system

Abstract

Provide a system. [Solution] A means for a user to input desired product information; A means for receiving product information and collecting information such as price, availability, and shipping costs from multiple online stores on the Internet; A means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products; A means for listing the selected lowest priced product information and providing it to users; A system including:

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] In conventional online shopping, users have to manually search multiple stores to find the lowest price for a product, which requires a lot of time and effort. It is also difficult to find the lowest overall price, taking shipping costs into account, which makes it difficult for users to make the best choice. Furthermore, constantly tracking price information, which fluctuates daily, is a significant burden for users. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides the following means. Specifically, the system includes a means for a user to input product information they want, a means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, a means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, and a means for creating a list of the selected cheapest products and providing it to the user. The system also includes a means for calculating the total price by adding up the product prices and shipping costs, allowing the user to make the most economical choice. Furthermore, the system further includes a means for periodically checking price fluctuations based on the product information registered by the user and notifying them when prices drop, allowing the user to efficiently obtain the latest lowest price information.

[0006] "User" refers to an individual or corporation that uses the system to find out the lowest price for a product.

[0007] "Product information" is information input by the user to identify a specific product, and includes the product name, model number, specifications, and the like.

[0008] "Terminal" refers to a device used by a user to input product information, and refers to electronic devices such as PCs, smartphones, and tablets.

[0009] "Server" refers to the central processing unit for receiving product information and collecting and analyzing information from the online store.

[0010] An "online store" is any website that sells products over the Internet, including, for example, major shopping sites and retailer websites.

[0011] "Price" means the selling price at which a particular Product is offered in the Online Store.

[0012] "Inventory status" is information that indicates whether a particular product is currently available in the online store.

[0013] "Shipping Costs" refers to any additional costs incurred in shipping a Product.

[0014] "Means for collecting information" refers to the process by which the server obtains product-related data from multiple online stores on the Internet.

[0015] "Means for analyzing information" refers to the process by which the server processes data collected, such as product prices, stock status, and shipping costs.

[0016] "Total" refers to the total price of the product and shipping fee.

[0017] "Cheapest product selection method" refers to the process of identifying the lowest priced product from the analyzed totals.

[0018] "Listing method" refers to the process of compiling the selected lowest priced product information in a table or other list format.

[0019] "Means for providing to the user" refers to the process of notifying the user of the listed lowest prices.

[0020] "Means for periodically checking price fluctuations" refers to the process by which the server monitors the price of the product at regular intervals and tracks fluctuations.

[0021] "Means for notifying when prices drop" refers to a process for notifying users when the price of a particular product drops during price fluctuation monitoring. [Brief explanation of the drawings]

[0022] [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

[0023] 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.

[0024] First, the terms used in the following description will be explained.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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."

[0030] [First embodiment]

[0031] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0032] 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.

[0033] 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).

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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."

[0043] The present invention is a system for efficiently finding the lowest price for a product when a user is shopping online, and functions through communication between a server and a terminal. Specific embodiments of this system will be described below.

[0044] Overall system configuration

[0045] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores that collect information. Users enter information about the products they want into their terminal, which then sends it to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists that information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies users when prices drop.

[0046] Program processing description

[0047] Enter and submit product information

[0048] The user enters information about the product they want into the terminal. For example, they enter detailed information about a "laptop computer" (brand, model, specs, etc.) into a form. The terminal then sends this information to the server.

[0049] Information gathering

[0050] Based on the received product information, the server accesses multiple online stores to collect information on the product's price, stock status, shipping costs, etc. For example, for a specified "laptop computer," the server obtains the price, stock status, and shipping costs from online store A, online store B, and online store C.

[0051] Analysis of information

[0052] The server analyzes all the collected information and calculates the total price of each product from each online store, including shipping costs. It then compares all the totals to find the cheapest option, allowing the user to purchase the product most economically.

[0053] Listing and Notification

[0054] The server creates a list of the lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check the list and purchase the product from the specified link.

[0055] Monitoring price fluctuations

[0056] The server periodically collects and monitors the prices of products from online stores based on the product information registered by the user in advance. If the price drops, the server notifies the device so that the user can obtain the latest lowest price information.

[0057] Specific examples

[0058] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the prices, and sends that information to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0059] Thus, the system of the present invention is designed to help users efficiently and effectively find and purchase products at the lowest prices.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] The user enters product information into the terminal, for example, "laptop XYZ model." This prepares the data for the next step.

[0063] Step 2:

[0064] The terminal sends the product information entered by the user to the server, including the product name, model number, specifications, etc.

[0065] Step 3:

[0066] The server sends requests to multiple online stores based on the received product information, and then crawls between the online stores to collect the necessary data.

[0067] Step 4:

[0068] The server analyzes the data collected from each online store. This data includes price, stock status, shipping costs, etc. For example, online store A may retrieve data such as "price: 80,000 yen, shipping cost: 500 yen," and online store B may retrieve data such as "price: 78,000 yen, shipping cost: free."

[0069] Step 5:

[0070] The server calculates the total amount based on the collected data. For example, the total amount for online store A is calculated as 80,500 yen, and the total amount for online store B is calculated as 78,000 yen.

[0071] Step 6:

[0072] The server compares the calculated totals and selects the product with the lowest total price. In this case, online store B's total price of 78,000 yen is the cheapest.

[0073] Step 7:

[0074] The server creates a list of the cheapest products. This list includes the product name, lowest price, store name, and purchase link. For example, it might be listed in the format "laptop XYZ model, price 78,000 yen, store B, link [purchase page]."

[0075] Step 8:

[0076] The server sends the generated list to the terminal, allowing the user to obtain the latest lowest price information.

[0077] Step 9:

[0078] The device displays the list to the user, who can then review the list and click a link to the purchase page.

[0079] Step 10:

[0080] The user clicks on the link and is taken to the designated online store's purchase page, where they can purchase the product at the most economical price.

[0081] The above are the specific processing steps that a user takes from obtaining information about the cheapest product to making a purchase.

[0082] Example 1

[0083] 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."

[0084] In online shopping, users often have to compare products across multiple sales sites to find the best price. Furthermore, product prices often fluctuate, making it difficult to obtain the lowest price information in a timely manner.

[0085] 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.

[0086] In this invention, the server includes means for users to input product information they want, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple sales sites on the Internet, means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, means for listing the selected cheapest product information and providing it to the user, and means for monitoring daily price fluctuations and notifying the user when prices drop, thereby enabling users to efficiently and reliably find and purchase the cheapest products.

[0087] "User" means any individual or legal entity that uses the System to conduct online shopping.

[0088] "Product information" refers to data including detailed information such as the brand, model, and specifications of the product that the user wishes to purchase.

[0089] "Sales Site" refers to any online platform that sells products over the Internet.

[0090] "Price" refers to the purchase price of the Product displayed on the Sales Site.

[0091] "Stock status" refers to information indicating whether or not a product is in stock at a sales site and the quantity.

[0092] "Shipping Costs" refers to any additional costs incurred in shipping the Product.

[0093] "Total amount" refers to the total amount of the product price and shipping fee.

[0094] "Lowest price" refers to the lowest total price of a product across multiple sales sites.

[0095] "Listing" refers to organizing collected and analyzed information and displaying it in a list format.

[0096] "Price fluctuation monitoring" refers to the process of regularly collecting and monitoring product price information and notifying you if there are any fluctuations.

[0097] This invention is a system that allows users to efficiently find the lowest prices for products when shopping online, and it functions through communication between a server and a terminal. It consists of a terminal used by the user, a server that performs the central processing, and multiple sales sites that collect information.

[0098] The user enters the product information they want into the terminal. This product information might include, for example, "laptop, brand ABC, model XYZ, 16GB RAM, 512GB SSD." The terminal converts this information into a data format such as JSON and sends it to the server as an HTTP POST request. When the user enters information into the form and presses the submit button, the input data is sent to the server.

[0099] Based on the received product information, the server sends requests to multiple sales site APIs to obtain information such as the price, stock status, and shipping costs of the target product. For example, the server sends HTTP GET requests to the API endpoints of online stores A, B, and C to collect real-time price information. The obtained information is stored in a database and used for further analysis.

[0100] The server analyzes the price, inventory status, and shipping information collected from each sales site and calculates the total price (product price + shipping). To ensure the most economical product purchase, the server compares all the total prices and identifies the product with the lowest price. For example, if online store A has a total price of 80,000 yen, online store B has a total price of 78,000 yen, and online store C has a total price of 79,000 yen, the server determines that online store B has the lowest price.

[0101] The server creates a list of the cheapest products (price, store name, link, etc.) and sends the list to the user's device. The user can then check the list on their device and purchase the product from the specified link. This process allows users to efficiently find and purchase the cheapest products.

[0102] Furthermore, the server periodically collects and monitors the prices of products registered by the user from various sales sites, based on the product information. If there is a price change, the information is sent to the terminal. For example, when the price of a registered "laptop computer" drops, the information is sent to the user, allowing the user to obtain the latest lowest price information.

[0103] As a concrete example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to a server, which then collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple sales sites. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of that information, and sends it to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0104] Example prompt sentence:

[0105] "Compare online stores to find the cheapest deal on the latest smartphone model XYZ. Collect pricing, availability, and shipping information from each store and tell me the cheapest option."

[0106] In this way, the system of the present invention helps users efficiently and reliably find and purchase products at the lowest prices.

[0107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0108] Step 1: Enter product information

[0109] The user enters details of the product they want into the terminal, such as "laptop, brand ABC, model XYZ, 16GB RAM, 512GB SSD." The terminal receives the user's input, formats the information as JSON data, and sends it to the server as an HTTP POST request.

[0110] Input: Product information entered by the user (brand, model, specifications, etc.)

[0111] Data processing: Convert product information into JSON format

[0112] Output: HTTP POST request with product information in JSON format

[0113] Specific behavior:

[0114] The user enters "Brand ABC, Model XYZ, 16GB RAM, 512GB SSD" into the form and presses the submit button. The device receives this information and sends the following JSON data to the server:

[0115] json

[0116] {

[0117] "category": "laptop",

[0118] "brand": "Brand ABC",

[0119] "model": "XYZ",

[0120] "specs": {

[0121] "RAM": "16GB",

[0122] "storage": "512GB SSD"

[0123] }

[0124] }

[0125] Step 2: Gather information

[0126] Based on the received product information, the server sends requests to multiple sales site APIs to obtain information such as the price, stock status, shipping costs, etc. It sends HTTP GET requests to each sales site to collect real-time data.

[0127] Input: Product information in JSON format

[0128] Data processing: Generating and sending HTTP GET requests to each sales site

[0129] Output: Price, stock status, and shipping information for each sales site (JSON format)

[0130] Specific behavior:

[0131] Your server sends an API request to your online store like this:

[0132] Online Store A's API: GET https: / / api.storeA.com / products?brand=BrandABC&model=XYZ

[0133] Online Store B's API: GET https: / / api.storeB.com / products?brand=BrandABC&model=XYZ

[0134] Online Store C API: GET https: / / api.storeC.com / products?brand=BrandABC&model=XYZ

[0135] Step 3: Analyze the information

[0136] The server analyzes the price, stock status, and shipping information collected from each sales site, calculates the total price of the product, and identifies the cheapest product based on the total price (product price + shipping).

[0137] Input: Price, stock status, shipping information for each sales site

[0138] Data processing: Calculate the total price by adding up the price and shipping fee, and identify the lowest price

[0139] Output: Cheapest seller information (price, total price, store name, link, etc.)

[0140] Specific behavior:

[0141] Calculate the total amount based on the data retrieved by the server:

[0142] Online Store A: Price: 70,000 yen, shipping: 10,000 yen → Total: 80,000 yen

[0143] Online Store B: Price: 75,000 yen, shipping: 3,000 yen → Total: 78,000 yen

[0144] Online Store C: Price 72,000 yen, shipping 7,000 yen → Total 79,000 yen

[0145] The server identifies online store B, which has the lowest price (total price: 78,000 yen).

[0146] Step 4: List and notify

[0147] The server creates a list of the lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check the list on their device and access the product purchase link.

[0148] Input: Cheapest price sales site information

[0149] Data processing: Formatting information into a list and generating notification data

[0150] Output: List sent to user's device (lowest price information)

[0151] Specific behavior:

[0152] The server lists the best prices as follows:

[0153] json

[0154] {

[0155] "store": "Online Store B",

[0156] "price": 78,000,

[0157] "link": "https: / / storeB.com / product / xyz"

[0158] }

[0159] The server sends this list to the user's device, and the user can access the purchase link.

[0160] Step 5: Monitor price fluctuations

[0161] The server periodically collects and monitors prices from each sales site based on product information registered in advance by the user, and notifies the user if the price drops.

[0162] Input: Registered product information, price information of each sales site

[0163] Data processing: Regular collection and monitoring of price information, and generation of notification data in the event of fluctuations

[0164] Output: Notification data when price changes

[0165] Specific behavior:

[0166] The server accesses each sales site's API at a specified time each day to collect price information. For example, if the price drops from 70,000 yen to 65,000 yen, that information is sent to the user's device.

[0167] (Application example 1)

[0168] 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."

[0169] In conventional online shopping systems, users often spend a great deal of time and effort finding the lowest priced products, and the lack of a seamless purchasing process can be frustrating. Furthermore, many systems lack the functionality to monitor price fluctuations and provide timely notifications, making it easy to miss opportunities to purchase at the lowest price. Therefore, there is a need for a system that can efficiently and seamlessly find the lowest priced products, quickly complete the payment process, and provide timely notifications of price fluctuations.

[0170] 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.

[0171] In this invention, the server includes means for inputting product information that a user wants, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, means for analyzing the collected information, calculating the total cost of the products, and selecting the cheapest product, means for listing the selected cheapest product information and providing it to the user, means for processing payments, and means for seamlessly executing the reception, collection, analysis, and payment of information as a series of processes. This enables users to efficiently and seamlessly find the cheapest products and pay quickly, and also allows them to avoid missing the optimal timing for purchase by receiving timely notifications of price fluctuations.

[0172] "Means for users to input product information they want" refers to an interface that allows users to input detailed information about the product they wish to acquire.

[0173] "Means for receiving product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet" refers to a communication means for collecting related data from multiple online stores on the Internet based on product information entered by a user.

[0174] "Means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product" refers to an algorithm that analyzes the collected data, calculates the total price by adding the product price and shipping costs, and selects the cheapest option.

[0175] "Means for listing the selected lowest priced product information and providing it to the user" refers to a component that organizes the information on the lowest priced products based on the analysis results, displays it as a list, and provides it to the user.

[0176] "Means for processing payments and for seamlessly receiving, collecting, analyzing information, and processing payments as a series of processes" refers to the overall system functions for carrying out payment procedures to purchase selected products, and for consistently and seamlessly collecting, analyzing information, and processing payments.

[0177] "Means to sum product prices and shipping costs" refers to a component that has the logic to calculate the total by adding up the product prices and shipping costs collected from the online store.

[0178] "A means of periodically checking price fluctuations based on product information registered by the user and notifying the user when the price drops" refers to a function that periodically checks the prices of products registered by the user in advance and notifies the user in real time when the price drops.

[0179] This invention is an electronic payment system that enables a user to purchase a desired product at the lowest price, and is realized by the following configuration.

[0180] Overall system configuration

[0181] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores that collect information. Users enter information about the products they want into their terminal and send it from the terminal to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from online stores. It identifies the products with the lowest prices, lists this information, and sends it to the terminal. It also provides a function to monitor daily price fluctuations and notify users when prices drop. Finally, it supports users so that they can smoothly complete payment at the store with the lowest price.

[0182] Program processing description

[0183] Enter and submit product information

[0184] The user inputs information about the product they want through the terminal interface. For example, they enter detailed information about a "laptop computer" (such as brand, model, and specifications) into a form, and the information is sent to the server.

[0185] Information gathering

[0186] Based on the received product information, the server accesses multiple online stores to collect information such as the price, stock status, shipping costs, etc. This process uses Python's requests library to obtain data from the Internet via API.

[0187] Analysis of information

[0188] The server analyzes all the collected information and calculates the total price of each online store, adding up the product price and shipping costs. It then compares the products and finds the cheapest option, using a data analysis library (e.g., Pandas or NumPy).

[0189] Listing and Notification

[0190] The server creates a list of the selected lowest priced products (price, store name, link, etc.) and provides the list to the user's device. The user can check the list and purchase the product from the specified link. This includes a notification system with a user interface (UI), such as email or in-app notifications.

[0191] Payment Processing

[0192] When the user decides to purchase from the store with the lowest price, the server executes the procedure for payment processing. For this, the payment API is used to securely send the user's credit card information, etc. A payment completion notification is sent to the user, and the system updates the purchase history.

[0193] Monitoring price fluctuations

[0194] The server periodically collects and monitors the price of a product from the online store based on the product information registered by the user in advance. If the price drops, the server notifies the device. For example, if the price of the "Laptop XYZ Model" registered by the user drops, the device will receive a notification such as "The price of Laptop XYZ Model has dropped: The current lowest price is 70,000 yen."

[0195] Examples of concrete examples and prompts

[0196] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the prices, and sends that information to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0197] As a result, this system allows users to efficiently and seamlessly find the lowest priced products and quickly complete payment.

[0198] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0199] Step 1:

[0200] The user uses a device to input information about the product they want, specifically details such as "laptop XYZ model" (brand, model, specs, etc.) into the device's interface, and the information is sent to the server. The input product information is converted into an API request format and sent to the server.

[0201] Step 2:

[0202] Based on the received product information, the server accesses multiple online stores on the Internet and collects information such as product price, stock status, and shipping costs. The server uses the Python requests library to request product information from the API of each online store and receives data in JSON format. The input is product information, and the output is the product data obtained from each online store.

[0203] Step 3:

[0204] The server analyzes all the collected information and calculates the total product price (price + shipping cost). Specifically, it uses data analysis libraries such as Pandas and NumPy to add up the product price and shipping cost for each online store and calculate the total price. The input is the product data collected from each online store, and the output is the analyzed data including the total price.

[0205] Step 4:

[0206] The server identifies the cheapest products based on the analysis results and lists the information. The lowest price is calculated using logic that compares all total prices and identifies the cheapest one. The input is the analysis data including the total price, and the output is a list of the cheapest products.

[0207] Step 5:

[0208] The server provides the selected cheapest product information to the user's device. Specifically, it sends a notification to the user's device, displaying details of the cheapest product, the store name, a purchase link, etc. The input is a list of cheapest product information, and the output is a notification and link displayed on the user's device.

[0209] Step 6:

[0210] The user uses the device to purchase the cheapest product from the provided link. Once the user proceeds with the purchase, the server executes the payment process. The payment process involves calling the payment API of each online store, sending payment information, and receiving the payment result. The input is the user's payment information, and the output is a payment completion notification.

