria data sent from the device and activates the AI ​​engine. The AI ​​engine collects data from multiple data sources (e.g., word-of-mouth sites, e-commerce sites, product review sites) based on the selection criteria. The collected data is analyzed using natural language processing (NLP) technology to score and rank each product.

[1699] Product list presentation

[1700] Product proposals

[1701] The server generates a scored and ranked product list and adds additional information for each product, including "points to note when purchasing," "lowest price information," and "recommended features." This generated product list and additional information are sent to the terminal, which displays the product list and additional information on the user interface. The user can review the presented products and select the most suitable one.

[1702] Specific examples

[1703] For air purifiers

[1704] Starting the system

[1705] 1. The user opens "EC Sensei" in a web browser.

[1706] 2. The device displays the homepage.

[1707] Condition Input Phase

[1708] 3. The user selects the Air Purifier category.

[1709] 4. The device will display a form to input detailed conditions for the air purifier.

[1710] 5. The user enters the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[1711] Product selection phase by AI

[1712] 6. The device sends the condition data to the server.

[1713] 7. The server sends the condition data to the AI ​​engine and begins collecting and analyzing product information.

[1714] 8. The server collects data from word-of-mouth sites, e-commerce sites, and product review sites, and analyzes and scores it using NLP technology.

[1715] Optimal product presentation phase

[1716] 9. The server generates a list of optimal products and adds information such as "points to note when purchasing," "lowest price information," and "recommended features."

[1717] 10. The server sends the product list to the terminal.

[1718] 11. The device will display a list of products and additional information.

[1719] 12. The user selects the best product and decides to purchase.

[1720] Example prompts for generative AI models

[1721] Prompt statement:

[1722] Please describe the process by which a user would use the "EC Sensei" system to select the best air purifier based on the following selection criteria: price (up to ¥30,000), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (available), smartphone connectivity (available)

[1723] By inputting this prompt into a generative AI model, users can efficiently select the most suitable product.

[1724] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1725] Step 1:

[1726] The user opens the "EC Sensei" application or website on a device such as a PC or smartphone.

[1727] Input: Device launch and application or browser access.

[1728] Output: Application or browser homepage display.

[1729] Specific action: The user taps the application icon or enters the URL in the browser to open the site.

[1730] Step 2:

[1731] The terminal displays a home page and prompts the user to select a product category.

[1732] Input: The user's access request.

[1733] Output: Display of product category selection screen.

[1734] Specific operation: The device renders the "EC Sensei" homepage and offers product category selection.

[1735] Step 3:

[1736] The user selects a product category (e.g., air purifiers).

[1737] Input: A category selected by the user.

[1738] Output: Save selected category information.

[1739] Specific Action: User clicks on the Air Purifiers category.

[1740] Step 4:

[1741] The device will display a detailed selection criteria input form based on the selected category.

[1742] Input: Selected product category information.

[1743] Output: Display of detailed selection criteria input form.

[1744] Specific operation: The device renders and displays a detailed input form (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.) according to the selected category.

[1745] Step 5:

[1746] The user enters detailed selection criteria.

[1747] Input: Detailed selection criteria (e.g. price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), smartphone connectivity (yes)).

[1748] Output: Saves the entered selection criteria data.

[1749] Specific operation: The user enters values ​​or options for each condition item and presses the submit button.

[1750] Step 6:

[1751] The terminal transmits the input condition data to the server.

[1752] Input: Detailed selection criteria data.

[1753] Output: Sending data to the server.

[1754] Specific operation: The terminal generates an HTTP request and sends the condition data in JSON format to the server.

[1755] Step 7:

[1756] The server supplies the received selection condition data to the AI ​​engine.

[1757] Input: The received selection criteria data.

[1758] Output: Data feed to the AI ​​engine.

[1759] Specific operation: The server stores data in a database and provides that data as input to the AI ​​engine.

[1760] Step 8:

[1761] The server's AI engine collects data from multiple data sources (e.g., word-of-mouth sites, e-commerce sites, product review sites) based on selection criteria.

[1762] Input: Selection criteria data.

[1763] Output: Collected product data.

[1764] What it does: The AI ​​engine uses APIs and web scraping technology to collect relevant product data from designated sites.

[1765] Step 9:

[1766] The server uses natural language processing (NLP) techniques to analyze the collected data and score and rank the products.

[1767] Input: Collected text data (word of mouth, reviews, etc.).

[1768] Output: Analysis results and scored product list.

[1769] Specific operation: Text data is input into the NLP model, analyzed, and product characteristics and evaluation scores are calculated and ranked.