[0211] Step 7:

[0212] The server periodically monitors price fluctuations based on the product information registered by the user. For example, it uses a Python scheduling library to call the API of each online store every hour to obtain the latest price information. The input is the registered product information, and the output is the latest price information.

[0213] Step 8:

[0214] The server notifies the user when the price drops. When a price change is detected, it sends a notification to the user's device, providing the latest lowest price information. For example, it sends a notification such as "The price of laptop model XYZ has dropped: the current lowest price is 70,000 yen." The input is the latest price information, and the output is the notification to the user.

[0215] 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.

[0216] The present invention is a system for efficiently finding the lowest prices for products when a user is shopping online, and functions through communication between a server and a terminal. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions. This system is designed to provide users with an appropriate and personalized purchasing experience. Specific embodiments of this system are described below.

[0217] Overall system configuration

[0218] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores for collecting information. In addition, it incorporates an emotion engine that recognizes the user's emotions. The user enters information about the product they want into the terminal, which then sends it to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists this information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies the user when prices drop. The emotion engine recognizes the user's emotions during this process and makes appropriate product suggestions and notifications.

[0219] Program processing description

[0220] Enter and submit product information

[0221] The user enters information about the product they want into the terminal. For example, they enter detailed information about "laptop model XYZ" (brand, model, specs, etc.) into a form. The terminal then sends this information to the server.

[0222] Information gathering

[0223] The server sends requests to multiple online stores based on the received product information. Based on the product information, the server crawls between online stores to collect the necessary data. For example, for a specified "laptop," it retrieves the price, stock information, and shipping costs from online store A, online store B, and online store C.

[0224] Analysis of information

[0225] The server analyzes all the collected information and calculates the total price of each product from each online store, including shipping costs. It then compares all the totals to find the cheapest option, allowing the user to purchase the product most economically.

[0226] Emotion Engine Operation

[0227] The emotion engine recognizes emotions from user input and selections. For example, it analyzes the user's input speed, items selected, purchase history, etc. to determine the user's current emotion. Based on this emotional information, it makes optimal product suggestions and notifies the user at the appropriate time. For example, if it determines that the user is in a hurry, it will prioritize displaying a list of products that can be delivered immediately.

[0228] Listing and Notification

[0229] The server creates a list of the selected lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check this list and purchase the product from the specified link. The emotion engine also improves the user experience by notifying users of the lowest priced products at the appropriate time.

[0230] Monitoring price fluctuations

[0231] The server periodically collects and monitors the price of a product from online stores based on the product information registered by the user in advance. If the price drops, the server notifies the user of the latest lowest price information. The emotion engine also participates in this notification, providing personalized notifications that take into account the user's current emotional state.

[0232] Specific examples

[0233] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0234] In this way, the system of the present invention is designed to help users efficiently and effectively find and purchase products at the lowest prices, and by combining it with an emotion engine, it provides users with a personalized purchasing experience.

[0235] The processing flow will be explained below.

[0236] Step 1:

[0237] The user enters product information into the terminal. For example, they enter a specific product name, model number, specifications, etc., such as "laptop XYZ model," into the form. This allows the system to retrieve the product information they are searching for.

[0238] Step 2:

[0239] The terminal sends the entered product information to the server, which then prepares to start processing based on the received information.

[0240] Step 3:

[0241] A server sends a search request to multiple online stores, including keywords such as product name, model number, etc. For example, a request for "laptop model XYZ" is sent to online store A, online store B, and online store C.

[0242] Step 4:

[0243] The server receives data returned from the online stores, including the price, stock status, shipping costs, etc. For example, online store A may return "price 80,000 yen, shipping cost 500 yen," while online store B may return "price 78,000 yen, shipping cost free."

[0244] Step 5:

[0245] The server analyzes the collected data and calculates the total price for each item. For example, the total price for online store A is calculated as 80,500 yen, and the total price for online store B is calculated as 78,000 yen.

[0246] Step 6:

[0247] The server compares the total prices and selects the product with the lowest total price. In this case, it determines that the product with the lowest total price of 78,000 yen from Online Store B is the cheapest.

[0248] Step 7:

[0249] The server creates a list of the lowest priced products (price, store name, purchase link, etc.). For example, it creates a list like "Laptop XYZ model, price 78,000 yen, store B, link [purchase page]."

[0250] Step 8:

[0251] The server sends the generated list to the terminal, allowing the user to obtain the latest lowest price information.

[0252] Step 9:

[0253] The device displays the list to the user, who can then review the list and click a link to the purchase page.

[0254] Step 10:

[0255] The user clicks on the link and is taken to the designated online store's purchase page, where they can purchase the product at the most economical price.

[0256] Step 11:

[0257] The emotion engine recognizes emotions from user input and selections. For example, if the user is typing in a hurry, the emotion engine will detect "impatience" and respond appropriately.

[0258] Step 12:

[0259] The emotion engine makes optimal product suggestions based on the user's emotions. For example, if it determines that the user is in a hurry, it will suggest products that can be delivered immediately.

[0260] Step 13:

[0261] The emotion engine will notify you at the right time, for example, when the price drops or when you are feeling relaxed, taking into account the user's emotional state.

[0262] Step 14:

[0263] The server periodically checks price fluctuations, and when the price drops, it works with the emotion engine to send a notification to the user. The emotion engine takes into account the user's current emotions and adjusts the appropriate notification content and timing.

[0264] In this way, the system of the present invention provides users with an optimal purchasing experience by seamlessly collecting product information, making optimal suggestions, and providing personalized notifications based on emotions.

[0265] Example 2

[0266] 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."

[0267] When consumers shop online, it is extremely time-consuming to check numerous e-commerce sites individually to find the lowest priced product. Furthermore, as user needs become more diverse, it is important not only to simply offer the lowest priced product, but also to suggest products that reflect the user's emotions and circumstances. Furthermore, monitoring price fluctuations even after purchase and notifying users when prices drop is necessary to improve user satisfaction.

[0268] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting product information desired by the user, a means for receiving the product information and collecting information such as price, stock status, and shipping fee from multiple e-commerce sites on a communication network, a means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product, a means for listing the selected cheapest product information and providing it to the user, and a means for recognizing the user's emotional state and suggesting products or notifying them based on the user's emotion. This enables the user to efficiently and quickly find the cheapest products, providing a personalized shopping experience.

[0269] A "user" is a person who uses the system to shop online.

[0270] "Product information" refers to detailed data such as the brand, model, and specifications of the product that the user wishes to purchase.

[0271] "Communications Network" means the infrastructure for carrying the Internet and other data communications.

[0272] "E-commerce site" refers to a website or online marketplace that sells products over the Internet.

[0273] "Price" refers to the selling price of the Product.

[0274] "Inventory status" refers to whether a particular item is available for sale and in what quantity.

[0275] "Shipping Fee" refers to the shipping fee incurred when delivering a product to a purchaser.

[0276] "Means of collection" refers to the process or technology by which the server obtains the necessary information from multiple e-commerce sites.

[0277] "Analytical methods" refers to the algorithms or methods used to examine the collected data and identify the lowest prices.

[0278] "Total" refers to the total price of the product and shipping fee.

[0279] "Means of selection" refers to the process of choosing the cheapest option from multiple options.

[0280] "Listing methods" refers to methods for organizing selected information and presenting it in a format that is easy for users to understand.

[0281] "Means of providing" refers to the process of presenting the listed information to the user.

[0282] "Emotional state" refers to a user's current mental or emotional state.

[0283] "Means for making suggestions and notifications based on emotions" refers to algorithms and technologies that analyze users' emotions and make product suggestions and notifications accordingly.

[0284] This invention is a system that allows users to efficiently find the lowest priced products when shopping online. This system is primarily composed of a terminal used by the user, a server that collects and analyzes information, and multiple e-commerce sites that provide data. It also incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions.

[0285] Overall system configuration

[0286] The user inputs the desired product information into the terminal, for example, "laptop XYZ model," including detailed information such as brand, model, and specifications. The terminal then sends this input information to the server.

[0287] Based on the received product information, the server uses programming languages ​​such as Python or Java (registered trademark) to collect the necessary data from multiple e-commerce sites. Specifically, it uses scraping tools (e.g., BeautifulSoup or Selenium) and APIs to obtain the price, inventory information, and shipping costs of the specified product. For example, it collects price information from online store A, online store B, and online store C.

[0288] The server analyzes all the collected information and calculates the total price by adding the product price and shipping costs from each e-commerce site. The collected data is stored in a data frame using Python's pandas, and an algorithm is run to find the lowest price by adding a column for the total price.

[0289] The emotion engine recognizes emotions from user input and selection history. For example, it analyzes the user's input speed, click patterns, and past purchase history, and uses NLP (natural language processing) libraries and machine learning models (e.g., scikit-learn and TENSORFLOW (registered trademark)) to determine the user's current emotion. If the user is in a hurry, it will prioritize a list of products that can be delivered immediately.

[0290] The server selects the lowest priced products and lists them using an HTML template engine (e.g., Jinja2). This list is sent to the user's device, where the user can view the information and purchase the products from the specified link.

[0291] The server periodically collects price fluctuations for products registered by the user from online stores and notifies the device when the price drops. This process is scheduled periodically using a Cron job or shell script. The emotion engine also participates in notifications, providing personalized notifications that take into account the user's current emotional state.

[0292] Specific examples

[0293] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to a server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple e-commerce sites. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0294] Prompt Sentence Examples

[0295] Here are some example prompts to input to a generative AI model:

[0296] 1. "I would like to develop an online shopping system. The user inputs information about the product they want, and based on that information, the system retrieves information about the lowest prices from multiple online stores. I would also like to incorporate an emotion recognition function so that the system can suggest appropriate products based on the user's emotions. Please explain the implementation of this system and the specific processing method."

[0297] 2. "I'm designing a system to find the lowest price when a user purchases a smartphone. I'd also like to use an emotion engine to suggest products based on the user's emotions. Please explain the overall flow of this system and the specific processing steps."

[0298] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0299] Step 1:

[0300] A user enters information about the product they want into a device. Specifically, they enter details about the brand, model, specs, etc. of "laptop XYZ model" into a web form on the device. The entered data is converted into JSON format and prepared for further processing. The input data is detailed information about the product, and the output is structured data in JSON format.

[0301] Step 2:

[0302] The terminal sends the product information entered by the user to the server. Specifically, it uses an HTTP POST request to send the product information data to the server's endpoint. At this time, the data is sent along with the appropriate HTTP headers. The input is the product information in JSON format, and the output is a success message sent to the server.

[0303] Step 3:

[0304] The server sends requests to multiple e-commerce sites based on the received product information. Specifically, it uses a Python scraping tool (e.g., BeautifulSoup or Selenium) to collect product data (price, stock, shipping costs) from each site. The input is detailed product information in JSON format, and the output is the raw data obtained from each site.

[0305] Step 4:

[0306] The server analyzes all the collected information and calculates the total price of the items. Specifically, it uses the Python pandas library to store the information in a data frame and runs an algorithm to calculate the total price by adding up the price and shipping. The input is a data frame of raw data, and the output is a data frame with the calculated total price.

[0307] Step 5:

[0308] The server selects the cheapest product from the data analysis results. Using the Python standard library, it runs an algorithm to select the row with the lowest value in the total price column. The input is a data frame with the calculated total price, and the output is the information about the cheapest product.

[0309] Step 6:

[0310] The server lists the selected cheapest products. Specifically, it uses an HTML template engine (e.g., Jinja2) to generate a visually organized list format HTML. The input is the cheapest product information, and the output is the HTML list data.

[0311] Step 7:

[0312] The server sends the generated list to the terminal. Specifically, it returns HTML data to the terminal as an HTTP response or sends it in real time using WebSocket. The input is the list HTML data, and the output is a notification message to the user terminal.

[0313] Step 8:

[0314] The emotion engine recognizes the user's emotions and provides optimal product suggestions and notifications. Specifically, it uses NLP libraries and machine learning models (e.g., scikit-learn and TensorFlow) to analyze the user's input speed and past selection data and cluster emotions. The input is user behavior data, and the output is emotion labels and notifications based on them.

[0315] Step 9:

[0316] The server periodically monitors price fluctuations based on product information registered in advance by the user. Specifically, it periodically runs a data collection script using a Cron job or shell script, and notifies the user if the price drops. The input is the product information registered by the user and current price information, and the output is a notification that a price change has been detected.

[0317] (Application example 2)

[0318] 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."

[0319] In conventional online shopping, users have to compare products from multiple online stores to find the cheapest price, which is time-consuming and inefficient. Furthermore, personalized information is not provided based on the user's emotions or circumstances, making it difficult to achieve a satisfying shopping experience. The present invention aims to solve these problems and provide users with an efficient and personalized shopping experience.

[0320] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0321] In this invention, the server includes means for inputting product information desired by the user, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, means for listing the selected cheapest product information and providing it to the user, means for recognizing the user's emotions and making optimal product suggestions and notifications based on the recognized emotions, and means for evaluating the reliability of the collected information and filtering the product information based on the evaluation results. This allows the user to not only efficiently find the cheapest products, but also receive appropriate product suggestions and notifications according to their emotional state.

[0322] The "means for inputting information about a product desired by the user" is an interface for inputting detailed information about a product that the user wishes to purchase.

[0323] "Means for receiving product information and collecting information such as price, stock status, and shipping charges from multiple online stores on the Internet" refers to a function that automatically collects data such as related price, stock status, and shipping charges from multiple online stores on the Internet based on product information entered by the user.

[0324] "Means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product" refers to algorithms and procedures for analyzing the collected data to calculate the total price of the products and identifying the cheapest product from among them.

[0325] The "means of listing the selected lowest priced product information and providing it to the user" is a function that organizes the lowest priced product information selected through analysis and displays it so that the user can easily check it.

[0326] "Means for recognizing a user's emotions and making optimal product suggestions and notifications based on the recognized emotions" refers to a system that evaluates a user's emotions in real time and generates appropriate product suggestions and notifications according to that state.

[0327] "Means for evaluating the reliability of collected information and filtering product information based on the evaluation results" refers to a function that evaluates the accuracy and reliability of information obtained from each online store and eliminates inaccurate information based on the evaluation results.

[0328] "The total amount calculation means is a means for adding up the product prices and shipping costs" refers to a system for adding up the product prices and shipping costs collected from each online store to calculate the total purchase cost.

[0329] "Means of periodically checking price fluctuations and notifying users when prices drop" refers to a system that periodically monitors the prices of products registered by users and sends notifications to users when prices drop.

[0330] This invention is a system that allows users to efficiently find the lowest prices for products when shopping online. It functions through communication between a server and a terminal. It also incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions. This system is designed to provide users with an appropriate and personalized shopping experience.

[0331] Overall system configuration

[0332] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores for collecting information. It also incorporates an emotion engine that recognizes user emotions. Users enter information about the products they want into their terminal, which then sends the information to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists this information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies the user when prices drop. The emotion engine recognizes the user's emotions during this process and makes appropriate product suggestions and notifications.

[0333] Program processing description

[0334] Hardware and software used

[0335] The server uses a server machine equipped with a high-performance processor and sufficient storage capacity. A Python program is used to collect information and perform the necessary data analysis. The emotion engine uses a pre-trained generative AI model using Keras. The user's device is a smartphone or personal computer, which communicates with the server via an internet connection.

[0336] Data processing and calculation

[0337] When the server receives the product information sent by the user, it accesses multiple online stores on the Internet and scrapes information such as price, stock status, and shipping costs. The data is analyzed using libraries such as BeautifulSoup. The collected data is evaluated for accuracy and reliability, and inaccurate data is filtered out. Next, the product price and shipping costs collected from each store are added together to calculate the total price, and the cheapest product is identified. The results are sent as a list to the user's device.

[0338] Meanwhile, the emotion engine collects user input information and behavioral data and analyzes the user's emotional state using a generative AI model. For example, input speed, selections, and past purchase history are analyzed to estimate the user's current emotional state. Based on this information, product suggestions and notifications that best fit the user's emotions are generated.

[0339] Specific examples

[0340] For example, if a user wants to buy the latest smartphone, they enter the information for "Smartphone Model XYZ" into their device and press the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone Model XYZ" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of this information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone Model XYZ" at the lowest price.

[0341] Example prompt for a generative AI model:

[0342] Provide user data: {typing_speed: 45, recent_clicks: ["home", "search", "product page"]}. A user is searching for "Smartphone XYZ model". Recognize the user's sentiment, gather information on the cheapest online store, and generate an appropriate notification message.

[0343] In this way, the system of the present invention not only enables users to efficiently find the cheapest products, but also allows users to receive appropriate product suggestions and notifications according to their emotional state.

[0344] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0345] Step 1:

[0346] The user inputs information about the product they want into the terminal. The input information is detailed information such as "smartphone XYZ model."

[0347] input:

[0348] Product details entered by the user.

[0349] output:

[0350] The input product information is sent from the terminal to the server.

[0351] Data processing / calculation:

[0352] The terminal prepares the entered text data for transmission to the server.

[0353] Step 2:

[0354] The server sends requests to a plurality of online stores based on the product information received from the terminal.

[0355] input:

[0356] Product information sent from the device.

[0357] output:

[0358] Pricing, stock, shipping information, etc. obtained from online stores.

[0359] Data processing / calculation:

[0360] The server uses the specified keywords to gather the necessary information using the online store's API and web scraping techniques, accessing web pages using Python requests and parsing the HTML data using BeautifulSoup.

[0361] Step 3:

[0362] The server analyzes the collected information, calculates the total price of the items (price + shipping fee), and selects the cheapest item.

[0363] input:

[0364] Pricing, stock, shipping information, etc. obtained from online stores.

[0365] output:

[0366] Information on the total price and lowest prices of products at each online store.

[0367] Data processing / calculation:

[0368] The server calculates a total price for each item by adding up the price and shipping costs, then compares the calculated prices to identify the cheapest item.

[0369] Step 4:

[0370] The server creates a list of the lowest priced products selected and provides it to the user.

[0371] input:

[0372] Lowest price product information, total price.

[0373] output:

[0374] User-viewable list of lowest priced products.

[0375] Data processing / calculation:

[0376] The server formats the selected lowest priced product information into a list format and converts it into a data format for transmission to the user's terminal.

[0377] Step 5:

[0378] The emotion engine analyzes the user's input information and behavioral data to recognize emotions.

[0379] input:

[0380] Behavioral data such as user typing speed, selections, and past purchases.

[0381] output:

[0382] The user's emotional state.