[1770] Step 10:

[1771] The server generates a list of rated and ranked products and adds additional information such as "things to note when purchasing," "lowest price information," and "recommended features."

[1772] Input: Scored product list.

[1773] Output: Final product list with additional information added.

[1774] Specific operation: The server generates information about each product, such as warnings, features, and price comparisons, and adds it to the scored list.

[1775] Step 11:

[1776] The server transmits the generated product list and additional information to the terminal.

[1777] Input: Final product list.

[1778] Output: Sending data to the terminal.

[1779] Specific operation: Generates an HTTP response to send the product list and additional information in JSON format to the terminal.

[1780] Step 12:

[1781] The terminal displays a list of products and additional information.

[1782] Input: Product list and additional information sent from the server.

[1783] Output: Display to the user interface.

[1784] What happens: The device renders the product list and additional information and displays it on the screen.

[1785] Step 13:

[1786] The user checks the products presented and selects and purchases the most suitable product.

[1787] Input: Displayed product list and additional information.

[1788] Output: Product selection and purchase confirmation.

[1789] Specific operation: The user checks the product list, clicks on the product they want to purchase, and completes the purchase process.

[1790] (Application example 1)

[1791] 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."

[1792] In conventional online shopping, users often face an overwhelming number of options when selecting the products they need, and are often misled by exaggerated advertising and false representations, making it difficult to select the optimal product. Furthermore, collecting and analyzing reliable information from multiple data sources requires a great deal of effort. There is an urgent need to provide a system that can solve these problems and enable users to quickly and reliably select the optimal product.

[1793] 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.

[1794] In this invention, the server includes: means for inputting selection criteria for a desired product by a user; communication means for collecting data on the products based on the input selection criteria; artificial intelligence means for analyzing the collected data and rating and ranking the products; means for presenting a list of rated and ranked products to the user; means for adding additional information to the presented product list, including "points to note when purchasing," "cheapest sites," and "recommended features," for each product; means for transmitting the product selection criteria input by the user via the user interface to the server; means for an artificial intelligence engine within the server to collect and analyze product information from a data source based on the user's input criteria; and means for displaying the analysis results on the user interface. This enables users to quickly and accurately select optimal products based on reliable data.

[1795] "Users" are individuals or groups who search for products through online shopping and consider purchasing them.

[1796] "Choice criteria" are the specific features or criteria that a user seeks when purchasing a product, such as price, functionality, or quality.

[1797] "Communication means" refers to the technology and infrastructure for sending and receiving data between the user's device and the server, including the Internet and wireless communications.

[1798] "Artificial intelligence tools" refer to algorithms and techniques used to analyze collected data and evaluate and rank products. Machine learning and deep learning techniques are primarily used.

[1799] "Rating and ranking" refers to scoring products based on user selection criteria and sorting them in an appropriate order. This process includes analyzing word-of-mouth and reviews.

[1800] "Presenting" is the act of showing a user a rated and ranked product list and its additional information.

[1801] "Purchase precautions" is information that indicates important points that users should consider when purchasing a product. For example, it includes product-specific drawbacks and usage precautions.

[1802] A "cheapest site" is a sales site where you can purchase a particular product at the lowest price.

[1803] "Recommended features" refer to the particularly outstanding functions or features of a particular product.

[1804] "User interface" refers to the screens and operating methods that allow users to directly interact with systems and applications.

[1805] "Data source" refers to an online source of information from which product information is collected, such as a word-of-mouth site, an e-commerce site, or a product review site.

[1806] "Natural language processing" is a technology that analyzes collected text data such as word-of-mouth and reviews and converts it into meaningful information. It mainly uses machine learning algorithms.

[1807] The system for carrying out this invention is composed of a user terminal, a server, and an infrastructure that connects these via communication means. Specifically, the system provides a user interface for users to select products, collects and analyzes data on the server side based on the selection criteria, and presents the most suitable products.

[1808] User's device

[1809] The terminal is an electronic device such as a smartphone, personal computer, or tablet, and provides an interface for users to input selection criteria for their desired products. The user uses this interface to input product categories and detailed selection criteria.

[1810] Specific example of input procedure

[1811] 1. User: Launch the EC Sensei application on their smartphone.

[1812] 2. Device: View product categories on the app homepage.

[1813] 3. User: Select the Air Purifier category.

[1814] 4. Device: Display the detailed conditions input form for the air purifier.

[1815] 5. User: Enter the desired price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity conditions.

[1816] Server Processing

[1817] The server activates an AI engine based on each user's input and collects product information from multiple data sources. It then uses natural language processing (NLP) technology to analyze text data from user reviews and scores products. Furthermore, the product list, which is scored based on the analysis results, includes additional information such as "things to note when purchasing," "the site with the lowest price," and "recommended features."

[1818] Software Configuration

[1819] AI Engine: Analyzes customer testimonials and reviews using deep learning frameworks like TensorFlow or PyTorch.

[1820] Framework: Uses Flask to manage communication between the server and the user interface.

[1821] Communication library: Uses the Python Requests library to send and receive data.

[1822] Specific examples of processing procedures

[1823] 1. Terminal: The selection criteria entered by the user are sent to the server.

[1824] 2. Server: Sends condition data to the AI ​​engine and begins collecting and analyzing product information.

[1825] 3. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites.

[1826] 4. Server: Analyzes data using natural language processing and scores products.

[1827] 5. Server: Generates a list of optimal products and adds features such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[1828] 6. Server: Sends the product list to the terminal.

[1829] 7. Terminal: Displays product list and additional information.

[1830] 8. User: Selects the best product and decides to purchase.

[1831] Prompt Sentence Examples

[1832] Conditions for purchase: The user opens the smartphone app "EC Sensei" and enters the details of the air purifier they require. The desired conditions are "price under 30,000 yen," "applicable area up to 20 tatami mats," "filter replacement frequency once a year," "humidification function," and "smartphone connectivity."

[1833] Input: Enter "air purifier," "under 30,000 yen," "20 tatami mats," "once a year," "humidifier function," and "smartphone connectivity" into the user interface.

[1834] Output: After AI analysis, a list of the "best air purifiers" is presented, along with reviews for each product, the lowest price store, and details of recommended features.

[1835] The above is a mode for carrying out the invention, and enables users to quickly and accurately select the most suitable product based on reliable data.

[1836] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1837] Step 1:

[1838] The user launches the EC Sensei application on their smartphone and selects a product category.

[1839] Input: A user launches the application and selects "Air Purifier" as the product category.

[1840] Output: A form for entering detailed conditions for the air purifier will be displayed on the terminal.

[1841] Step 2:

[1842] The user enters detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[1843] Input: The user enters conditions such as "price under 30,000 yen," "applicable area up to 20 tatami mats," "filter replacement frequency once a year," "humidification function included," and "smartphone connectivity available."

[1844] Output: The entered selection criteria are displayed on the terminal and are ready to be sent to the server.

[1845] Step 3:

[1846] The terminal transmits the input selection condition data to the server.

[1847] Input: Selection criteria data entered by the user.

[1848] Output: The condition data is sent to the server.

[1849] Step 4:

[1850] The server receives the condition data and starts the AI ​​engine.

[1851] Input: The submitted selection criteria data.

[1852] Output: The AI ​​engine is now up and running, ready to start collecting and analyzing product information from data sources.

[1853] Step 5:

[1854] The server collects product information from multiple data sources (word-of-mouth sites, e-commerce sites, product review sites).

[1855] Input: Product selection criteria specified by the AI ​​engine.

[1856] Output: Collected product information data. For example, text data of word-of-mouth and reviews.

[1857] Step 6:

[1858] The server analyzes the collected data using natural language processing (NLP) and scores the products.

[1859] Input: Collected text data of word-of-mouth and reviews.

[1860] The analysis involves extracting evaluation scores and important features from text data.

[1861] Output: Rating score and ranking for each product.

[1862] Step 7:

[1863] The server generates a list of rated and ranked products and attaches additional information including "things to note when purchasing," "cheapest sites," and "recommended features."

[1864] Input: Scoring results and additional information.

[1865] Output: A detailed product list.

[1866] Step 8:

[1867] The server transmits the generated product list and additional information to the terminal.

[1868] Input: A rated and ranked list of products and their additional information.

[1869] Output: The product list and additional information are sent to the terminal.

[1870] Step 9:

[1871] The terminal displays the product list and additional information on a user interface.

[1872] Input: Product list and additional information received from the server.

[1873] Output: A user interface with a list of products and their details.

[1874] Step 10:

[1875] The user checks the presented product list, selects the most suitable product, and decides to purchase it.

[1876] Input: Proposed product list and additional information.

[1877] Output: The product selected by the user and a purchase decision is made.

[1878] The above are the processing steps of the system program that realizes the application example.

[1879] 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.