[0383] Data processing / calculation:

[0384] The emotion engine uses a generative AI model (pre-trained using Keras) to predict user emotions from input data.

[0385] Step 6:

[0386] The server then makes optimal product suggestions and notifications based on the recognized emotions.

[0387] input:

[0388] User emotional state, lowest price product information.

[0389] output:

[0390] Personalized notification messages.

[0391] Data processing / calculation:

[0392] The server generates appropriate messages and notifications based on the user's emotional state. For example, a relaxed user might receive a message like, "If you're not in a hurry, this product is perfect for you!"

[0393] Step 7:

[0394] The server monitors price fluctuations and notifies the user if the price drops.

[0395] input:

[0396] Registered product information and historical price data.

[0397] output:

[0398] Get notified when the price drops.

[0399] Data processing / calculation:

[0400] The server periodically retrieves price data for each product and compares it with previous data to detect price fluctuations. If the price drops, the server notifies the user.

[0401] 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.

[0402] 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.

[0403] 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.

[0404] [Second embodiment]

[0405] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0406] 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.

[0407] 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).

[0408] 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.

[0409] 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.

[0410] 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).

[0411] 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.

[0412] 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.

[0413] 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.

[0414] 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.

[0415] 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.

[0416] 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."

[0417] The present invention is a system for efficiently finding the lowest price for a product when a user is shopping online, and functions through communication between a server and a terminal. Specific embodiments of this system will be described below.

[0418] Overall system configuration

[0419] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores that collect information. Users enter information about the products they want into their terminal, which then sends it to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists that information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies users when prices drop.

[0420] Program processing description

[0421] Enter and submit product information

[0422] The user enters information about the product they want into the terminal. For example, they enter detailed information about a "laptop computer" (brand, model, specs, etc.) into a form. The terminal then sends this information to the server.

[0423] Information gathering

[0424] Based on the received product information, the server accesses multiple online stores to collect information on the product's price, stock status, shipping costs, etc. For example, for a specified "laptop computer," the server obtains the price, stock status, and shipping costs from online store A, online store B, and online store C.

[0425] Analysis of information

[0426] The server analyzes all the collected information and calculates the total price of each product from each online store, including shipping costs. It then compares all the totals to find the cheapest option, allowing the user to purchase the product most economically.

[0427] Listing and Notification

[0428] The server creates a list of the lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check the list and purchase the product from the specified link.

[0429] Monitoring price fluctuations

[0430] The server periodically collects and monitors the prices of products from online stores based on the product information registered by the user in advance. If the price drops, the server notifies the device so that the user can obtain the latest lowest price information.

[0431] Specific examples

[0432] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the prices, and sends that information to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0433] Thus, the system of the present invention is designed to help users efficiently and effectively find and purchase products at the lowest prices.

[0434] The processing flow will be explained below.

[0435] Step 1:

[0436] The user enters product information into the terminal, for example, "laptop XYZ model." This prepares the data for the next step.

[0437] Step 2:

[0438] The terminal sends the product information entered by the user to the server, including the product name, model number, specifications, etc.

[0439] Step 3:

[0440] The server sends requests to multiple online stores based on the received product information, and then crawls between the online stores to collect the necessary data.

[0441] Step 4:

[0442] The server analyzes the data collected from each online store. This data includes price, stock status, shipping costs, etc. For example, online store A may retrieve data such as "price: 80,000 yen, shipping cost: 500 yen," and online store B may retrieve data such as "price: 78,000 yen, shipping cost: free."

[0443] Step 5:

[0444] The server calculates the total amount based on the collected data. For example, the total amount for online store A is calculated as 80,500 yen, and the total amount for online store B is calculated as 78,000 yen.

[0445] Step 6:

[0446] The server compares the calculated totals and selects the product with the lowest total price. In this case, online store B's total price of 78,000 yen is the cheapest.

[0447] Step 7:

[0448] The server creates a list of the cheapest products. This list includes the product name, lowest price, store name, and purchase link. For example, it might be listed in the format "laptop XYZ model, price 78,000 yen, store B, link [purchase page]."

[0449] Step 8:

[0450] The server sends the generated list to the terminal, allowing the user to obtain the latest lowest price information.

[0451] Step 9:

[0452] The device displays the list to the user, who can then review the list and click a link to the purchase page.

[0453] Step 10:

[0454] The user clicks on the link and is taken to the designated online store's purchase page, where they can purchase the product at the most economical price.

[0455] The above are the specific processing steps that a user takes from obtaining information about the cheapest product to making a purchase.

[0456] Example 1

[0457] 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."

[0458] In online shopping, users often have to compare products across multiple sales sites to find the best price. Furthermore, product prices often fluctuate, making it difficult to obtain the lowest price information in a timely manner.

[0459] 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.

[0460] In this invention, the server includes means for users to input product information they want, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple sales sites on the Internet, means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, means for listing the selected cheapest product information and providing it to the user, and means for monitoring daily price fluctuations and notifying the user when prices drop, thereby enabling users to efficiently and reliably find and purchase the cheapest products.

[0461] "User" means any individual or legal entity that uses the System to conduct online shopping.

[0462] "Product information" refers to data including detailed information such as the brand, model, and specifications of the product that the user wishes to purchase.

[0463] "Sales Site" refers to any online platform that sells products over the Internet.

[0464] "Price" refers to the purchase price of the Product displayed on the Sales Site.

[0465] "Stock status" refers to information indicating whether or not a product is in stock at a sales site and the quantity.

[0466] "Shipping Costs" refers to any additional costs incurred in shipping the Product.

[0467] "Total amount" refers to the total amount of the product price and shipping fee.

[0468] "Lowest price" refers to the lowest total price of a product across multiple sales sites.

[0469] "Listing" refers to organizing collected and analyzed information and displaying it in a list format.

[0470] "Price fluctuation monitoring" refers to the process of regularly collecting and monitoring product price information and notifying you if there are any fluctuations.

[0471] This invention is a system that allows users to efficiently find the lowest prices for products when shopping online, and it functions through communication between a server and a terminal. It consists of a terminal used by the user, a server that performs the central processing, and multiple sales sites that collect information.

[0472] The user enters the product information they want into the terminal. This product information might include, for example, "laptop, brand ABC, model XYZ, 16GB RAM, 512GB SSD." The terminal converts this information into a data format such as JSON and sends it to the server as an HTTP POST request. When the user enters information into the form and presses the submit button, the input data is sent to the server.

[0473] Based on the received product information, the server sends requests to multiple sales site APIs to obtain information such as the price, stock status, and shipping costs of the target product. For example, the server sends HTTP GET requests to the API endpoints of online stores A, B, and C to collect real-time price information. The obtained information is stored in a database and used for further analysis.

[0474] The server analyzes the price, inventory status, and shipping information collected from each sales site and calculates the total price (product price + shipping). To ensure the most economical product purchase, the server compares all the total prices and identifies the product with the lowest price. For example, if online store A has a total price of 80,000 yen, online store B has a total price of 78,000 yen, and online store C has a total price of 79,000 yen, the server determines that online store B has the lowest price.

[0475] The server creates a list of the cheapest products (price, store name, link, etc.) and sends the list to the user's device. The user can then check the list on their device and purchase the product from the specified link. This process allows users to efficiently find and purchase the cheapest products.

[0476] Furthermore, the server periodically collects and monitors the prices of products registered by the user from various sales sites, based on the product information. If there is a price change, the information is sent to the terminal. For example, when the price of a registered "laptop computer" drops, the information is sent to the user, allowing the user to obtain the latest lowest price information.

[0477] As a concrete example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to a server, which then collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple sales sites. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of that information, and sends it to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0478] Example prompt sentence:

[0479] "Compare online stores to find the cheapest deal on the latest smartphone model XYZ. Collect pricing, availability, and shipping information from each store and tell me the cheapest option."

[0480] In this way, the system of the present invention helps users efficiently and reliably find and purchase products at the lowest prices.

[0481] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0482] Step 1: Enter product information

[0483] The user enters details of the product they want into the terminal, such as "laptop, brand ABC, model XYZ, 16GB RAM, 512GB SSD." The terminal receives the user's input, formats the information as JSON data, and sends it to the server as an HTTP POST request.

[0484] Input: Product information entered by the user (brand, model, specifications, etc.)

[0485] Data processing: Convert product information into JSON format

[0486] Output: HTTP POST request with product information in JSON format

[0487] Specific behavior:

[0488] The user enters "Brand ABC, Model XYZ, 16GB RAM, 512GB SSD" into the form and presses the submit button. The device receives this information and sends the following JSON data to the server:

[0489] json

[0490] {

[0491] "category": "laptop",

[0492] "brand": "Brand ABC",

[0493] "model": "XYZ",

[0494] "specs": {

[0495] "RAM": "16GB",

[0496] "storage": "512GB SSD"

[0497] }

[0498] }

[0499] Step 2: Gather information

[0500] Based on the received product information, the server sends requests to multiple sales site APIs to obtain information such as the price, stock status, shipping costs, etc. It sends HTTP GET requests to each sales site to collect real-time data.

[0501] Input: Product information in JSON format

[0502] Data processing: Generating and sending HTTP GET requests to each sales site

[0503] Output: Price, stock status, and shipping information for each sales site (JSON format)

[0504] Specific behavior:

[0505] Your server sends an API request to your online store like this:

[0506] Online Store A's API: GET https: / / api.storeA.com / products?brand=BrandABC&model=XYZ

[0507] Online Store B's API: GET https: / / api.storeB.com / products?brand=BrandABC&model=XYZ

[0508] Online Store C API: GET https: / / api.storeC.com / products?brand=BrandABC&model=XYZ

[0509] Step 3: Analyze the information

[0510] The server analyzes the price, stock status, and shipping information collected from each sales site, calculates the total price of the product, and identifies the cheapest product based on the total price (product price + shipping).

[0511] Input: Price, stock status, shipping information for each sales site

[0512] Data processing: Calculate the total price by adding up the price and shipping fee, and identify the lowest price

[0513] Output: Cheapest seller information (price, total price, store name, link, etc.)

[0514] Specific behavior:

[0515] Calculate the total amount based on the data retrieved by the server:

[0516] Online Store A: Price: 70,000 yen, shipping: 10,000 yen → Total: 80,000 yen

[0517] Online Store B: Price: 75,000 yen, shipping: 3,000 yen → Total: 78,000 yen

[0518] Online Store C: Price 72,000 yen, shipping 7,000 yen → Total 79,000 yen

[0519] The server identifies online store B, which has the lowest price (total price: 78,000 yen).

[0520] Step 4: List and notify

[0521] The server creates a list of the lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check the list on their device and access the product purchase link.

[0522] Input: Cheapest price sales site information

[0523] Data processing: Formatting information into a list and generating notification data

[0524] Output: List sent to user's device (lowest price information)

[0525] Specific behavior:

[0526] The server lists the best prices as follows:

[0527] json

[0528] {

[0529] "store": "Online Store B",

[0530] "price": 78,000,

[0531] "link": "https: / / storeB.com / product / xyz"

[0532] }

[0533] The server sends this list to the user's device, and the user can access the purchase link.

[0534] Step 5: Monitor price fluctuations

[0535] The server periodically collects and monitors prices from each sales site based on product information registered in advance by the user, and notifies the user if the price drops.

[0536] Input: Registered product information, price information of each sales site

[0537] Data processing: Regular collection and monitoring of price information, and generation of notification data in the event of fluctuations

[0538] Output: Notification data when price changes

[0539] Specific behavior:

[0540] The server accesses each sales site's API at a specified time each day to collect price information. For example, if the price drops from 70,000 yen to 65,000 yen, that information is sent to the user's device.

[0541] (Application example 1)

[0542] 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."

[0543] In conventional online shopping systems, users often spend a great deal of time and effort finding the lowest priced products, and the lack of a seamless purchasing process can be frustrating. Furthermore, many systems lack the functionality to monitor price fluctuations and provide timely notifications, making it easy to miss opportunities to purchase at the lowest price. Therefore, there is a need for a system that can efficiently and seamlessly find the lowest priced products, quickly complete the payment process, and provide timely notifications of price fluctuations.

[0544] 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.

[0545] In this invention, the server includes means for inputting product information that a user wants, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, means for analyzing the collected information, calculating the total cost of the products, and selecting the cheapest product, means for listing the selected cheapest product information and providing it to the user, means for processing payments, and means for seamlessly executing the reception, collection, analysis, and payment of information as a series of processes. This enables users to efficiently and seamlessly find the cheapest products and pay quickly, and also allows them to avoid missing the optimal timing for purchase by receiving timely notifications of price fluctuations.

[0546] "Means for users to input product information they want" refers to an interface that allows users to input detailed information about the product they wish to acquire.

[0547] "Means for receiving product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet" refers to a communication means for collecting related data from multiple online stores on the Internet based on product information entered by a user.

[0548] "Means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product" refers to an algorithm that analyzes the collected data, calculates the total price by adding the product price and shipping costs, and selects the cheapest option.

[0549] "Means for listing the selected lowest priced product information and providing it to the user" refers to a component that organizes the information on the lowest priced products based on the analysis results, displays it as a list, and provides it to the user.

[0550] "Means for processing payments and for seamlessly receiving, collecting, analyzing information, and processing payments as a series of processes" refers to the overall system functions for carrying out payment procedures to purchase selected products, and for consistently and seamlessly collecting, analyzing information, and processing payments.

[0551] "Means to sum product prices and shipping costs" refers to a component that has the logic to calculate the total by adding up the product prices and shipping costs collected from the online store.

[0552] "A means of periodically checking price fluctuations based on product information registered by the user and notifying the user when the price drops" refers to a function that periodically checks the prices of products registered by the user in advance and notifies the user in real time when the price drops.

[0553] This invention is an electronic payment system that enables a user to purchase a desired product at the lowest price, and is realized by the following configuration.

[0554] Overall system configuration

[0555] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores that collect information. Users enter information about the products they want into their terminal and send it from the terminal to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from online stores. It identifies the products with the lowest prices, lists this information, and sends it to the terminal. It also provides a function to monitor daily price fluctuations and notify users when prices drop. Finally, it supports users so that they can smoothly complete payment at the store with the lowest price.

[0556] Program processing description

[0557] Enter and submit product information

[0558] The user inputs information about the product they want through the terminal interface. For example, they enter detailed information about a "laptop computer" (such as brand, model, and specifications) into a form, and the information is sent to the server.

[0559] Information gathering

[0560] Based on the received product information, the server accesses multiple online stores to collect information such as the price, stock status, shipping costs, etc. This process uses Python's requests library to obtain data from the Internet via API.

[0561] Analysis of information

[0562] The server analyzes all the collected information and calculates the total price of each online store, adding up the product price and shipping costs. It then compares the products and finds the cheapest option, using a data analysis library (e.g., Pandas or NumPy).

[0563] Listing and Notification

[0564] The server creates a list of the selected lowest priced products (price, store name, link, etc.) and provides the list to the user's device. The user can check the list and purchase the product from the specified link. This includes a notification system with a user interface (UI), such as email or in-app notifications.

[0565] Payment Processing

[0566] When the user decides to purchase from the store with the lowest price, the server executes the procedure for payment processing. For this, the payment API is used to securely send the user's credit card information, etc. A payment completion notification is sent to the user, and the system updates the purchase history.

[0567] Monitoring price fluctuations

[0568] The server periodically collects and monitors the price of a product from the online store based on the product information registered by the user in advance. If the price drops, the server notifies the device. For example, if the price of the "Laptop XYZ Model" registered by the user drops, the device will receive a notification such as "The price of Laptop XYZ Model has dropped: The current lowest price is 70,000 yen."

[0569] Examples of concrete examples and prompts

[0570] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the prices, and sends that information to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0571] As a result, this system allows users to efficiently and seamlessly find the lowest priced products and quickly complete payment.

[0572] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0573] Step 1:

[0574] The user uses a device to input information about the product they want, specifically details such as "laptop XYZ model" (brand, model, specs, etc.) into the device's interface, and the information is sent to the server. The input product information is converted into an API request format and sent to the server.

[0575] Step 2:

[0576] Based on the received product information, the server accesses multiple online stores on the Internet and collects information such as product price, stock status, and shipping costs. The server uses the Python requests library to request product information from the API of each online store and receives data in JSON format. The input is product information, and the output is the product data obtained from each online store.

[0577] Step 3:

[0578] The server analyzes all the collected information and calculates the total product price (price + shipping cost). Specifically, it uses data analysis libraries such as Pandas and NumPy to add up the product price and shipping cost for each online store and calculate the total price. The input is the product data collected from each online store, and the output is the analyzed data including the total price.

[0579] Step 4:

[0580] The server identifies the cheapest products based on the analysis results and lists the information. The lowest price is calculated using logic that compares all total prices and identifies the cheapest one. The input is the analysis data including the total price, and the output is a list of the cheapest products.

[0581] Step 5:

[0582] The server provides the selected cheapest product information to the user's device. Specifically, it sends a notification to the user's device, displaying details of the cheapest product, the store name, a purchase link, etc. The input is a list of cheapest product information, and the output is a notification and link displayed on the user's device.

[0583] Step 6:

[0584] The user uses the device to purchase the cheapest product from the provided link. Once the user proceeds with the purchase, the server executes the payment process. The payment process involves calling the payment API of each online store, sending payment information, and receiving the payment result. The input is the user's payment information, and the output is a payment completion notification.

[0585] Step 7:

[0586] The server periodically monitors price fluctuations based on the product information registered by the user. For example, it uses a Python scheduling library to call the API of each online store every hour to obtain the latest price information. The input is the registered product information, and the output is the latest price information.

[0587] Step 8:

[0588] The server notifies the user when the price drops. When a price change is detected, it sends a notification to the user's device, providing the latest lowest price information. For example, it sends a notification such as "The price of laptop model XYZ has dropped: the current lowest price is 70,000 yen." The input is the latest price information, and the output is the notification to the user.

[0589] 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.

[0590] The present invention is a system for efficiently finding the lowest prices for products when a user is shopping online, and functions through communication between a server and a terminal. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions. This system is designed to provide users with an appropriate and personalized purchasing experience. Specific embodiments of this system are described below.

[0591] Overall system configuration

[0592] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores for collecting information. In addition, it incorporates an emotion engine that recognizes the user's emotions. The user enters information about the product they want into the terminal, which then sends it to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists this information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies the user when prices drop. The emotion engine recognizes the user's emotions during this process and makes appropriate product suggestions and notifications.

[0593] Program processing description

[0594] Enter and submit product information

[0595] The user enters information about the product they want into the terminal. For example, they enter detailed information about "laptop model XYZ" (brand, model, specs, etc.) into a form. The terminal then sends this information to the server.

[0596] Information gathering

[0597] The server sends requests to multiple online stores based on the received product information. Based on the product information, the server crawls between online stores to collect the necessary data. For example, for a specified "laptop," it retrieves the price, stock information, and shipping costs from online store A, online store B, and online store C.

[0598] Analysis of information

[0599] The server analyzes all the collected information and calculates the total price of each product from each online store, including shipping costs. It then compares all the totals to find the cheapest option, allowing the user to purchase the product most economically.

[0600] Emotion Engine Operation

[0601] The emotion engine recognizes emotions from user input and selections. For example, it analyzes the user's input speed, items selected, purchase history, etc. to determine the user's current emotion. Based on this emotional information, it makes optimal product suggestions and notifies the user at the appropriate time. For example, if it determines that the user is in a hurry, it will prioritize displaying a list of products that can be delivered immediately.

[0602] Listing and Notification

[0603] The server creates a list of the selected lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check this list and purchase the product from the specified link. The emotion engine also improves the user experience by notifying users of the lowest priced products at the appropriate time.

[0604] Monitoring price fluctuations

[0605] The server periodically collects and monitors the price of a product from online stores based on the product information registered by the user in advance. If the price drops, the server notifies the user of the latest lowest price information. The emotion engine also participates in this notification, providing personalized notifications that take into account the user's current emotional state.

[0606] Specific examples

[0607] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0608] In this way, the system of the present invention is designed to help users efficiently and effectively find and purchase products at the lowest prices, and by combining it with an emotion engine, it provides users with a personalized purchasing experience.

[0609] The processing flow will be explained below.

[0610] Step 1:

[0611] The user enters product information into the terminal. For example, they enter a specific product name, model number, specifications, etc., such as "laptop XYZ model," into the form. This allows the system to retrieve the product information they are searching for.

[0612] Step 2:

[0613] The terminal sends the entered product information to the server, which then prepares to start processing based on the received information.

[0614] Step 3:

[0615] A server sends a search request to multiple online stores, including keywords such as product name, model number, etc. For example, a request for "laptop model XYZ" is sent to online store A, online store B, and online store C.

[0616] Step 4:

[0617] The server receives data returned from the online stores, including the price, stock status, shipping costs, etc. For example, online store A may return "price 80,000 yen, shipping cost 500 yen," while online store B may return "price 78,000 yen, shipping cost free."

[0618] Step 5:

[0619] The server analyzes the collected data and calculates the total price for each item. For example, the total price for online store A is calculated as 80,500 yen, and the total price for online store B is calculated as 78,000 yen.

[0620] Step 6:

[0621] The server compares the total prices and selects the product with the lowest total price. In this case, it determines that the product with the lowest total price of 78,000 yen from Online Store B is the cheapest.

[0622] Step 7:

[0623] The server creates a list of the lowest priced products (price, store name, purchase link, etc.). For example, it creates a list like "Laptop XYZ model, price 78,000 yen, store B, link [purchase page]."

[0624] Step 8:

[0625] The server sends the generated list to the terminal, allowing the user to obtain the latest lowest price information.

[0626] Step 9:

[0627] The device displays the list to the user, who can then review the list and click a link to the purchase page.

[0628] Step 10:

[0629] The user clicks on the link and is taken to the designated online store's purchase page, where they can purchase the product at the most economical price.

[0630] Step 11:

[0631] The emotion engine recognizes emotions from user input and selections. For example, if the user is typing in a hurry, the emotion engine will detect "impatience" and respond appropriately.

[0632] Step 12:

[0633] The emotion engine makes optimal product suggestions based on the user's emotions. For example, if it determines that the user is in a hurry, it will suggest products that can be delivered immediately.

[0634] Step 13:

[0635] The emotion engine will notify you at the right time, for example, when the price drops or when you are feeling relaxed, taking into account the user's emotional state.

[0636] Step 14:

[0637] The server periodically checks price fluctuations, and when the price drops, it works with the emotion engine to send a notification to the user. The emotion engine takes into account the user's current emotions and adjusts the appropriate notification content and timing.

[0638] In this way, the system of the present invention provides users with an optimal purchasing experience by seamlessly collecting product information, making optimal suggestions, and providing personalized notifications based on emotions.

[0639] Example 2

[0640] 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."

[0641] When consumers shop online, it is extremely time-consuming to check numerous e-commerce sites individually to find the lowest priced product. Furthermore, as user needs become more diverse, it is important not only to simply offer the lowest priced product, but also to suggest products that reflect the user's emotions and circumstances. Furthermore, monitoring price fluctuations even after purchase and notifying users when prices drop is necessary to improve user satisfaction.

[0642] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting product information desired by the user, a means for receiving the product information and collecting information such as price, stock status, and shipping fee from multiple e-commerce sites on a communication network, a means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product, a means for listing the selected cheapest product information and providing it to the user, and a means for recognizing the user's emotional state and suggesting products or notifying them based on the user's emotion. This enables the user to efficiently and quickly find the cheapest products, providing a personalized shopping experience.

[0643] A "user" is a person who uses the system to shop online.

[0644] "Product information" refers to detailed data such as the brand, model, and specifications of the product that the user wishes to purchase.

[0645] "Communications Network" means the infrastructure for carrying the Internet and other data communications.

[0646] "E-commerce site" refers to a website or online marketplace that sells products over the Internet.

[0647] "Price" refers to the selling price of the Product.

[0648] "Inventory status" refers to whether a particular item is available for sale and in what quantity.

[0649] "Shipping Fee" refers to the shipping fee incurred when delivering a product to a purchaser.

[0650] "Means of collection" refers to the process or technology by which the server obtains the necessary information from multiple e-commerce sites.

[0651] "Analytical methods" refers to the algorithms or methods used to examine the collected data and identify the lowest prices.

[0652] "Total" refers to the total price of the product and shipping fee.

[0653] "Means of selection" refers to the process of choosing the cheapest option from multiple options.

[0654] "Listing methods" refers to methods for organizing selected information and presenting it in a format that is easy for users to understand.

[0655] "Means of providing" refers to the process of presenting the listed information to the user.

[0656] "Emotional state" refers to a user's current mental or emotional state.

[0657] "Means for making suggestions and notifications based on emotions" refers to algorithms and technologies that analyze users' emotions and make product suggestions and notifications accordingly.

[0658] This invention is a system that allows users to efficiently find the lowest priced products when shopping online. This system is primarily composed of a terminal used by the user, a server that collects and analyzes information, and multiple e-commerce sites that provide data. It also incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions.

[0659] Overall system configuration

[0660] The user inputs the desired product information into the terminal, for example, "laptop XYZ model," including detailed information such as brand, model, and specifications. The terminal then sends this input information to the server.

[0661] Based on the received product information, the server uses programming languages ​​such as Python or Java to collect the necessary data from multiple e-commerce sites. Specifically, it uses scraping tools (e.g., BeautifulSoup or Selenium) and APIs to obtain the price, stock information, and shipping costs of the specified product. For example, it collects price information from online store A, online store B, and online store C.

[0662] The server analyzes all the collected information and calculates the total price by adding the product price and shipping costs from each e-commerce site. The collected data is stored in a data frame using Python's pandas, and an algorithm is run to find the lowest price by adding a column for the total price.

[0663] The emotion engine recognizes emotions from user input and selection history. For example, it analyzes the user's input speed, click patterns, and past purchase history to determine the user's current emotion using NLP (natural language processing) libraries and machine learning models (e.g., scikit-learn and TensorFlow). If the user is in a hurry, it can prioritize a list of products that can be delivered immediately.

[0664] The server selects the lowest priced products and lists them using an HTML template engine (e.g., Jinja2). This list is sent to the user's device, where the user can view the information and purchase the products from the specified link.

[0665] The server periodically collects price fluctuations for products registered by the user from online stores and notifies the device when the price drops. This process is scheduled periodically using a Cron job or shell script. The emotion engine also participates in notifications, providing personalized notifications that take into account the user's current emotional state.

[0666] Specific examples

[0667] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to a server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple e-commerce sites. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0668] Prompt Sentence Examples

[0669] Here are some example prompts to input to a generative AI model:

[0670] 1. "I would like to develop an online shopping system. The user inputs information about the product they want, and based on that information, the system retrieves information about the lowest prices from multiple online stores. I would also like to incorporate an emotion recognition function so that the system can suggest appropriate products based on the user's emotions. Please explain the implementation of this system and the specific processing method."

[0671] 2. "I'm designing a system to find the lowest price when a user purchases a smartphone. I'd also like to use an emotion engine to suggest products based on the user's emotions. Please explain the overall flow of this system and the specific processing steps."

[0672] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0673] Step 1:

[0674] A user enters information about the product they want into a device. Specifically, they enter details about the brand, model, specs, etc. of "laptop XYZ model" into a web form on the device. The entered data is converted into JSON format and prepared for further processing. The input data is detailed information about the product, and the output is structured data in JSON format.

[0675] Step 2:

[0676] The terminal sends the product information entered by the user to the server. Specifically, it uses an HTTP POST request to send the product information data to the server's endpoint. At this time, the data is sent along with the appropriate HTTP headers. The input is the product information in JSON format, and the output is a success message sent to the server.

[0677] Step 3:

[0678] The server sends requests to multiple e-commerce sites based on the received product information. Specifically, it uses a Python scraping tool (e.g., BeautifulSoup or Selenium) to collect product data (price, stock, shipping costs) from each site. The input is detailed product information in JSON format, and the output is the raw data obtained from each site.

[0679] Step 4:

[0680] The server analyzes all the collected information and calculates the total price of the items. Specifically, it uses the Python pandas library to store the information in a data frame and runs an algorithm to calculate the total price by adding up the price and shipping. The input is a data frame of raw data, and the output is a data frame with the calculated total price.

[0681] Step 5:

[0682] The server selects the cheapest product from the data analysis results. Using the Python standard library, it runs an algorithm to select the row with the lowest value in the total price column. The input is a data frame with the calculated total price, and the output is the information about the cheapest product.

[0683] Step 6:

[0684] The server lists the selected cheapest products. Specifically, it uses an HTML template engine (e.g., Jinja2) to generate a visually organized list format HTML. The input is the cheapest product information, and the output is the HTML list data.

[0685] Step 7:

[0686] The server sends the generated list to the terminal. Specifically, it returns HTML data to the terminal as an HTTP response or sends it in real time using WebSocket. The input is the list HTML data, and the output is a notification message to the user terminal.

[0687] Step 8:

[0688] The emotion engine recognizes the user's emotions and provides optimal product suggestions and notifications. Specifically, it uses NLP libraries and machine learning models (e.g., scikit-learn and TensorFlow) to analyze the user's input speed and past selection data and cluster emotions. The input is user behavior data, and the output is emotion labels and notifications based on them.

[0689] Step 9:

[0690] The server periodically monitors price fluctuations based on product information registered in advance by the user. Specifically, it periodically runs a data collection script using a Cron job or shell script, and notifies the user if the price drops. The input is the product information registered by the user and current price information, and the output is a notification that a price change has been detected.

[0691] (Application example 2)

[0692] 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."

[0693] In conventional online shopping, users have to compare products from multiple online stores to find the cheapest price, which is time-consuming and inefficient. Furthermore, personalized information is not provided based on the user's emotions or circumstances, making it difficult to achieve a satisfying shopping experience. The present invention aims to solve these problems and provide users with an efficient and personalized shopping experience.

[0694] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0695] In this invention, the server includes means for inputting product information desired by the user, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, means for listing the selected cheapest product information and providing it to the user, means for recognizing the user's emotions and making optimal product suggestions and notifications based on the recognized emotions, and means for evaluating the reliability of the collected information and filtering the product information based on the evaluation results. This allows the user to not only efficiently find the cheapest products, but also receive appropriate product suggestions and notifications according to their emotional state.

[0696] The "means for inputting information about a product desired by the user" is an interface for inputting detailed information about a product that the user wishes to purchase.

[0697] "Means for receiving product information and collecting information such as price, stock status, and shipping charges from multiple online stores on the Internet" refers to a function that automatically collects data such as related price, stock status, and shipping charges from multiple online stores on the Internet based on product information entered by the user.

[0698] "Means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product" refers to algorithms and procedures for analyzing the collected data to calculate the total price of the products and identifying the cheapest product from among them.

[0699] The "means of listing the selected lowest priced product information and providing it to the user" is a function that organizes the lowest priced product information selected through analysis and displays it so that the user can easily check it.

[0700] "Means for recognizing a user's emotions and making optimal product suggestions and notifications based on the recognized emotions" refers to a system that evaluates a user's emotions in real time and generates appropriate product suggestions and notifications according to that state.

[0701] "Means for evaluating the reliability of collected information and filtering product information based on the evaluation results" refers to a function that evaluates the accuracy and reliability of information obtained from each online store and eliminates inaccurate information based on the evaluation results.

[0702] "The total amount calculation means is a means for adding up the product prices and shipping costs" refers to a system for adding up the product prices and shipping costs collected from each online store to calculate the total purchase cost.

[0703] "Means of periodically checking price fluctuations and notifying users when prices drop" refers to a system that periodically monitors the prices of products registered by users and sends notifications to users when prices drop.

[0704] This invention is a system that allows users to efficiently find the lowest prices for products when shopping online. It functions through communication between a server and a terminal. It also incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions. This system is designed to provide users with an appropriate and personalized shopping experience.

[0705] Overall system configuration

[0706] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores for collecting information. It also incorporates an emotion engine that recognizes user emotions. Users enter information about the products they want into their terminal, which then sends the information to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists this information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies the user when prices drop. The emotion engine recognizes the user's emotions during this process and makes appropriate product suggestions and notifications.

[0707] Program processing description

[0708] Hardware and software used

[0709] The server uses a server machine equipped with a high-performance processor and sufficient storage capacity. A Python program is used to collect information and perform the necessary data analysis. The emotion engine uses a pre-trained generative AI model using Keras. The user's device is a smartphone or personal computer, which communicates with the server via an internet connection.

[0710] Data processing and calculation

[0711] When the server receives the product information sent by the user, it accesses multiple online stores on the Internet and scrapes information such as price, stock status, and shipping costs. The data is analyzed using libraries such as BeautifulSoup. The collected data is evaluated for accuracy and reliability, and inaccurate data is filtered out. Next, the product price and shipping costs collected from each store are added together to calculate the total price, and the cheapest product is identified. The results are sent as a list to the user's device.

[0712] Meanwhile, the emotion engine collects user input information and behavioral data and analyzes the user's emotional state using a generative AI model. For example, input speed, selections, and past purchase history are analyzed to estimate the user's current emotional state. Based on this information, product suggestions and notifications that best fit the user's emotions are generated.

[0713] Specific examples

[0714] For example, if a user wants to buy the latest smartphone, they enter the information for "Smartphone Model XYZ" into their device and press the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone Model XYZ" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of this information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone Model XYZ" at the lowest price.

[0715] Example prompt for a generative AI model:

[0716] Provide user data: {typing_speed: 45, recent_clicks: ["home", "search", "product page"]}. A user is searching for "Smartphone XYZ model". Recognize the user's sentiment, gather information on the cheapest online store, and generate an appropriate notification message.

[0717] In this way, the system of the present invention not only enables users to efficiently find the cheapest products, but also allows users to receive appropriate product suggestions and notifications according to their emotional state.

[0718] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0719] Step 1:

[0720] The user inputs information about the product they want into the terminal. The input information is detailed information such as "smartphone XYZ model."

[0721] input:

[0722] Product details entered by the user.

[0723] output:

[0724] The input product information is sent from the terminal to the server.

[0725] Data processing / calculation:

[0726] The terminal prepares the entered text data for transmission to the server.

[0727] Step 2:

[0728] The server sends requests to a plurality of online stores based on the product information received from the terminal.

[0729] input:

[0730] Product information sent from the device.

[0731] output:

[0732] Pricing, stock, shipping information, etc. obtained from online stores.

[0733] Data processing / calculation:

[0734] The server uses the specified keywords to gather the necessary information using the online store's API and web scraping techniques, accessing web pages using Python requests and parsing the HTML data using BeautifulSoup.

[0735] Step 3:

[0736] The server analyzes the collected information, calculates the total price of the items (price + shipping fee), and selects the cheapest item.

[0737] input:

[0738] Pricing, stock, shipping information, etc. obtained from online stores.

[0739] output:

[0740] Information on the total price and lowest prices of products at each online store.

[0741] Data processing / calculation:

[0742] The server calculates a total price for each item by adding up the price and shipping costs, then compares the calculated prices to identify the cheapest item.

[0743] Step 4:

[0744] The server creates a list of the lowest priced products selected and provides it to the user.

[0745] input:

[0746] Lowest price product information, total price.

[0747] output:

[0748] User-viewable list of lowest priced products.

[0749] Data processing / calculation:

[0750] The server formats the selected lowest priced product information into a list format and converts it into a data format for transmission to the user's terminal.

[0751] Step 5:

[0752] The emotion engine analyzes the user's input information and behavioral data to recognize emotions.

[0753] input:

[0754] Behavioral data such as user typing speed, selections, and past purchases.

[0755] output:

[0756] The user's emotional state.

[0757] Data processing / calculation:

[0758] The emotion engine uses a generative AI model (pre-trained using Keras) to predict user emotions from input data.

[0759] Step 6:

[0760] The server then makes optimal product suggestions and notifications based on the recognized emotions.

[0761] input:

[0762] User emotional state, lowest price product information.

[0763] output:

[0764] Personalized notification messages.

[0765] Data processing / calculation:

[0766] The server generates appropriate messages and notifications based on the user's emotional state. For example, a relaxed user might receive a message like, "If you're not in a hurry, this product is perfect for you!"

[0767] Step 7:

[0768] The server monitors price fluctuations and notifies the user if the price drops.

[0769] input:

[0770] Registered product information and historical price data.

[0771] output:

[0772] Get notified when the price drops.

[0773] Data processing / calculation:

[0774] The server periodically retrieves price data for each product and compares it with previous data to detect price fluctuations. If the price drops, the server notifies the user.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] [Third embodiment]

[0779] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0780] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0781] 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).

[0782] 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.

[0783] 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.

[0784] 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).

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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."

[0791] The present invention is a system for efficiently finding the lowest price for a product when a user is shopping online, and functions through communication between a server and a terminal. Specific embodiments of this system will be described below.

[0792] Overall system configuration

[0793] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores that collect information. Users enter information about the products they want into their terminal, which then sends it to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists that information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies users when prices drop.

[0794] Program processing description

[0795] Enter and submit product information

[0796] The user enters information about the product they want into the terminal. For example, they enter detailed information about a "laptop computer" (brand, model, specs, etc.) into a form. The terminal then sends this information to the server.