[1880] The present invention relates to a system that allows users to efficiently select optimal products when shopping online. In particular, it aims to solve the problems of conventional systems by combining the user's selection criteria and emotional data to suggest optimal products. The present invention is realized using a user's terminal, a server, an artificial intelligence engine, and an emotional engine.

[1881] System Configuration and Operation

[1882] This system has the following configuration and operation.

[1883] User's device

[1884] 1. User: Open the "EC Sensei" application or website on your device (PC, smartphone, tablet, etc.).

[1885] 2. Terminal: Displays the interface and allows the user to select a product category.

[1886] 3. User: Select a product category (e.g., air purifier).

[1887] 4. Terminal: Based on the selected category, a detailed selection criteria input form will be displayed.

[1888] 5. User: Enter detailed selection criteria (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.).

[1889] Emotion Engine Operation

[1890] 1. Terminal: Collects the user's emotion data along with the input selection criteria and sends it to the server. Emotion data is extracted from sensor data such as camera, microphone, and touch input.

[1891] 2. Server: Analyzes the received emotional data and determines the user's emotional state.

[1892] Server and AI engine

[1893] 1. Server: Passes the selection criteria data and emotion data to the AI ​​engine and begins data collection and analysis.

[1894] 2. Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[1895] 3. Server: Using natural language processing (NLP) technology, the collected text data of user comments and reviews is analyzed, and product scores and rankings are generated taking into account sentiment data.

[1896] Product list presentation

[1897] 1. Server: Generates a scored and ranked product list and adds additional information for each product, including "Points to Note When Purchasing," "Lowest Price Site," and "Recommended Features." It also adjusts the priority and content of the information presented based on emotional data.

[1898] 2. Server: Sends the generated product list and additional information to the terminal.

[1899] 3. Terminal: displays the product list and additional information in a user interface.

[1900] 4. User: Check the presented products and select and purchase the most suitable product.

[1901] Specific examples

[1902] For air purifiers

[1903] Starting the system

[1904] 1. User: Open "EC Sensei" in a web browser.

[1905] 2. Device: Display the homepage.

[1906] Condition input and emotion recognition phase

[1907] 1. User: Select the Air Purifier category.

[1908] 2. Device: Display the detailed conditions input form for the air purifier.

[1909] 3. User: Enter the price (maximum 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (yes), and smartphone connectivity (yes).

[1910] 4. Device: Analyzes the user's facial expressions and voice using a camera and microphone to obtain emotional data. The obtained emotional data and selection criteria are sent to the server.

[1911] Product selection phase by AI

[1912] 1. Server: Sends condition data and emotion data to the AI ​​engine and begins collecting and analyzing product information.

[1913] 2. Server: Collects data from word-of-mouth sites, e-commerce sites, and product review sites, analyzes and scores it using NLP technology, and ranks products taking into account emotional data.

[1914] Optimal product presentation phase

[1915] 1. Server: Generates a list of optimal products and adds information such as "Points to note when purchasing," "Lowest price site," and "Recommended features." Adjusts the information presented based on emotional data.

[1916] 2. Server: Sends the product list and related information to the terminal.

[1917] 3. Terminal: Displays product list and additional information.

[1918] 4. User: Selects the best product and decides to purchase.

[1919] This makes it possible to significantly reduce the difficulty of selection and the risk of making a mistaken purchase in conventional online shopping by analyzing the user's detailed selection criteria and emotional data. This specific embodiment supports the claims and clarifies the technical scope of the invention.

[1920] The processing flow will be explained below.

[1921] Step 1:

[1922] User: Open the "EC Sensei" application or website on your device.

[1923] Launch a web browser and enter the specified URL or tap the application icon.

[1924] Step 2:

[1925] Server: Receives the user's request, generates the HTML / CSS / JavaScript resources for the homepage, and sends them to the terminal.

[1926] Based on user requests, homepage data is dynamically generated and transmitted.

[1927] Step 3:

[1928] User: Select a product category (e.g., air purifier).

[1929] Click on the drop-down menu or icon to select the product category you want.

[1930] Step 4:

[1931] Server: Based on the selected category, a related detailed selection criteria input form is generated and sent to the terminal.

[1932] The input form corresponding to the product category is retrieved from the database, and the data required for displaying it is generated and sent.

[1933] Step 5:

[1934] User: Enter detailed selection criteria (e.g. price, applicable area, filter replacement frequency, humidification function, smartphone connectivity).

[1935] Enter the condition in the input field and select an option.

[1936] Step 6:

[1937] Terminal: Organizes the input selection criteria data and emotion data and sends a request in JSON format to the server.