[0797] Information gathering

[0798] Based on the received product information, the server accesses multiple online stores to collect information on the product's price, stock status, shipping costs, etc. For example, for a specified "laptop computer," the server obtains the price, stock status, and shipping costs from online store A, online store B, and online store C.

[0799] Analysis of information

[0800] The server analyzes all the collected information and calculates the total price of each product from each online store, including shipping costs. It then compares all the totals to find the cheapest option, allowing the user to purchase the product most economically.

[0801] Listing and Notification

[0802] The server creates a list of the lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check the list and purchase the product from the specified link.

[0803] Monitoring price fluctuations

[0804] The server periodically collects and monitors the prices of products from online stores based on the product information registered by the user in advance. If the price drops, the server notifies the device so that the user can obtain the latest lowest price information.

[0805] Specific examples

[0806] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the prices, and sends that information to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0807] Thus, the system of the present invention is designed to help users efficiently and effectively find and purchase products at the lowest prices.

[0808] The processing flow will be explained below.

[0809] Step 1:

[0810] The user enters product information into the terminal, for example, "laptop XYZ model." This prepares the data for the next step.

[0811] Step 2:

[0812] The terminal sends the product information entered by the user to the server, including the product name, model number, specifications, etc.

[0813] Step 3:

[0814] The server sends requests to multiple online stores based on the received product information, and then crawls between the online stores to collect the necessary data.

[0815] Step 4:

[0816] The server analyzes the data collected from each online store. This data includes price, stock status, shipping costs, etc. For example, online store A may retrieve data such as "price: 80,000 yen, shipping cost: 500 yen," and online store B may retrieve data such as "price: 78,000 yen, shipping cost: free."

[0817] Step 5:

[0818] The server calculates the total amount based on the collected data. For example, the total amount for online store A is calculated as 80,500 yen, and the total amount for online store B is calculated as 78,000 yen.

[0819] Step 6:

[0820] The server compares the calculated totals and selects the product with the lowest total price. In this case, online store B's total price of 78,000 yen is the cheapest.

[0821] Step 7:

[0822] The server creates a list of the cheapest products. This list includes the product name, lowest price, store name, and purchase link. For example, it might be listed in the format "laptop XYZ model, price 78,000 yen, store B, link [purchase page]."

[0823] Step 8:

[0824] The server sends the generated list to the terminal, allowing the user to obtain the latest lowest price information.

[0825] Step 9:

[0826] The device displays the list to the user, who can then review the list and click a link to the purchase page.

[0827] Step 10:

[0828] The user clicks on the link and is taken to the designated online store's purchase page, where they can purchase the product at the most economical price.

[0829] The above are the specific processing steps that a user takes from obtaining information about the cheapest product to making a purchase.

[0830] Example 1

[0831] 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."

[0832] In online shopping, users often have to compare products across multiple sales sites to find the best price. Furthermore, product prices often fluctuate, making it difficult to obtain the lowest price information in a timely manner.

[0833] 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.

[0834] In this invention, the server includes means for users to input product information they want, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple sales sites on the Internet, means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, means for listing the selected cheapest product information and providing it to the user, and means for monitoring daily price fluctuations and notifying the user when prices drop, thereby enabling users to efficiently and reliably find and purchase the cheapest products.

[0835] "User" means any individual or legal entity that uses the System to conduct online shopping.

[0836] "Product information" refers to data including detailed information such as the brand, model, and specifications of the product that the user wishes to purchase.

[0837] "Sales Site" refers to any online platform that sells products over the Internet.

[0838] "Price" refers to the purchase price of the Product displayed on the Sales Site.

[0839] "Stock status" refers to information indicating whether or not a product is in stock at a sales site and the quantity.

[0840] "Shipping Costs" refers to any additional costs incurred in shipping the Product.

[0841] "Total amount" refers to the total amount of the product price and shipping fee.

[0842] "Lowest price" refers to the lowest total price of a product across multiple sales sites.

[0843] "Listing" refers to organizing collected and analyzed information and displaying it in a list format.

[0844] "Price fluctuation monitoring" refers to the process of regularly collecting and monitoring product price information and notifying you if there are any fluctuations.

[0845] This invention is a system that allows users to efficiently find the lowest prices for products when shopping online, and it functions through communication between a server and a terminal. It consists of a terminal used by the user, a server that performs the central processing, and multiple sales sites that collect information.

[0846] The user enters the product information they want into the terminal. This product information might include, for example, "laptop, brand ABC, model XYZ, 16GB RAM, 512GB SSD." The terminal converts this information into a data format such as JSON and sends it to the server as an HTTP POST request. When the user enters information into the form and presses the submit button, the input data is sent to the server.

[0847] Based on the received product information, the server sends requests to multiple sales site APIs to obtain information such as the price, stock status, and shipping costs of the target product. For example, the server sends HTTP GET requests to the API endpoints of online stores A, B, and C to collect real-time price information. The obtained information is stored in a database and used for further analysis.

[0848] The server analyzes the price, inventory status, and shipping information collected from each sales site and calculates the total price (product price + shipping). To ensure the most economical product purchase, the server compares all the total prices and identifies the product with the lowest price. For example, if online store A has a total price of 80,000 yen, online store B has a total price of 78,000 yen, and online store C has a total price of 79,000 yen, the server determines that online store B has the lowest price.

[0849] The server creates a list of the cheapest products (price, store name, link, etc.) and sends the list to the user's device. The user can then check the list on their device and purchase the product from the specified link. This process allows users to efficiently find and purchase the cheapest products.

[0850] Furthermore, the server periodically collects and monitors the prices of products registered by the user from various sales sites, based on the product information. If there is a price change, the information is sent to the terminal. For example, when the price of a registered "laptop computer" drops, the information is sent to the user, allowing the user to obtain the latest lowest price information.

[0851] As a concrete example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to a server, which then collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple sales sites. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of that information, and sends it to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0852] Example prompt sentence:

[0853] "Compare online stores to find the cheapest deal on the latest smartphone model XYZ. Collect pricing, availability, and shipping information from each store and tell me the cheapest option."

[0854] In this way, the system of the present invention helps users efficiently and reliably find and purchase products at the lowest prices.

[0855] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0856] Step 1: Enter product information

[0857] The user enters details of the product they want into the terminal, such as "laptop, brand ABC, model XYZ, 16GB RAM, 512GB SSD." The terminal receives the user's input, formats the information as JSON data, and sends it to the server as an HTTP POST request.

[0858] Input: Product information entered by the user (brand, model, specifications, etc.)

[0859] Data processing: Convert product information into JSON format

[0860] Output: HTTP POST request with product information in JSON format

[0861] Specific behavior:

[0862] The user enters "Brand ABC, Model XYZ, 16GB RAM, 512GB SSD" into the form and presses the submit button. The device receives this information and sends the following JSON data to the server:

[0863] json

[0864] {

[0865] "category": "laptop",

[0866] "brand": "Brand ABC",

[0867] "model": "XYZ",

[0868] "specs": {

[0869] "RAM": "16GB",

[0870] "storage": "512GB SSD"

[0871] }

[0872] }

[0873] Step 2: Gather information

[0874] Based on the received product information, the server sends requests to multiple sales site APIs to obtain information such as the price, stock status, shipping costs, etc. It sends HTTP GET requests to each sales site to collect real-time data.

[0875] Input: Product information in JSON format

[0876] Data processing: Generating and sending HTTP GET requests to each sales site

[0877] Output: Price, stock status, and shipping information for each sales site (JSON format)

[0878] Specific behavior:

[0879] Your server sends an API request to your online store like this:

[0880] Online Store A's API: GET https: / / api.storeA.com / products?brand=BrandABC&model=XYZ

[0881] Online Store B's API: GET https: / / api.storeB.com / products?brand=BrandABC&model=XYZ

[0882] Online Store C API: GET https: / / api.storeC.com / products?brand=BrandABC&model=XYZ

[0883] Step 3: Analyze the information

[0884] The server analyzes the price, stock status, and shipping information collected from each sales site, calculates the total price of the product, and identifies the cheapest product based on the total price (product price + shipping).

[0885] Input: Price, stock status, shipping information for each sales site

[0886] Data processing: Calculate the total price by adding up the price and shipping fee, and identify the lowest price

[0887] Output: Cheapest seller information (price, total price, store name, link, etc.)

[0888] Specific behavior:

[0889] Calculate the total amount based on the data retrieved by the server:

[0890] Online Store A: Price: 70,000 yen, shipping: 10,000 yen → Total: 80,000 yen

[0891] Online Store B: Price: 75,000 yen, shipping: 3,000 yen → Total: 78,000 yen

[0892] Online Store C: Price 72,000 yen, shipping 7,000 yen → Total 79,000 yen

[0893] The server identifies online store B, which has the lowest price (total price: 78,000 yen).

[0894] Step 4: List and notify

[0895] The server creates a list of the lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check the list on their device and access the product purchase link.

[0896] Input: Cheapest price sales site information

[0897] Data processing: Formatting information into a list and generating notification data

[0898] Output: List sent to user's device (lowest price information)

[0899] Specific behavior:

[0900] The server lists the best prices as follows:

[0901] json

[0902] {

[0903] "store": "Online Store B",

[0904] "price": 78,000,

[0905] "link": "https: / / storeB.com / product / xyz"

[0906] }

[0907] The server sends this list to the user's device, and the user can access the purchase link.

[0908] Step 5: Monitor price fluctuations

[0909] The server periodically collects and monitors prices from each sales site based on product information registered in advance by the user, and notifies the user if the price drops.

[0910] Input: Registered product information, price information of each sales site

[0911] Data processing: Regular collection and monitoring of price information, and generation of notification data in the event of fluctuations

[0912] Output: Notification data when price changes

[0913] Specific behavior:

[0914] The server accesses each sales site's API at a specified time each day to collect price information. For example, if the price drops from 70,000 yen to 65,000 yen, that information is sent to the user's device.

[0915] (Application example 1)

[0916] 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."

[0917] In conventional online shopping systems, users often spend a great deal of time and effort finding the lowest priced products, and the lack of a seamless purchasing process can be frustrating. Furthermore, many systems lack the functionality to monitor price fluctuations and provide timely notifications, making it easy to miss opportunities to purchase at the lowest price. Therefore, there is a need for a system that can efficiently and seamlessly find the lowest priced products, quickly complete the payment process, and provide timely notifications of price fluctuations.

[0918] 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.

[0919] In this invention, the server includes means for inputting product information that a user wants, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, means for analyzing the collected information, calculating the total cost of the products, and selecting the cheapest product, means for listing the selected cheapest product information and providing it to the user, means for processing payments, and means for seamlessly executing the reception, collection, analysis, and payment of information as a series of processes. This enables users to efficiently and seamlessly find the cheapest products and pay quickly, and also allows them to avoid missing the optimal timing for purchase by receiving timely notifications of price fluctuations.

[0920] "Means for users to input product information they want" refers to an interface that allows users to input detailed information about the product they wish to acquire.

[0921] "Means for receiving product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet" refers to a communication means for collecting related data from multiple online stores on the Internet based on product information entered by a user.

[0922] "Means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product" refers to an algorithm that analyzes the collected data, calculates the total price by adding the product price and shipping costs, and selects the cheapest option.

[0923] "Means for listing the selected lowest priced product information and providing it to the user" refers to a component that organizes the information on the lowest priced products based on the analysis results, displays it as a list, and provides it to the user.

[0924] "Means for processing payments and for seamlessly receiving, collecting, analyzing information, and processing payments as a series of processes" refers to the overall system functions for carrying out payment procedures to purchase selected products, and for consistently and seamlessly collecting, analyzing information, and processing payments.

[0925] "Means to sum product prices and shipping costs" refers to a component that has the logic to calculate the total by adding up the product prices and shipping costs collected from the online store.

[0926] "A means of periodically checking price fluctuations based on product information registered by the user and notifying the user when the price drops" refers to a function that periodically checks the prices of products registered by the user in advance and notifies the user in real time when the price drops.

[0927] This invention is an electronic payment system that enables a user to purchase a desired product at the lowest price, and is realized by the following configuration.

[0928] Overall system configuration

[0929] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores that collect information. Users enter information about the products they want into their terminal and send it from the terminal to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from online stores. It identifies the products with the lowest prices, lists this information, and sends it to the terminal. It also provides a function to monitor daily price fluctuations and notify users when prices drop. Finally, it supports users so that they can smoothly complete payment at the store with the lowest price.

[0930] Program processing description

[0931] Enter and submit product information

[0932] The user inputs information about the product they want through the terminal interface. For example, they enter detailed information about a "laptop computer" (such as brand, model, and specifications) into a form, and the information is sent to the server.

[0933] Information gathering

[0934] Based on the received product information, the server accesses multiple online stores to collect information such as the price, stock status, shipping costs, etc. This process uses Python's requests library to obtain data from the Internet via API.

[0935] Analysis of information

[0936] The server analyzes all the collected information and calculates the total price of each online store, adding up the product price and shipping costs. It then compares the products and finds the cheapest option, using a data analysis library (e.g., Pandas or NumPy).

[0937] Listing and Notification

[0938] The server creates a list of the selected lowest priced products (price, store name, link, etc.) and provides the list to the user's device. The user can check the list and purchase the product from the specified link. This includes a notification system with a user interface (UI), such as email or in-app notifications.

[0939] Payment Processing

[0940] When the user decides to purchase from the store with the lowest price, the server executes the procedure for payment processing. For this, the payment API is used to securely send the user's credit card information, etc. A payment completion notification is sent to the user, and the system updates the purchase history.

[0941] Monitoring price fluctuations

[0942] The server periodically collects and monitors the price of a product from the online store based on the product information registered by the user in advance. If the price drops, the server notifies the device. For example, if the price of the "Laptop XYZ Model" registered by the user drops, the device will receive a notification such as "The price of Laptop XYZ Model has dropped: The current lowest price is 70,000 yen."

[0943] Examples of concrete examples and prompts

[0944] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the prices, and sends that information to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0945] As a result, this system allows users to efficiently and seamlessly find the lowest priced products and quickly complete payment.

[0946] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0947] Step 1:

[0948] The user uses a device to input information about the product they want, specifically details such as "laptop XYZ model" (brand, model, specs, etc.) into the device's interface, and the information is sent to the server. The input product information is converted into an API request format and sent to the server.

[0949] Step 2:

[0950] Based on the received product information, the server accesses multiple online stores on the Internet and collects information such as product price, stock status, and shipping costs. The server uses the Python requests library to request product information from the API of each online store and receives data in JSON format. The input is product information, and the output is the product data obtained from each online store.

[0951] Step 3:

[0952] The server analyzes all the collected information and calculates the total product price (price + shipping cost). Specifically, it uses data analysis libraries such as Pandas and NumPy to add up the product price and shipping cost for each online store and calculate the total price. The input is the product data collected from each online store, and the output is the analyzed data including the total price.

[0953] Step 4:

[0954] The server identifies the cheapest products based on the analysis results and lists the information. The lowest price is calculated using logic that compares all total prices and identifies the cheapest one. The input is the analysis data including the total price, and the output is a list of the cheapest products.

[0955] Step 5:

[0956] The server provides the selected cheapest product information to the user's device. Specifically, it sends a notification to the user's device, displaying details of the cheapest product, the store name, a purchase link, etc. The input is a list of cheapest product information, and the output is a notification and link displayed on the user's device.

[0957] Step 6:

[0958] The user uses the device to purchase the cheapest product from the provided link. Once the user proceeds with the purchase, the server executes the payment process. The payment process involves calling the payment API of each online store, sending payment information, and receiving the payment result. The input is the user's payment information, and the output is a payment completion notification.

[0959] Step 7:

[0960] The server periodically monitors price fluctuations based on the product information registered by the user. For example, it uses a Python scheduling library to call the API of each online store every hour to obtain the latest price information. The input is the registered product information, and the output is the latest price information.

[0961] Step 8:

[0962] The server notifies the user when the price drops. When a price change is detected, it sends a notification to the user's device, providing the latest lowest price information. For example, it sends a notification such as "The price of laptop model XYZ has dropped: the current lowest price is 70,000 yen." The input is the latest price information, and the output is the notification to the user.

[0963] 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.

[0964] The present invention is a system for efficiently finding the lowest prices for products when a user is shopping online, and functions through communication between a server and a terminal. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions. This system is designed to provide users with an appropriate and personalized purchasing experience. Specific embodiments of this system are described below.

[0965] Overall system configuration

[0966] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores for collecting information. In addition, it incorporates an emotion engine that recognizes the user's emotions. The user enters information about the product they want into the terminal, which then sends it to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists this information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies the user when prices drop. The emotion engine recognizes the user's emotions during this process and makes appropriate product suggestions and notifications.

[0967] Program processing description

[0968] Enter and submit product information

[0969] The user enters information about the product they want into the terminal. For example, they enter detailed information about "laptop model XYZ" (brand, model, specs, etc.) into a form. The terminal then sends this information to the server.

[0970] Information gathering

[0971] The server sends requests to multiple online stores based on the received product information. Based on the product information, the server crawls between online stores to collect the necessary data. For example, for a specified "laptop," it retrieves the price, stock information, and shipping costs from online store A, online store B, and online store C.

[0972] Analysis of information

[0973] The server analyzes all the collected information and calculates the total price of each product from each online store, including shipping costs. It then compares all the totals to find the cheapest option, allowing the user to purchase the product most economically.

[0974] Emotion Engine Operation

[0975] The emotion engine recognizes emotions from user input and selections. For example, it analyzes the user's input speed, items selected, purchase history, etc. to determine the user's current emotion. Based on this emotional information, it makes optimal product suggestions and notifies the user at the appropriate time. For example, if it determines that the user is in a hurry, it will prioritize displaying a list of products that can be delivered immediately.

[0976] Listing and Notification

[0977] The server creates a list of the selected lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check this list and purchase the product from the specified link. The emotion engine also improves the user experience by notifying users of the lowest priced products at the appropriate time.

[0978] Monitoring price fluctuations

[0979] The server periodically collects and monitors the price of a product from online stores based on the product information registered by the user in advance. If the price drops, the server notifies the user of the latest lowest price information. The emotion engine also participates in this notification, providing personalized notifications that take into account the user's current emotional state.

[0980] Specific examples

[0981] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[0982] In this way, the system of the present invention is designed to help users efficiently and effectively find and purchase products at the lowest prices, and by combining it with an emotion engine, it provides users with a personalized purchasing experience.

[0983] The processing flow will be explained below.

[0984] Step 1:

[0985] The user enters product information into the terminal. For example, they enter a specific product name, model number, specifications, etc., such as "laptop XYZ model," into the form. This allows the system to retrieve the product information they are searching for.

[0986] Step 2:

[0987] The terminal sends the entered product information to the server, which then prepares to start processing based on the received information.

[0988] Step 3:

[0989] A server sends a search request to multiple online stores, including keywords such as product name, model number, etc. For example, a request for "laptop model XYZ" is sent to online store A, online store B, and online store C.

[0990] Step 4:

[0991] The server receives data returned from the online stores, including the price, stock status, shipping costs, etc. For example, online store A may return "price 80,000 yen, shipping cost 500 yen," while online store B may return "price 78,000 yen, shipping cost free."

[0992] Step 5:

[0993] The server analyzes the collected data and calculates the total price for each item. For example, the total price for online store A is calculated as 80,500 yen, and the total price for online store B is calculated as 78,000 yen.

[0994] Step 6:

[0995] The server compares the total prices and selects the product with the lowest total price. In this case, it determines that the product with the lowest total price of 78,000 yen from Online Store B is the cheapest.

[0996] Step 7:

[0997] The server creates a list of the lowest priced products (price, store name, purchase link, etc.). For example, it creates a list like "Laptop XYZ model, price 78,000 yen, store B, link [purchase page]."

[0998] Step 8:

[0999] The server sends the generated list to the terminal, allowing the user to obtain the latest lowest price information.

[1000] Step 9:

[1001] The device displays the list to the user, who can then review the list and click a link to the purchase page.

[1002] Step 10:

[1003] The user clicks on the link and is taken to the designated online store's purchase page, where they can purchase the product at the most economical price.

[1004] Step 11:

[1005] The emotion engine recognizes emotions from user input and selections. For example, if the user is typing in a hurry, the emotion engine will detect "impatience" and respond appropriately.

[1006] Step 12:

[1007] The emotion engine makes optimal product suggestions based on the user's emotions. For example, if it determines that the user is in a hurry, it will suggest products that can be delivered immediately.

[1008] Step 13:

[1009] The emotion engine will notify you at the right time, for example, when the price drops or when you are feeling relaxed, taking into account the user's emotional state.

[1010] Step 14:

[1011] The server periodically checks price fluctuations, and when the price drops, it works with the emotion engine to send a notification to the user. The emotion engine takes into account the user's current emotions and adjusts the appropriate notification content and timing.

[1012] In this way, the system of the present invention provides users with an optimal purchasing experience by seamlessly collecting product information, making optimal suggestions, and providing personalized notifications based on emotions.

[1013] Example 2

[1014] 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."

[1015] When consumers shop online, it is extremely time-consuming to check numerous e-commerce sites individually to find the lowest priced product. Furthermore, as user needs become more diverse, it is important not only to simply offer the lowest priced product, but also to suggest products that reflect the user's emotions and circumstances. Furthermore, monitoring price fluctuations even after purchase and notifying users when prices drop is necessary to improve user satisfaction.

[1016] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting product information desired by the user, a means for receiving the product information and collecting information such as price, stock status, and shipping fee from multiple e-commerce sites on a communication network, a means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product, a means for listing the selected cheapest product information and providing it to the user, and a means for recognizing the user's emotional state and suggesting products or notifying them based on the user's emotion. This enables the user to efficiently and quickly find the cheapest products, providing a personalized shopping experience.

[1017] A "user" is a person who uses the system to shop online.

[1018] "Product information" refers to detailed data such as the brand, model, and specifications of the product that the user wishes to purchase.

[1019] "Communications Network" means the infrastructure for carrying the Internet and other data communications.

[1020] "E-commerce site" refers to a website or online marketplace that sells products over the Internet.

[1021] "Price" refers to the selling price of the Product.

[1022] "Inventory status" refers to whether a particular item is available for sale and in what quantity.

[1023] "Shipping Fee" refers to the shipping fee incurred when delivering a product to a purchaser.

[1024] "Means of collection" refers to the process or technology by which the server obtains the necessary information from multiple e-commerce sites.

[1025] "Analytical methods" refers to the algorithms or methods used to examine the collected data and identify the lowest prices.

[1026] "Total" refers to the total price of the product and shipping fee.

[1027] "Means of selection" refers to the process of choosing the cheapest option from multiple options.

[1028] "Listing methods" refers to methods for organizing selected information and presenting it in a format that is easy for users to understand.

[1029] "Means of providing" refers to the process of presenting the listed information to the user.

[1030] "Emotional state" refers to a user's current mental or emotional state.

[1031] "Means for making suggestions and notifications based on emotions" refers to algorithms and technologies that analyze users' emotions and make product suggestions and notifications accordingly.

[1032] This invention is a system that allows users to efficiently find the lowest priced products when shopping online. This system is primarily composed of a terminal used by the user, a server that collects and analyzes information, and multiple e-commerce sites that provide data. It also incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions.

[1033] Overall system configuration

[1034] The user inputs the desired product information into the terminal, for example, "laptop XYZ model," including detailed information such as brand, model, and specifications. The terminal then sends this input information to the server.

[1035] Based on the received product information, the server uses programming languages ​​such as Python or Java to collect the necessary data from multiple e-commerce sites. Specifically, it uses scraping tools (e.g., BeautifulSoup or Selenium) and APIs to obtain the price, stock information, and shipping costs of the specified product. For example, it collects price information from online store A, online store B, and online store C.

[1036] The server analyzes all the collected information and calculates the total price by adding the product price and shipping costs from each e-commerce site. The collected data is stored in a data frame using Python's pandas, and an algorithm is run to find the lowest price by adding a column for the total price.

[1037] The emotion engine recognizes emotions from user input and selection history. For example, it analyzes the user's input speed, click patterns, and past purchase history to determine the user's current emotion using NLP (natural language processing) libraries and machine learning models (e.g., scikit-learn and TensorFlow). If the user is in a hurry, it can prioritize a list of products that can be delivered immediately.

[1038] The server selects the lowest priced products and lists them using an HTML template engine (e.g., Jinja2). This list is sent to the user's device, where the user can view the information and purchase the products from the specified link.

[1039] The server periodically collects price fluctuations for products registered by the user from online stores and notifies the device when the price drops. This process is scheduled periodically using a Cron job or shell script. The emotion engine also participates in notifications, providing personalized notifications that take into account the user's current emotional state.

[1040] Specific examples

[1041] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to a server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple e-commerce sites. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[1042] Prompt Sentence Examples

[1043] Here are some example prompts to input to a generative AI model:

[1044] 1. "I would like to develop an online shopping system. The user inputs information about the product they want, and based on that information, the system retrieves information about the lowest prices from multiple online stores. I would also like to incorporate an emotion recognition function so that the system can suggest appropriate products based on the user's emotions. Please explain the implementation of this system and the specific processing method."

[1045] 2. "I'm designing a system to find the lowest price when a user purchases a smartphone. I'd also like to use an emotion engine to suggest products based on the user's emotions. Please explain the overall flow of this system and the specific processing steps."

[1046] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1047] Step 1:

[1048] A user enters information about the product they want into a device. Specifically, they enter details about the brand, model, specs, etc. of "laptop XYZ model" into a web form on the device. The entered data is converted into JSON format and prepared for further processing. The input data is detailed information about the product, and the output is structured data in JSON format.

[1049] Step 2:

[1050] The terminal sends the product information entered by the user to the server. Specifically, it uses an HTTP POST request to send the product information data to the server's endpoint. At this time, the data is sent along with the appropriate HTTP headers. The input is the product information in JSON format, and the output is a success message sent to the server.

[1051] Step 3:

[1052] The server sends requests to multiple e-commerce sites based on the received product information. Specifically, it uses a Python scraping tool (e.g., BeautifulSoup or Selenium) to collect product data (price, stock, shipping costs) from each site. The input is detailed product information in JSON format, and the output is the raw data obtained from each site.

[1053] Step 4:

[1054] The server analyzes all the collected information and calculates the total price of the items. Specifically, it uses the Python pandas library to store the information in a data frame and runs an algorithm to calculate the total price by adding up the price and shipping. The input is a data frame of raw data, and the output is a data frame with the calculated total price.

[1055] Step 5:

[1056] The server selects the cheapest product from the data analysis results. Using the Python standard library, it runs an algorithm to select the row with the lowest value in the total price column. The input is a data frame with the calculated total price, and the output is the information about the cheapest product.

[1057] Step 6:

[1058] The server lists the selected cheapest products. Specifically, it uses an HTML template engine (e.g., Jinja2) to generate a visually organized list format HTML. The input is the cheapest product information, and the output is the HTML list data.

[1059] Step 7:

[1060] The server sends the generated list to the terminal. Specifically, it returns HTML data to the terminal as an HTTP response or sends it in real time using WebSocket. The input is the list HTML data, and the output is a notification message to the user terminal.

[1061] Step 8:

[1062] The emotion engine recognizes the user's emotions and provides optimal product suggestions and notifications. Specifically, it uses NLP libraries and machine learning models (e.g., scikit-learn and TensorFlow) to analyze the user's input speed and past selection data and cluster emotions. The input is user behavior data, and the output is emotion labels and notifications based on them.

[1063] Step 9:

[1064] The server periodically monitors price fluctuations based on product information registered in advance by the user. Specifically, it periodically runs a data collection script using a Cron job or shell script, and notifies the user if the price drops. The input is the product information registered by the user and current price information, and the output is a notification that a price change has been detected.

[1065] (Application example 2)

[1066] 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."

[1067] In conventional online shopping, users have to compare products from multiple online stores to find the cheapest price, which is time-consuming and inefficient. Furthermore, personalized information is not provided based on the user's emotions or circumstances, making it difficult to achieve a satisfying shopping experience. The present invention aims to solve these problems and provide users with an efficient and personalized shopping experience.

[1068] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1069] In this invention, the server includes means for inputting product information desired by the user, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, means for listing the selected cheapest product information and providing it to the user, means for recognizing the user's emotions and making optimal product suggestions and notifications based on the recognized emotions, and means for evaluating the reliability of the collected information and filtering the product information based on the evaluation results. This allows the user to not only efficiently find the cheapest products, but also receive appropriate product suggestions and notifications according to their emotional state.

[1070] The "means for inputting information about a product desired by the user" is an interface for inputting detailed information about a product that the user wishes to purchase.

[1071] "Means for receiving product information and collecting information such as price, stock status, and shipping charges from multiple online stores on the Internet" refers to a function that automatically collects data such as related price, stock status, and shipping charges from multiple online stores on the Internet based on product information entered by the user.

[1072] "Means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product" refers to algorithms and procedures for analyzing the collected data to calculate the total price of the products and identifying the cheapest product from among them.

[1073] The "means of listing the selected lowest priced product information and providing it to the user" is a function that organizes the lowest priced product information selected through analysis and displays it so that the user can easily check it.

[1074] "Means for recognizing a user's emotions and making optimal product suggestions and notifications based on the recognized emotions" refers to a system that evaluates a user's emotions in real time and generates appropriate product suggestions and notifications according to that state.

[1075] "Means for evaluating the reliability of collected information and filtering product information based on the evaluation results" refers to a function that evaluates the accuracy and reliability of information obtained from each online store and eliminates inaccurate information based on the evaluation results.

[1076] "The total amount calculation means is a means for adding up the product prices and shipping costs" refers to a system for adding up the product prices and shipping costs collected from each online store to calculate the total purchase cost.

[1077] "Means of periodically checking price fluctuations and notifying users when prices drop" refers to a system that periodically monitors the prices of products registered by users and sends notifications to users when prices drop.

[1078] This invention is a system that allows users to efficiently find the lowest prices for products when shopping online. It functions through communication between a server and a terminal. It also incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions. This system is designed to provide users with an appropriate and personalized shopping experience.

[1079] Overall system configuration

[1080] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores for collecting information. It also incorporates an emotion engine that recognizes user emotions. Users enter information about the products they want into their terminal, which then sends the information to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists this information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies the user when prices drop. The emotion engine recognizes the user's emotions during this process and makes appropriate product suggestions and notifications.

[1081] Program processing description

[1082] Hardware and software used

[1083] The server uses a server machine equipped with a high-performance processor and sufficient storage capacity. A Python program is used to collect information and perform the necessary data analysis. The emotion engine uses a pre-trained generative AI model using Keras. The user's device is a smartphone or personal computer, which communicates with the server via an internet connection.

[1084] Data processing and calculation

[1085] When the server receives the product information sent by the user, it accesses multiple online stores on the Internet and scrapes information such as price, stock status, and shipping costs. The data is analyzed using libraries such as BeautifulSoup. The collected data is evaluated for accuracy and reliability, and inaccurate data is filtered out. Next, the product price and shipping costs collected from each store are added together to calculate the total price, and the cheapest product is identified. The results are sent as a list to the user's device.

[1086] Meanwhile, the emotion engine collects user input information and behavioral data and analyzes the user's emotional state using a generative AI model. For example, input speed, selections, and past purchase history are analyzed to estimate the user's current emotional state. Based on this information, product suggestions and notifications that best fit the user's emotions are generated.

[1087] Specific examples

[1088] For example, if a user wants to buy the latest smartphone, they enter the information for "Smartphone Model XYZ" into their device and press the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone Model XYZ" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of this information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone Model XYZ" at the lowest price.

[1089] Example prompt for a generative AI model:

[1090] Provide user data: {typing_speed: 45, recent_clicks: ["home", "search", "product page"]}. A user is searching for "Smartphone XYZ model". Recognize the user's sentiment, gather information on the cheapest online store, and generate an appropriate notification message.

[1091] In this way, the system of the present invention not only enables users to efficiently find the cheapest products, but also allows users to receive appropriate product suggestions and notifications according to their emotional state.

[1092] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1093] Step 1:

[1094] The user inputs information about the product they want into the terminal. The input information is detailed information such as "smartphone XYZ model."

[1095] input:

[1096] Product details entered by the user.

[1097] output:

[1098] The input product information is sent from the terminal to the server.

[1099] Data processing / calculation:

[1100] The terminal prepares the entered text data for transmission to the server.

[1101] Step 2:

[1102] The server sends requests to a plurality of online stores based on the product information received from the terminal.

[1103] input:

[1104] Product information sent from the device.

[1105] output:

[1106] Pricing, stock, shipping information, etc. obtained from online stores.

[1107] Data processing / calculation:

[1108] The server uses the specified keywords to gather the necessary information using the online store's API and web scraping techniques, accessing web pages using Python requests and parsing the HTML data using BeautifulSoup.

[1109] Step 3:

[1110] The server analyzes the collected information, calculates the total price of the items (price + shipping fee), and selects the cheapest item.

[1111] input:

[1112] Pricing, stock, shipping information, etc. obtained from online stores.

[1113] output:

[1114] Information on the total price and lowest prices of products at each online store.

[1115] Data processing / calculation:

[1116] The server calculates a total price for each item by adding up the price and shipping costs, then compares the calculated prices to identify the cheapest item.

[1117] Step 4:

[1118] The server creates a list of the lowest priced products selected and provides it to the user.

[1119] input:

[1120] Lowest price product information, total price.

[1121] output:

[1122] User-viewable list of lowest priced products.

[1123] Data processing / calculation:

[1124] The server formats the selected lowest priced product information into a list format and converts it into a data format for transmission to the user's terminal.

[1125] Step 5:

[1126] The emotion engine analyzes the user's input information and behavioral data to recognize emotions.

[1127] input:

[1128] Behavioral data such as user typing speed, selections, and past purchases.

[1129] output:

[1130] The user's emotional state.

[1131] Data processing / calculation:

[1132] The emotion engine uses a generative AI model (pre-trained using Keras) to predict user emotions from input data.

[1133] Step 6:

[1134] The server then makes optimal product suggestions and notifications based on the recognized emotions.

[1135] input:

[1136] User emotional state, lowest price product information.

[1137] output:

[1138] Personalized notification messages.

[1139] Data processing / calculation:

[1140] The server generates appropriate messages and notifications based on the user's emotional state. For example, a relaxed user might receive a message like, "If you're not in a hurry, this product is perfect for you!"

[1141] Step 7:

[1142] The server monitors price fluctuations and notifies the user if the price drops.

[1143] input:

[1144] Registered product information and historical price data.

[1145] output:

[1146] Get notified when the price drops.

[1147] Data processing / calculation:

[1148] The server periodically retrieves price data for each product and compares it with previous data to detect price fluctuations. If the price drops, the server notifies the user.

[1149] 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.

[1150] 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.

[1151] 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.

[1152] [Fourth embodiment]

[1153] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1154] 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.

[1155] 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).

[1156] 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.

[1157] 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.

[1158] 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).

[1159] 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.

[1160] 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.

[1161] 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.

[1162] 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.

[1163] 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.

[1164] 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.

[1165] 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."

[1166] The present invention is a system for efficiently finding the lowest price for a product when a user is shopping online, and functions through communication between a server and a terminal. Specific embodiments of this system will be described below.

[1167] Overall system configuration

[1168] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores that collect information. Users enter information about the products they want into their terminal, which then sends it to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists that information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies users when prices drop.

[1169] Program processing description

[1170] Enter and submit product information

[1171] The user enters information about the product they want into the terminal. For example, they enter detailed information about a "laptop computer" (brand, model, specs, etc.) into a form. The terminal then sends this information to the server.

[1172] Information gathering

[1173] Based on the received product information, the server accesses multiple online stores to collect information on the product's price, stock status, shipping costs, etc. For example, for a specified "laptop computer," the server obtains the price, stock status, and shipping costs from online store A, online store B, and online store C.

[1174] Analysis of information

[1175] The server analyzes all the collected information and calculates the total price of each product from each online store, including shipping costs. It then compares all the totals to find the cheapest option, allowing the user to purchase the product most economically.

[1176] Listing and Notification

[1177] The server creates a list of the lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check the list and purchase the product from the specified link.

[1178] Monitoring price fluctuations

[1179] The server periodically collects and monitors the prices of products from online stores based on the product information registered by the user in advance. If the price drops, the server notifies the device so that the user can obtain the latest lowest price information.

[1180] Specific examples

[1181] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the prices, and sends that information to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[1182] Thus, the system of the present invention is designed to help users efficiently and effectively find and purchase products at the lowest prices.

[1183] The processing flow will be explained below.

[1184] Step 1:

[1185] The user enters product information into the terminal, for example, "laptop XYZ model." This prepares the data for the next step.

[1186] Step 2:

[1187] The terminal sends the product information entered by the user to the server, including the product name, model number, specifications, etc.

[1188] Step 3:

[1189] The server sends requests to multiple online stores based on the received product information, and then crawls between the online stores to collect the necessary data.

[1190] Step 4:

[1191] The server analyzes the data collected from each online store. This data includes price, stock status, shipping costs, etc. For example, online store A may retrieve data such as "price: 80,000 yen, shipping cost: 500 yen," and online store B may retrieve data such as "price: 78,000 yen, shipping cost: free."