[1938] Form data and emotion data obtained from the camera, microphone, etc. are converted into JSON format and sent to the specified API endpoint.

[1939] Step 7:

[1940] Server: Passes the received selection criteria data and emotion data to the AI ​​engine and starts the data collection process.

[1941] Based on the conditions and sentiment data, it activates an AI module to collect product-related information from multiple data sources.

[1942] Step 8:

[1943] Server: Collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[1944] Use APIs and scraping techniques to collect product information from designated data sources.

[1945] Step 9:

[1946] Server: Uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[1947] The NLP engine is activated to analyze the text data and extract important keywords and evaluation points, taking into account sentiment data.

[1948] Step 10:

[1949] Server: Based on the analysis results, the products are scored and a ranking is generated.

[1950] A scoring algorithm is applied to rank the products that best match the criteria and the user's emotional state.

[1951] Step 11:

[1952] Server: Generates a list of optimal products and adds additional information for each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features." Adjusts the priority and content of information based on emotional data.

[1953] Generate data in JSON format that includes relevant information in the product list.

[1954] Step 12:

[1955] Server: Sends the generated product list and additional information to the terminal.

[1956] The product list and related information are sent to the terminal and prepared for display.

[1957] Step 13:

[1958] Terminal: Analyzes the received product list and additional information and displays it on the user interface.

[1959] Convert the JSON data into HTML and display the information to the user.

[1960] Step 14:

[1961] User: Check the presented products, select the most suitable product and purchase it.

[1962] Based on the product information provided, select the desired product and proceed with the purchase.

[1963] This allows users to input detailed product selection criteria and emotional data, and with the help of AI, efficiently select the most suitable product.

[1964] Example 2

[1965] 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."

[1966] In conventional online shopping systems, users must manually compare and judge a large amount of information when selecting products based on their desired product selection criteria, which leads to a lack of efficiency and a high risk of making the wrong purchase. Furthermore, products are suggested without taking into account the user's emotional state, which can lead to problems in which the system does not adequately reflect the user's purchasing intentions. Furthermore, the collected data is fragmented, making it difficult to make a comprehensive evaluation. There is a need for a system that can solve these issues and enable users to select the optimal product in a short amount of time.

[1967] 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.

[1968] In this invention, the server includes a communication means for collecting selection criteria and emotional data for products desired by the user, a means for analyzing the collected selection criteria and emotional data and determining the emotional state, and an artificial intelligence means for collecting and analyzing data related to the products based on the determined emotional state and selection criteria. This makes it possible to evaluate and rank products and present an optimal product list after taking into account the user's detailed selection criteria and emotional data. This significantly reduces the difficulty of selection and the risk of purchasing the wrong product in conventional systems, improving the user's purchasing experience.

[1969] "User" refers to a person who uses the system or service to select and purchase products.

[1970] "Selection criteria" refers to specific requirements such as price, functionality, size, etc. that a user considers when selecting a product.

[1971] "Emotional data" refers to data that indicates the emotional state of a user analyzed from facial expressions, voice, operating behavior, etc.

[1972] "Communication means" refers to the technical elements used to send and receive data between a user's terminal and a server.

[1973] "Emotional state" refers to the psychological state determined by analyzing the user's emotional data.

[1974] "Artificial Intelligence Means" refers to the artificial intelligence technologies used to analyze, evaluate, and rank the collected data.

[1975] "Product List" refers to a list of information about analyzed and ranked products.

[1976] "Additional information" refers to supplementary information related to a product, such as "Points to note when purchasing," "Lowest price site," and "Recommended features," that is added to the product list.

[1977] "Sensor device" refers to hardware such as a camera, microphone, or touch sensor used to collect a user's emotional data.

[1978] "Natural language processing means" refers to natural language processing technology for mechanically understanding and analyzing text data of word-of-mouth and reviews.

[1979] This invention is a system that allows users to efficiently select the most suitable product when shopping online. Specifically, it aims to solve the problems of conventional systems by combining the user's selection criteria and emotional data to suggest the most suitable product. This system is realized using a user's terminal, a server, an artificial intelligence engine, and an emotional engine.

[1980] User's device

[1981] The user opens the "EC Sensei" application or website on their device, such as a PC, smartphone, or tablet. The device displays the application or website interface and allows the user to select a product category. Once the user selects the desired product category (e.g., air purifier), a form for entering detailed selection criteria is displayed. Here, the user enters detailed selection criteria such as price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity.

[1982] Emotion Engine Operation

[1983] The device collects the user's emotional data, along with detailed selection conditions, using sensor devices such as a camera, microphone, and touch sensor. This emotional data is extracted from the user's facial expressions, voice, and the speed and strength of touch operations. The collected emotional data and selection condition data are sent from the device to the server.

[1984] Server and AI engine

[1985] The server receives the selection criteria data and emotion data sent by the user and supplies them to the AI ​​engine to begin the analysis process. The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites (e.g., Amazon, Rakuten, Yahoo! Shopping). It then uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews, scoring and ranking products while also taking into account the user's emotional state.

[1986] Product list presentation

[1987] The server generates a rated and ranked product list based on the analysis and scoring results. This product list includes additional information such as "things to note when purchasing," "cheapest sites," and "recommended features," and the presentation priority and content of this information are adjusted based on the emotional data. The generated product list and additional information are sent from the server to the terminal, which displays them on the user interface. The user can review the presented product list, select the most suitable product, and purchase it.

[1988] Specific examples

[1989] For air purifiers

[1990] The user opens "EC Sensei" in a web browser on their PC. The homepage is displayed, and the user selects the air purifier category. A form for entering detailed conditions for the air purifier is then displayed. The user enters the following conditions: price (up to 30,000 yen), applicable area (up to 20 tatami mats), filter replacement frequency (once a year), humidification function (available), and smartphone connectivity (available). The device uses a camera and microphone to analyze the user's facial expressions and voice, and obtains emotional data. This emotional data and the selection conditions are then sent to the server.

[1991] The server sends this data to an AI engine, which begins collecting and analyzing product information. Data is collected from word-of-mouth sites, e-commerce sites, and product review sites, and analyzed and scored using NLP technology. Products are ranked taking emotional data into consideration. As a result, an optimal product list is generated, and additional information such as "things to note when purchasing," "cheapest site," and "recommended features" is added. The server then sends the generated product list and related information to the device, which displays it. The user selects the optimal product and decides to purchase.

[1992] Example of input prompt for generative AI model

[1993] "Please find and recommend the best air purifier based on user feedback and reviews, with a maximum price of ¥30,000, an applicable area of ​​up to 20 tatami mats, filter replacement frequency of once a year, humidification function, and smartphone connectivity. Please also take into account user sentiment data."

[1994] By analyzing users' detailed selection criteria and emotional data, this system can significantly reduce the difficulty of selection and the risk of making the wrong purchase that are associated with traditional online shopping, thereby improving the user's purchasing experience.

[1995] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1996] Step 1:

[1997] The user opens the "EC Sensei" application or website on their device, such as a PC, smartphone, or tablet.

[1998] Specific operation: The user launches a web browser and enters the URL of "EC Sensei" to access it. Input: Target URL. Output: The homepage is displayed.

[1999] Step 2:

[2000] The terminal displays the interface of the application or website and prompts the user to select a product category.

[2001] Specific operation: The terminal renders and displays the homepage according to the user's access. Input: User access. Output: A product category selection screen is displayed.

[2002] Step 3:

[2003] The user selects a product category (e.g., air purifier).

[2004] Specific operation: The user taps or clicks on a category from the options on the screen. Input: The user's selection. Output: The selected category information.

[2005] Step 4:

[2006] The device will display a detailed selection criteria input form based on the selected category.

[2007] Specific operation: The terminal dynamically generates and displays a detailed condition input form for products corresponding to the selected category. Input: Selected category information. Output: Display of detailed condition input form.

[2008] Step 5:

[2009] The user enters detailed selection criteria (e.g., maximum price 30,000 yen, applicable area 20 tatami mats, filter replacement frequency once a year, humidification function, smartphone connectivity).

[2010] Specific operation: The user enters the selection criteria in the displayed form and presses the submit button. Input: User inputs the selection criteria. Output: Selection criteria data.

[2011] Step 6:

[2012] The device collects the user's emotional data using a camera, microphone, and touch sensor, along with detailed selection criteria.

[2013] Specific operation: The device captures facial expressions with a camera, records audio with a microphone, and obtains touch sensor operation data. Input: User selection criteria and emotion data. Output: Collected selection criteria data and emotion data.

[2014] Step 7:

[2015] The terminal transmits the collected selection condition data and emotion data to the server.

[2016] Specific operation: The device sends an HTTP request to the server, sending selection criteria data and emotion data via the API. Input: Selection criteria data and emotion data. Output: Data transmission to the server completed.

[2017] Step 8:

[2018] The server feeds the received data to the AI ​​engine, which starts the analysis process.