[1192] Step 5:

[1193] The server calculates the total amount based on the collected data. For example, the total amount for online store A is calculated as 80,500 yen, and the total amount for online store B is calculated as 78,000 yen.

[1194] Step 6:

[1195] The server compares the calculated totals and selects the product with the lowest total price. In this case, online store B's total price of 78,000 yen is the cheapest.

[1196] Step 7:

[1197] The server creates a list of the cheapest products. This list includes the product name, lowest price, store name, and purchase link. For example, it might be listed in the format "laptop XYZ model, price 78,000 yen, store B, link [purchase page]."

[1198] Step 8:

[1199] The server sends the generated list to the terminal, allowing the user to obtain the latest lowest price information.

[1200] Step 9:

[1201] The device displays the list to the user, who can then review the list and click a link to the purchase page.

[1202] Step 10:

[1203] The user clicks on the link and is taken to the designated online store's purchase page, where they can purchase the product at the most economical price.

[1204] The above are the specific processing steps that a user takes from obtaining information about the cheapest product to making a purchase.

[1205] Example 1

[1206] 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."

[1207] In online shopping, users often have to compare products across multiple sales sites to find the best price. Furthermore, product prices often fluctuate, making it difficult to obtain the lowest price information in a timely manner.

[1208] 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.

[1209] In this invention, the server includes means for users to input product information they want, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple sales sites on the Internet, means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, means for listing the selected cheapest product information and providing it to the user, and means for monitoring daily price fluctuations and notifying the user when prices drop, thereby enabling users to efficiently and reliably find and purchase the cheapest products.

[1210] "User" means any individual or legal entity that uses the System to conduct online shopping.

[1211] "Product information" refers to data including detailed information such as the brand, model, and specifications of the product that the user wishes to purchase.

[1212] "Sales Site" refers to any online platform that sells products over the Internet.

[1213] "Price" refers to the purchase price of the Product displayed on the Sales Site.

[1214] "Stock status" refers to information indicating whether or not a product is in stock at a sales site and the quantity.

[1215] "Shipping Costs" refers to any additional costs incurred in shipping the Product.

[1216] "Total amount" refers to the total amount of the product price and shipping fee.

[1217] "Lowest price" refers to the lowest total price of a product across multiple sales sites.

[1218] "Listing" refers to organizing collected and analyzed information and displaying it in a list format.

[1219] "Price fluctuation monitoring" refers to the process of regularly collecting and monitoring product price information and notifying you if there are any fluctuations.

[1220] This invention is a system that allows users to efficiently find the lowest prices for products when shopping online, and it functions through communication between a server and a terminal. It consists of a terminal used by the user, a server that performs the central processing, and multiple sales sites that collect information.

[1221] The user enters the product information they want into the terminal. This product information might include, for example, "laptop, brand ABC, model XYZ, 16GB RAM, 512GB SSD." The terminal converts this information into a data format such as JSON and sends it to the server as an HTTP POST request. When the user enters information into the form and presses the submit button, the input data is sent to the server.

[1222] Based on the received product information, the server sends requests to multiple sales site APIs to obtain information such as the price, stock status, and shipping costs of the target product. For example, the server sends HTTP GET requests to the API endpoints of online stores A, B, and C to collect real-time price information. The obtained information is stored in a database and used for further analysis.

[1223] The server analyzes the price, inventory status, and shipping information collected from each sales site and calculates the total price (product price + shipping). To ensure the most economical product purchase, the server compares all the total prices and identifies the product with the lowest price. For example, if online store A has a total price of 80,000 yen, online store B has a total price of 78,000 yen, and online store C has a total price of 79,000 yen, the server determines that online store B has the lowest price.

[1224] The server creates a list of the cheapest products (price, store name, link, etc.) and sends the list to the user's device. The user can then check the list on their device and purchase the product from the specified link. This process allows users to efficiently find and purchase the cheapest products.

[1225] Furthermore, the server periodically collects and monitors the prices of products registered by the user from various sales sites, based on the product information. If there is a price change, the information is sent to the terminal. For example, when the price of a registered "laptop computer" drops, the information is sent to the user, allowing the user to obtain the latest lowest price information.

[1226] As a concrete example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to a server, which then collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple sales sites. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of that information, and sends it to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[1227] Example prompt sentence:

[1228] "Compare online stores to find the cheapest deal on the latest smartphone model XYZ. Collect pricing, availability, and shipping information from each store and tell me the cheapest option."

[1229] In this way, the system of the present invention helps users efficiently and reliably find and purchase products at the lowest prices.

[1230] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1231] Step 1: Enter product information

[1232] The user enters details of the product they want into the terminal, such as "laptop, brand ABC, model XYZ, 16GB RAM, 512GB SSD." The terminal receives the user's input, formats the information as JSON data, and sends it to the server as an HTTP POST request.

[1233] Input: Product information entered by the user (brand, model, specifications, etc.)

[1234] Data processing: Convert product information into JSON format

[1235] Output: HTTP POST request with product information in JSON format

[1236] Specific behavior:

[1237] The user enters "Brand ABC, Model XYZ, 16GB RAM, 512GB SSD" into the form and presses the submit button. The device receives this information and sends the following JSON data to the server:

[1238] json

[1239] {

[1240] "category": "laptop",

[1241] "brand": "Brand ABC",

[1242] "model": "XYZ",

[1243] "specs": {

[1244] "RAM": "16GB",

[1245] "storage": "512GB SSD"

[1246] }

[1247] }

[1248] Step 2: Gather information

[1249] Based on the received product information, the server sends requests to multiple sales site APIs to obtain information such as the price, stock status, shipping costs, etc. It sends HTTP GET requests to each sales site to collect real-time data.

[1250] Input: Product information in JSON format

[1251] Data processing: Generating and sending HTTP GET requests to each sales site

[1252] Output: Price, stock status, and shipping information for each sales site (JSON format)

[1253] Specific behavior:

[1254] Your server sends an API request to your online store like this:

[1255] Online Store A's API: GET https: / / api.storeA.com / products?brand=BrandABC&model=XYZ

[1256] Online Store B's API: GET https: / / api.storeB.com / products?brand=BrandABC&model=XYZ

[1257] Online Store C API: GET https: / / api.storeC.com / products?brand=BrandABC&model=XYZ

[1258] Step 3: Analyze the information

[1259] The server analyzes the price, stock status, and shipping information collected from each sales site, calculates the total price of the product, and identifies the cheapest product based on the total price (product price + shipping).

[1260] Input: Price, stock status, shipping information for each sales site

[1261] Data processing: Calculate the total price by adding up the price and shipping fee, and identify the lowest price

[1262] Output: Cheapest seller information (price, total price, store name, link, etc.)

[1263] Specific behavior:

[1264] Calculate the total amount based on the data retrieved by the server:

[1265] Online Store A: Price: 70,000 yen, shipping: 10,000 yen → Total: 80,000 yen

[1266] Online Store B: Price: 75,000 yen, shipping: 3,000 yen → Total: 78,000 yen

[1267] Online Store C: Price 72,000 yen, shipping 7,000 yen → Total 79,000 yen

[1268] The server identifies online store B, which has the lowest price (total price: 78,000 yen).

[1269] Step 4: List and notify

[1270] The server creates a list of the lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check the list on their device and access the product purchase link.

[1271] Input: Cheapest price sales site information

[1272] Data processing: Formatting information into a list and generating notification data

[1273] Output: List sent to user's device (lowest price information)

[1274] Specific behavior:

[1275] The server lists the best prices as follows:

[1276] json

[1277] {

[1278] "store": "Online Store B",

[1279] "price": 78,000,

[1280] "link": "https: / / storeB.com / product / xyz"

[1281] }

[1282] The server sends this list to the user's device, and the user can access the purchase link.

[1283] Step 5: Monitor price fluctuations

[1284] The server periodically collects and monitors prices from each sales site based on product information registered in advance by the user, and notifies the user if the price drops.

[1285] Input: Registered product information, price information of each sales site

[1286] Data processing: Regular collection and monitoring of price information, and generation of notification data in the event of fluctuations

[1287] Output: Notification data when price changes

[1288] Specific behavior:

[1289] The server accesses each sales site's API at a specified time each day to collect price information. For example, if the price drops from 70,000 yen to 65,000 yen, that information is sent to the user's device.

[1290] (Application example 1)

[1291] 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."

[1292] In conventional online shopping systems, users often spend a great deal of time and effort finding the lowest priced products, and the lack of a seamless purchasing process can be frustrating. Furthermore, many systems lack the functionality to monitor price fluctuations and provide timely notifications, making it easy to miss opportunities to purchase at the lowest price. Therefore, there is a need for a system that can efficiently and seamlessly find the lowest priced products, quickly complete the payment process, and provide timely notifications of price fluctuations.

[1293] 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.

[1294] In this invention, the server includes means for inputting product information that a user wants, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, means for analyzing the collected information, calculating the total cost of the products, and selecting the cheapest product, means for listing the selected cheapest product information and providing it to the user, means for processing payments, and means for seamlessly executing the reception, collection, analysis, and payment of information as a series of processes. This enables users to efficiently and seamlessly find the cheapest products and pay quickly, and also allows them to avoid missing the optimal timing for purchase by receiving timely notifications of price fluctuations.

[1295] "Means for users to input product information they want" refers to an interface that allows users to input detailed information about the product they wish to acquire.

[1296] "Means for receiving product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet" refers to a communication means for collecting related data from multiple online stores on the Internet based on product information entered by a user.

[1297] "Means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product" refers to an algorithm that analyzes the collected data, calculates the total price by adding the product price and shipping costs, and selects the cheapest option.

[1298] "Means for listing the selected lowest priced product information and providing it to the user" refers to a component that organizes the information on the lowest priced products based on the analysis results, displays it as a list, and provides it to the user.

[1299] "Means for processing payments and for seamlessly receiving, collecting, analyzing information, and processing payments as a series of processes" refers to the overall system functions for carrying out payment procedures to purchase selected products, and for consistently and seamlessly collecting, analyzing information, and processing payments.

[1300] "Means to sum product prices and shipping costs" refers to a component that has the logic to calculate the total by adding up the product prices and shipping costs collected from the online store.

[1301] "A means of periodically checking price fluctuations based on product information registered by the user and notifying the user when the price drops" refers to a function that periodically checks the prices of products registered by the user in advance and notifies the user in real time when the price drops.

[1302] This invention is an electronic payment system that enables a user to purchase a desired product at the lowest price, and is realized by the following configuration.

[1303] Overall system configuration

[1304] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores that collect information. Users enter information about the products they want into their terminal and send it from the terminal to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from online stores. It identifies the products with the lowest prices, lists this information, and sends it to the terminal. It also provides a function to monitor daily price fluctuations and notify users when prices drop. Finally, it supports users so that they can smoothly complete payment at the store with the lowest price.

[1305] Program processing description

[1306] Enter and submit product information

[1307] The user inputs information about the product they want through the terminal interface. For example, they enter detailed information about a "laptop computer" (such as brand, model, and specifications) into a form, and the information is sent to the server.

[1308] Information gathering

[1309] Based on the received product information, the server accesses multiple online stores to collect information such as the price, stock status, shipping costs, etc. This process uses Python's requests library to obtain data from the Internet via API.

[1310] Analysis of information

[1311] The server analyzes all the collected information and calculates the total price of each online store, adding up the product price and shipping costs. It then compares the products and finds the cheapest option, using a data analysis library (e.g., Pandas or NumPy).

[1312] Listing and Notification

[1313] The server creates a list of the selected lowest priced products (price, store name, link, etc.) and provides the list to the user's device. The user can check the list and purchase the product from the specified link. This includes a notification system with a user interface (UI), such as email or in-app notifications.

[1314] Payment Processing

[1315] When the user decides to purchase from the store with the lowest price, the server executes the procedure for payment processing. For this, the payment API is used to securely send the user's credit card information, etc. A payment completion notification is sent to the user, and the system updates the purchase history.

[1316] Monitoring price fluctuations

[1317] The server periodically collects and monitors the price of a product from the online store based on the product information registered by the user in advance. If the price drops, the server notifies the device. For example, if the price of the "Laptop XYZ Model" registered by the user drops, the device will receive a notification such as "The price of Laptop XYZ Model has dropped: The current lowest price is 70,000 yen."

[1318] Examples of concrete examples and prompts

[1319] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the prices, and sends that information to the user's device. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[1320] As a result, this system allows users to efficiently and seamlessly find the lowest priced products and quickly complete payment.

[1321] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1322] Step 1:

[1323] The user uses a device to input information about the product they want, specifically details such as "laptop XYZ model" (brand, model, specs, etc.) into the device's interface, and the information is sent to the server. The input product information is converted into an API request format and sent to the server.

[1324] Step 2:

[1325] Based on the received product information, the server accesses multiple online stores on the Internet and collects information such as product price, stock status, and shipping costs. The server uses the Python requests library to request product information from the API of each online store and receives data in JSON format. The input is product information, and the output is the product data obtained from each online store.

[1326] Step 3:

[1327] The server analyzes all the collected information and calculates the total product price (price + shipping cost). Specifically, it uses data analysis libraries such as Pandas and NumPy to add up the product price and shipping cost for each online store and calculate the total price. The input is the product data collected from each online store, and the output is the analyzed data including the total price.

[1328] Step 4:

[1329] The server identifies the cheapest products based on the analysis results and lists the information. The lowest price is calculated using logic that compares all total prices and identifies the cheapest one. The input is the analysis data including the total price, and the output is a list of the cheapest products.

[1330] Step 5:

[1331] The server provides the selected cheapest product information to the user's device. Specifically, it sends a notification to the user's device, displaying details of the cheapest product, the store name, a purchase link, etc. The input is a list of cheapest product information, and the output is a notification and link displayed on the user's device.

[1332] Step 6:

[1333] The user uses the device to purchase the cheapest product from the provided link. Once the user proceeds with the purchase, the server executes the payment process. The payment process involves calling the payment API of each online store, sending payment information, and receiving the payment result. The input is the user's payment information, and the output is a payment completion notification.

[1334] Step 7:

[1335] The server periodically monitors price fluctuations based on the product information registered by the user. For example, it uses a Python scheduling library to call the API of each online store every hour to obtain the latest price information. The input is the registered product information, and the output is the latest price information.

[1336] Step 8:

[1337] The server notifies the user when the price drops. When a price change is detected, it sends a notification to the user's device, providing the latest lowest price information. For example, it sends a notification such as "The price of laptop model XYZ has dropped: the current lowest price is 70,000 yen." The input is the latest price information, and the output is the notification to the user.

[1338] 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.

[1339] The present invention is a system for efficiently finding the lowest prices for products when a user is shopping online, and functions through communication between a server and a terminal. Furthermore, it incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions. This system is designed to provide users with an appropriate and personalized purchasing experience. Specific embodiments of this system are described below.

[1340] Overall system configuration

[1341] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores for collecting information. In addition, it incorporates an emotion engine that recognizes the user's emotions. The user enters information about the product they want into the terminal, which then sends it to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists this information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies the user when prices drop. The emotion engine recognizes the user's emotions during this process and makes appropriate product suggestions and notifications.

[1342] Program processing description

[1343] Enter and submit product information

[1344] The user enters information about the product they want into the terminal. For example, they enter detailed information about "laptop model XYZ" (brand, model, specs, etc.) into a form. The terminal then sends this information to the server.

[1345] Information gathering

[1346] The server sends requests to multiple online stores based on the received product information. Based on the product information, the server crawls between online stores to collect the necessary data. For example, for a specified "laptop," it retrieves the price, stock information, and shipping costs from online store A, online store B, and online store C.

[1347] Analysis of information

[1348] The server analyzes all the collected information and calculates the total price of each product from each online store, including shipping costs. It then compares all the totals to find the cheapest option, allowing the user to purchase the product most economically.

[1349] Emotion Engine Operation

[1350] The emotion engine recognizes emotions from user input and selections. For example, it analyzes the user's input speed, items selected, purchase history, etc. to determine the user's current emotion. Based on this emotional information, it makes optimal product suggestions and notifies the user at the appropriate time. For example, if it determines that the user is in a hurry, it will prioritize displaying a list of products that can be delivered immediately.

[1351] Listing and Notification

[1352] The server creates a list of the selected lowest priced products (price, store name, link, etc.) and sends the list to the user's device. The user can check this list and purchase the product from the specified link. The emotion engine also improves the user experience by notifying users of the lowest priced products at the appropriate time.

[1353] Monitoring price fluctuations

[1354] The server periodically collects and monitors the price of a product from online stores based on the product information registered by the user in advance. If the price drops, the server notifies the user of the latest lowest price information. The emotion engine also participates in this notification, providing personalized notifications that take into account the user's current emotional state.

[1355] Specific examples

[1356] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[1357] In this way, the system of the present invention is designed to help users efficiently and effectively find and purchase products at the lowest prices, and by combining it with an emotion engine, it provides users with a personalized purchasing experience.

[1358] The processing flow will be explained below.

[1359] Step 1:

[1360] The user enters product information into the terminal. For example, they enter a specific product name, model number, specifications, etc., such as "laptop XYZ model," into the form. This allows the system to retrieve the product information they are searching for.

[1361] Step 2:

[1362] The terminal sends the entered product information to the server, which then prepares to start processing based on the received information.

[1363] Step 3:

[1364] A server sends a search request to multiple online stores, including keywords such as product name, model number, etc. For example, a request for "laptop model XYZ" is sent to online store A, online store B, and online store C.

[1365] Step 4:

[1366] The server receives data returned from the online stores, including the price, stock status, shipping costs, etc. For example, online store A may return "price 80,000 yen, shipping cost 500 yen," while online store B may return "price 78,000 yen, shipping cost free."

[1367] Step 5:

[1368] The server analyzes the collected data and calculates the total price for each item. For example, the total price for online store A is calculated as 80,500 yen, and the total price for online store B is calculated as 78,000 yen.

[1369] Step 6:

[1370] The server compares the total prices and selects the product with the lowest total price. In this case, it determines that the product with the lowest total price of 78,000 yen from Online Store B is the cheapest.

[1371] Step 7:

[1372] The server creates a list of the lowest priced products (price, store name, purchase link, etc.). For example, it creates a list like "Laptop XYZ model, price 78,000 yen, store B, link [purchase page]."

[1373] Step 8:

[1374] The server sends the generated list to the terminal, allowing the user to obtain the latest lowest price information.

[1375] Step 9:

[1376] The device displays the list to the user, who can then review the list and click a link to the purchase page.

[1377] Step 10:

[1378] The user clicks on the link and is taken to the designated online store's purchase page, where they can purchase the product at the most economical price.