[2019] Specific operation: The server saves the data in the database and supplies it to the AI ​​engine. Input: Selection criteria data and emotion data. Output: Start of the analysis process.

[2020] Step 9:

[2021] The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites.

[2022] Specific operation: The server uses scraping technology or API to obtain product data from external sites. Input: Selection criteria. Output: Collected product data.

[2023] Step 10:

[2024] The server uses natural language processing (NLP) technology to analyze the collected text data of word-of-mouth and reviews.

[2025] Specific operation: The NLP engine extracts keywords and performs sentiment analysis on text data to extract influential reviews. Input: Collected product data. Output: Analysis result data.

[2026] Step 11:

[2027] The server scores and ranks products, taking into account emotional data.

[2028] Specific operation: The AI ​​engine integrates emotion data and analysis results to calculate product scores and create rankings. Input: Analysis result data, emotion data. Output: Scoring and ranking data.

[2029] Step 12:

[2030] The server generates a list of rated and ranked products and adds additional information such as "things to note when purchasing," "cheapest site," and "recommended features."

[2031] Specific operation: The server generates a product list based on the ranking data and adds supplementary information. Input: Scoring and ranking data. Output: Generated product list.

[2032] Step 13:

[2033] The server transmits the generated product list and additional information to the terminal.

[2034] Specific operation: The server sends data to the terminal as an HTTP response. Input: Generated product list. Output: Data sent to the terminal completed.

[2035] Step 14:

[2036] The terminal displays the product list and additional information on a user interface.

[2037] Specific operation: The terminal parses the display data and displays it on the interface. Input: Product list data. Output: Information is presented to the user.

[2038] Step 15:

[2039] The user checks the presented product list and selects and purchases the most suitable product.

[2040] Specific operation: The user scrolls through the displayed product list, selects the most suitable product, and presses the purchase button. Input: Product list. Output: Selection and purchase completed.

[2041] (Application example 2)

[2042] 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."

[2043] Conventional online shopping systems make it difficult for users to efficiently select the most suitable product from a vast selection of products. Furthermore, because they do not take into account the user's emotional state, the selected product may not meet the user's expectations, resulting in a dissatisfying shopping experience.

[2044] 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 inputting selection conditions for products desired by the user, means including a sensor for collecting user emotional data, communication means for collecting data related to the products based on the input selection conditions and emotional data, artificial intelligence means for analyzing the collected data and evaluating and ranking the products, means for presenting a list of evaluated and ranked products to the user, and means for attaching additional information to the presented product list, including "points to note when purchasing," "cheapest site," and "recommended features" for each product. This makes it possible to analyze the user's detailed selection conditions and emotional data and efficiently select and provide optimal products.

[2045] "User" refers to an individual who selects and purchases a particular product or service.

[2046] "Emotional data" is data that indicates the user's emotional state and is collected through sensors such as cameras and microphones.

[2047] A "sensor" refers to a device that senses an external physical or chemical phenomenon and outputs it as an electrical signal.

[2048] "Artificial intelligence means" refers to a system that includes algorithms and programs for collecting and analyzing data and proposing optimal products based on the results.

[2049] "Natural language processing means" refers to technology and software that understands, analyzes, and extracts meaning from human language.

[2050] "Communication means" refers to the technology and protocols used to transmit and receive data between multiple devices or systems.

[2051] A "product list" is a list of multiple products that have been rated and ranked, and includes detailed information about each product.

[2052] "Additional information" is information attached to the product list, and includes such things as "things to note when purchasing," "cheapest site," and "recommended features."

[2053] A "product category" refers to a classification item that groups together a group of products with similar characteristics.

[2054] "Conditions" means any specific requirements or constraints specified by a User when selecting a Product.

[2055] A "word-of-mouth site" is a website where consumers can post ratings and reviews of products they have used.

[2056] "E-commerce site" refers to an online platform through which goods and services are bought and sold on a web-based basis.

[2057] A "product review site" refers to a website where consumers can post product ratings and comments and other consumers can view that information.

[2058] The present invention relates to an online shopping system that enables users to efficiently select the most suitable product. This system is realized with the following configuration.

[2059] System Configuration

[2060] User's device

[2061] Hardware: Smartphones, tablets, PCs, smart glasses

[2062] Software: "Shopping Assistant" application or website

[2063] First, the user opens the "Shopping Assistant" application on their device and selects the category of product they are looking for (e.g., home appliances). Next, they enter detailed selection criteria such as price, features, and brand. To collect emotion data, the device's built-in camera and microphone are used to collect the user's facial and voice data. This data is then sent to the server.

[2064] server

[2065] The server performs the following process:

[2066] Data collection: The server collects data about the product based on the received selection criteria and emotion data. For example, it collects product ratings and reviews from word-of-mouth sites, e-commerce sites, and product review sites. This data is acquired using communication methods.

[2067] Data analysis: Using artificial intelligence and natural language processing, we analyze the collected text and sentiment data. We score products and generate rankings taking into account the sentiment data.

[2068] Generate a list of rated products: Generate a list of rated and ranked products, and add additional information to each product, such as "Points to note when purchasing," "Lowest price site," and "Recommended features."

[2069] Product list presentation

[2070] Presentation method: The product list and additional information sent from the server are displayed on the user's device. The user can select the most suitable product based on the presented information and decide to purchase it.

[2071] Specific examples

[2072] For example, suppose a user is looking for an air purifier. In this case, the user puts on the smart glasses and operates the "Shopping Assistant" app by voice, inputting detailed requirements for the air purifier (price, applicable area, filter replacement frequency, humidification function, smartphone connectivity, etc.). The camera and microphone collect facial and voice data, which is then sent to a server. The server collects and analyzes product data based on the selection criteria and emotion data, and generates an optimal product list. This list is displayed on the smart glasses' display, allowing the user to select the most suitable product.

[2073] Prompt Sentence Examples

[2074] Let's say a user is looking for an air purifier, and they input the following criteria: price, applicable area, filter replacement frequency, humidification function, and smartphone connectivity, and then we created an application that suggests the most suitable product based on sentiment analysis.

[2075] In this way, the online shopping system of the present invention can provide a high level of satisfaction by taking into consideration the user's feelings and selection conditions.

[2076] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2077] Step 1:

[2078] The user opens the "Shopping Assistant" application on the device. The user selects the desired product category (e.g., home appliances) and enters detailed selection criteria (price, features, brand, etc.). The entered selection criteria are retrieved by the device.

[2079] Step 2:

[2080] The device uses a camera and microphone to collect facial and voice data from the user, and generates input data for analyzing emotional data based on the collected sensor data.

[2081] Step 3:

[2082] The terminal transmits the input selection conditions and analyzed emotion data to the server, which receives this data and prepares to start collecting data about the product.

[2083] Step 4:

[2084] The server collects relevant product data from word-of-mouth sites, e-commerce sites, and product review sites based on the selection criteria and emotion data. The collected data is passed to the next analysis step.

[2085] Step 5:

[2086] The server uses natural language processing to analyze the collected text data of word-of-mouth and reviews, and the analyzed text data becomes input data for rating and ranking products.

[2087] Step 6:

[2088] The server uses artificial intelligence means to score products taking into account the selection criteria and emotion data, and the scored data serves as input data for generating a product list.

[2089] Step 7:

[2090] The server generates a list of rated and ranked products, and adds additional information to each product, such as "points to note when purchasing," "cheapest site," and "recommended features." The generated product list is generated as output data.

[2091] Step 8:

[2092] The server sends the generated product list and additional information to the terminal, which receives it and displays it on the user's interface.

[2093] Step 9:

[2094] The user reviews the presented product list and additional information, selects the most suitable product, and then proceeds to purchase the selected product.

[2095] In this way, by processing input data and generating output data at each step, users can efficiently select the most suitable product taking into account their emotional data.

[2096] 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.

[2097] 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.

[2098] 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.

[2099] 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.

[2100] 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.

[2101] 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.

[2102] 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).

[2103] 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.

[2104] 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."

[2105] 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.

[2106] 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).

[2107] 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.

[2108] 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.

[2109] 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.

[2110] 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.

[2111] 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.

[2112] 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.

[2113] 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.

[2114] 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.

[2115] 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.

[2116] 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. ...

Claims

1. A means for inputting selection conditions for a desired product by a user; communication means for collecting data about products based on the input selection criteria; artificial intelligence means for analyzing the collected data and rating and ranking the products; means for presenting the rated and ranked product list to a user; The presented product list will include additional information about each product, including "Points to note when purchasing," "Lowest price site," and "Recommended features." A system including:

2. 10. The system of claim 1, further comprising: means for selecting a product category; and means for displaying related product selection criteria based on the selected category.

3. The system of claim 1, further comprising: means for collecting data from word-of-mouth sites, e-commerce sites, and product review sites based on input product selection conditions; and natural language processing means for analyzing the collected data.

Images