[1379] Step 11:

[1380] The emotion engine recognizes emotions from user input and selections. For example, if the user is typing in a hurry, the emotion engine will detect "impatience" and respond appropriately.

[1381] Step 12:

[1382] The emotion engine makes optimal product suggestions based on the user's emotions. For example, if it determines that the user is in a hurry, it will suggest products that can be delivered immediately.

[1383] Step 13:

[1384] The emotion engine will notify you at the right time, for example, when the price drops or when you are feeling relaxed, taking into account the user's emotional state.

[1385] Step 14:

[1386] The server periodically checks price fluctuations, and when the price drops, it works with the emotion engine to send a notification to the user. The emotion engine takes into account the user's current emotions and adjusts the appropriate notification content and timing.

[1387] In this way, the system of the present invention provides users with an optimal purchasing experience by seamlessly collecting product information, making optimal suggestions, and providing personalized notifications based on emotions.

[1388] Example 2

[1389] 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."

[1390] When consumers shop online, it is extremely time-consuming to check numerous e-commerce sites individually to find the lowest priced product. Furthermore, as user needs become more diverse, it is important not only to simply offer the lowest priced product, but also to suggest products that reflect the user's emotions and circumstances. Furthermore, monitoring price fluctuations even after purchase and notifying users when prices drop is necessary to improve user satisfaction.

[1391] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for inputting product information desired by the user, a means for receiving the product information and collecting information such as price, stock status, and shipping fee from multiple e-commerce sites on a communication network, a means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product, a means for listing the selected cheapest product information and providing it to the user, and a means for recognizing the user's emotional state and suggesting products or notifying them based on the user's emotion. This enables the user to efficiently and quickly find the cheapest products, providing a personalized shopping experience.

[1392] A "user" is a person who uses the system to shop online.

[1393] "Product information" refers to detailed data such as the brand, model, and specifications of the product that the user wishes to purchase.

[1394] "Communications Network" means the infrastructure for carrying the Internet and other data communications.

[1395] "E-commerce site" refers to a website or online marketplace that sells products over the Internet.

[1396] "Price" refers to the selling price of the Product.

[1397] "Inventory status" refers to whether a particular item is available for sale and in what quantity.

[1398] "Shipping Fee" refers to the shipping fee incurred when delivering a product to a purchaser.

[1399] "Means of collection" refers to the process or technology by which the server obtains the necessary information from multiple e-commerce sites.

[1400] "Analytical methods" refers to the algorithms or methods used to examine the collected data and identify the lowest prices.

[1401] "Total" refers to the total price of the product and shipping fee.

[1402] "Means of selection" refers to the process of choosing the cheapest option from multiple options.

[1403] "Listing methods" refers to methods for organizing selected information and presenting it in a format that is easy for users to understand.

[1404] "Means of providing" refers to the process of presenting the listed information to the user.

[1405] "Emotional state" refers to a user's current mental or emotional state.

[1406] "Means for making suggestions and notifications based on emotions" refers to algorithms and technologies that analyze users' emotions and make product suggestions and notifications accordingly.

[1407] This invention is a system that allows users to efficiently find the lowest priced products when shopping online. This system is primarily composed of a terminal used by the user, a server that collects and analyzes information, and multiple e-commerce sites that provide data. It also incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions.

[1408] Overall system configuration

[1409] The user inputs the desired product information into the terminal, for example, "laptop XYZ model," including detailed information such as brand, model, and specifications. The terminal then sends this input information to the server.

[1410] Based on the received product information, the server uses programming languages ​​such as Python or Java to collect the necessary data from multiple e-commerce sites. Specifically, it uses scraping tools (e.g., BeautifulSoup or Selenium) and APIs to obtain the price, stock information, and shipping costs of the specified product. For example, it collects price information from online store A, online store B, and online store C.

[1411] The server analyzes all the collected information and calculates the total price by adding the product price and shipping costs from each e-commerce site. The collected data is stored in a data frame using Python's pandas, and an algorithm is run to find the lowest price by adding a column for the total price.

[1412] The emotion engine recognizes emotions from user input and selection history. For example, it analyzes the user's input speed, click patterns, and past purchase history to determine the user's current emotion using NLP (natural language processing) libraries and machine learning models (e.g., scikit-learn and TensorFlow). If the user is in a hurry, it can prioritize a list of products that can be delivered immediately.

[1413] The server selects the lowest priced products and lists them using an HTML template engine (e.g., Jinja2). This list is sent to the user's device, where the user can view the information and purchase the products from the specified link.

[1414] The server periodically collects price fluctuations for products registered by the user from online stores and notifies the device when the price drops. This process is scheduled periodically using a Cron job or shell script. The emotion engine also participates in notifications, providing personalized notifications that take into account the user's current emotional state.

[1415] Specific examples

[1416] For example, suppose a user wants to purchase the latest smartphone. The user enters information about "Smartphone XYZ Model" into their device and presses the submit button. The device sends this information to a server, which collects the price, stock status, and shipping information for "Smartphone XYZ Model" from multiple e-commerce sites. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of the information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone XYZ Model" at the lowest price.

[1417] Prompt Sentence Examples

[1418] Here are some example prompts to input to a generative AI model:

[1419] 1. "I would like to develop an online shopping system. The user inputs information about the product they want, and based on that information, the system retrieves information about the lowest prices from multiple online stores. I would also like to incorporate an emotion recognition function so that the system can suggest appropriate products based on the user's emotions. Please explain the implementation of this system and the specific processing method."

[1420] 2. "I'm designing a system to find the lowest price when a user purchases a smartphone. I'd also like to use an emotion engine to suggest products based on the user's emotions. Please explain the overall flow of this system and the specific processing steps."

[1421] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1422] Step 1:

[1423] A user enters information about the product they want into a device. Specifically, they enter details about the brand, model, specs, etc. of "laptop XYZ model" into a web form on the device. The entered data is converted into JSON format and prepared for further processing. The input data is detailed information about the product, and the output is structured data in JSON format.

[1424] Step 2:

[1425] The terminal sends the product information entered by the user to the server. Specifically, it uses an HTTP POST request to send the product information data to the server's endpoint. At this time, the data is sent along with the appropriate HTTP headers. The input is the product information in JSON format, and the output is a success message sent to the server.

[1426] Step 3:

[1427] The server sends requests to multiple e-commerce sites based on the received product information. Specifically, it uses a Python scraping tool (e.g., BeautifulSoup or Selenium) to collect product data (price, stock, shipping costs) from each site. The input is detailed product information in JSON format, and the output is the raw data obtained from each site.

[1428] Step 4:

[1429] The server analyzes all the collected information and calculates the total price of the items. Specifically, it uses the Python pandas library to store the information in a data frame and runs an algorithm to calculate the total price by adding up the price and shipping. The input is a data frame of raw data, and the output is a data frame with the calculated total price.

[1430] Step 5:

[1431] The server selects the cheapest product from the data analysis results. Using the Python standard library, it runs an algorithm to select the row with the lowest value in the total price column. The input is a data frame with the calculated total price, and the output is the information about the cheapest product.

[1432] Step 6:

[1433] The server lists the selected cheapest products. Specifically, it uses an HTML template engine (e.g., Jinja2) to generate a visually organized list format HTML. The input is the cheapest product information, and the output is the HTML list data.

[1434] Step 7:

[1435] The server sends the generated list to the terminal. Specifically, it returns HTML data to the terminal as an HTTP response or sends it in real time using WebSocket. The input is the list HTML data, and the output is a notification message to the user terminal.

[1436] Step 8:

[1437] The emotion engine recognizes the user's emotions and provides optimal product suggestions and notifications. Specifically, it uses NLP libraries and machine learning models (e.g., scikit-learn and TensorFlow) to analyze the user's input speed and past selection data and cluster emotions. The input is user behavior data, and the output is emotion labels and notifications based on them.

[1438] Step 9:

[1439] The server periodically monitors price fluctuations based on product information registered in advance by the user. Specifically, it periodically runs a data collection script using a Cron job or shell script, and notifies the user if the price drops. The input is the product information registered by the user and current price information, and the output is a notification that a price change has been detected.

[1440] (Application example 2)

[1441] 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."

[1442] In conventional online shopping, users have to compare products from multiple online stores to find the cheapest price, which is time-consuming and inefficient. Furthermore, personalized information is not provided based on the user's emotions or circumstances, making it difficult to achieve a satisfying shopping experience. The present invention aims to solve these problems and provide users with an efficient and personalized shopping experience.

[1443] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1444] In this invention, the server includes means for inputting product information desired by the user, means for receiving the product information and collecting information such as price, stock status, and shipping costs from multiple online stores on the Internet, means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products, means for listing the selected cheapest product information and providing it to the user, means for recognizing the user's emotions and making optimal product suggestions and notifications based on the recognized emotions, and means for evaluating the reliability of the collected information and filtering the product information based on the evaluation results. This allows the user to not only efficiently find the cheapest products, but also receive appropriate product suggestions and notifications according to their emotional state.

[1445] The "means for inputting information about a product desired by the user" is an interface for inputting detailed information about a product that the user wishes to purchase.

[1446] "Means for receiving product information and collecting information such as price, stock status, and shipping charges from multiple online stores on the Internet" refers to a function that automatically collects data such as related price, stock status, and shipping charges from multiple online stores on the Internet based on product information entered by the user.

[1447] "Means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest product" refers to algorithms and procedures for analyzing the collected data to calculate the total price of the products and identifying the cheapest product from among them.

[1448] The "means of listing the selected lowest priced product information and providing it to the user" is a function that organizes the lowest priced product information selected through analysis and displays it so that the user can easily check it.

[1449] "Means for recognizing a user's emotions and making optimal product suggestions and notifications based on the recognized emotions" refers to a system that evaluates a user's emotions in real time and generates appropriate product suggestions and notifications according to that state.

[1450] "Means for evaluating the reliability of collected information and filtering product information based on the evaluation results" refers to a function that evaluates the accuracy and reliability of information obtained from each online store and eliminates inaccurate information based on the evaluation results.

[1451] "The total amount calculation means is a means for adding up the product prices and shipping costs" refers to a system for adding up the product prices and shipping costs collected from each online store to calculate the total purchase cost.

[1452] "Means of periodically checking price fluctuations and notifying users when prices drop" refers to a system that periodically monitors the prices of products registered by users and sends notifications to users when prices drop.

[1453] This invention is a system that allows users to efficiently find the lowest prices for products when shopping online. It functions through communication between a server and a terminal. It also incorporates an emotion engine that recognizes the user's emotions and makes optimal product suggestions and notifications based on those emotions. This system is designed to provide users with an appropriate and personalized shopping experience.

[1454] Overall system configuration

[1455] This system consists of a terminal used by the user, a server that performs central processing, and multiple online stores for collecting information. It also incorporates an emotion engine that recognizes user emotions. Users enter information about the products they want into their terminal, which then sends the information to the server. Based on this product information, the server collects and analyzes information such as price, stock status, and shipping costs from the online stores. It identifies the cheapest products, lists this information, and sends it to the terminal. It also provides a function that monitors daily price fluctuations and notifies the user when prices drop. The emotion engine recognizes the user's emotions during this process and makes appropriate product suggestions and notifications.

[1456] Program processing description

[1457] Hardware and software used

[1458] The server uses a server machine equipped with a high-performance processor and sufficient storage capacity. A Python program is used to collect information and perform the necessary data analysis. The emotion engine uses a pre-trained generative AI model using Keras. The user's device is a smartphone or personal computer, which communicates with the server via an internet connection.

[1459] Data processing and calculation

[1460] When the server receives the product information sent by the user, it accesses multiple online stores on the Internet and scrapes information such as price, stock status, and shipping costs. The data is analyzed using libraries such as BeautifulSoup. The collected data is evaluated for accuracy and reliability, and inaccurate data is filtered out. Next, the product price and shipping costs collected from each store are added together to calculate the total price, and the cheapest product is identified. The results are sent as a list to the user's device.

[1461] Meanwhile, the emotion engine collects user input information and behavioral data and analyzes the user's emotional state using a generative AI model. For example, input speed, selections, and past purchase history are analyzed to estimate the user's current emotional state. Based on this information, product suggestions and notifications that best fit the user's emotions are generated.

[1462] Specific examples

[1463] For example, if a user wants to buy the latest smartphone, they enter the information for "Smartphone Model XYZ" into their device and press the submit button. The device sends this information to the server, which collects the price, stock status, and shipping information for "Smartphone Model XYZ" from multiple online stores. For example, suppose online store A offers a total price of 80,000 yen, online store B offers a total price of 78,000 yen, and online store C offers a total price of 79,000 yen. After analyzing this information, the server determines that online store B offers the lowest price, creates a list of this information, and sends it to the user's device. The emotion engine determines that the user's emotion is "relaxed" and sends an appropriate notification. The user then checks the list on their device, accesses online store B's purchase page, and purchases "Smartphone Model XYZ" at the lowest price.

[1464] Example prompt for a generative AI model:

[1465] Provide user data: {typing_speed: 45, recent_clicks: ["home", "search", "product page"]}. A user is searching for "Smartphone XYZ model". Recognize the user's sentiment, gather information on the cheapest online store, and generate an appropriate notification message.

[1466] In this way, the system of the present invention not only enables users to efficiently find the cheapest products, but also allows users to receive appropriate product suggestions and notifications according to their emotional state.

[1467] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1468] Step 1:

[1469] The user inputs information about the product they want into the terminal. The input information is detailed information such as "smartphone XYZ model."

[1470] input:

[1471] Product details entered by the user.

[1472] output:

[1473] The input product information is sent from the terminal to the server.

[1474] Data processing / calculation:

[1475] The terminal prepares the entered text data for transmission to the server.

[1476] Step 2:

[1477] The server sends requests to a plurality of online stores based on the product information received from the terminal.

[1478] input:

[1479] Product information sent from the device.

[1480] output:

[1481] Pricing, stock, shipping information, etc. obtained from online stores.

[1482] Data processing / calculation:

[1483] The server uses the specified keywords to gather the necessary information using the online store's API and web scraping techniques, accessing web pages using Python requests and parsing the HTML data using BeautifulSoup.

[1484] Step 3:

[1485] The server analyzes the collected information, calculates the total price of the items (price + shipping fee), and selects the cheapest item.

[1486] input:

[1487] Pricing, stock, shipping information, etc. obtained from online stores.

[1488] output:

[1489] Information on the total price and lowest prices of products at each online store.

[1490] Data processing / calculation:

[1491] The server calculates a total price for each item by adding up the price and shipping costs, then compares the calculated prices to identify the cheapest item.

[1492] Step 4:

[1493] The server creates a list of the lowest priced products selected and provides it to the user.

[1494] input:

[1495] Lowest price product information, total price.

[1496] output:

[1497] User-viewable list of lowest priced products.

[1498] Data processing / calculation:

[1499] The server formats the selected lowest priced product information into a list format and converts it into a data format for transmission to the user's terminal.

[1500] Step 5:

[1501] The emotion engine analyzes the user's input information and behavioral data to recognize emotions.

[1502] input:

[1503] Behavioral data such as user typing speed, selections, and past purchases.

[1504] output:

[1505] The user's emotional state.

[1506] Data processing / calculation:

[1507] The emotion engine uses a generative AI model (pre-trained using Keras) to predict user emotions from input data.

[1508] Step 6:

[1509] The server then makes optimal product suggestions and notifications based on the recognized emotions.

[1510] input:

[1511] User emotional state, lowest price product information.

[1512] output:

[1513] Personalized notification messages.

[1514] Data processing / calculation:

[1515] The server generates appropriate messages and notifications based on the user's emotional state. For example, a relaxed user might receive a message like, "If you're not in a hurry, this product is perfect for you!"

[1516] Step 7:

[1517] The server monitors price fluctuations and notifies the user if the price drops.

[1518] input:

[1519] Registered product information and historical price data.

[1520] output:

[1521] Get notified when the price drops.

[1522] Data processing / calculation:

[1523] The server periodically retrieves price data for each product and compares it with previous data to detect price fluctuations. If the price drops, the server notifies the user.

[1524] 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.

[1525] 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.

[1526] 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.

[1527] 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.

[1528] FIG. 9 illustrates 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 behaviors 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.

[1529] 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.

[1530] 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).

[1531] 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.

[1532] 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."

[1533] 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.

[1534] 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).

[1535] 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.

[1536] 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.

[1537] 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.

[1538] 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.

[1539] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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 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.

[1540] 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.

[1541] 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.

[1542] 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.

[1543] 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.

[1544] 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.

[1545] The following is further disclosed regarding the above embodiment.

[1546] (Claim 1)

[1547] A means for a user to input desired product information;

[1548] A means for receiving product information and collecting information such as price, availability, and shipping costs from multiple online stores on the Internet;

[1549] A means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products;

[1550] A means for listing the selected lowest priced product information and providing it to users;

[1551] A system including:

[1552] (Claim 2)

[1553] 2. The system of claim 1, wherein the total amount calculation means includes means for totaling the product price and shipping cost.

[1554] (Claim 3)

[1555] 2. The system according to claim 1, further comprising means for periodically checking price fluctuations based on product information registered by the user and notifying the user when the price drops.

[1556] "Example 1"

[1557] (Claim 1)

[1558] A means for a user to input desired product information;

[1559] A means for receiving product information and collecting information such as price, stock status, and shipping costs from multiple sales sites on the Internet;

[1560] A means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products;

[1561] A means for listing the selected lowest priced product information and providing it to users;

[1562] A means to monitor daily price fluctuations and notify users when the price drops;

[1563] A system including:

[1564] (Claim 2)

[1565] 2. The system of claim 1, further comprising total calculation means for totaling the product price and shipping cost.

[1566] (Claim 3)

[1567] 2. The system according to claim 1, further comprising means for periodically checking price fluctuations based on product information registered by a user and notifying the user when the price drops.

[1568] "Application Example 1"

[1569] (Claim 1)

[1570] A means for a user to input desired product information;

[1571] A means for receiving product information and collecting information such as price, availability, and shipping costs from multiple online stores on the Internet;

[1572] A means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products;

[1573] A means for listing the selected lowest priced product information and providing it to users;

[1574] A means for performing payment processing and a means for seamlessly receiving, collecting, analyzing information, and performing payment as a series of processes;

[1575] A system including:

[1576] (Claim 2)

[1577] 10. The system of claim 1, further comprising means for totaling the product price and shipping cost.

[1578] (Claim 3)

[1579] 2. The system according to claim 1, further comprising means for periodically checking price fluctuations based on product information registered by a user and notifying the user when the price drops.

[1580] "Example 2: Combining Emotion Engines"

[1581] (Claim 1)

[1582] A means for a user to input desired product information;

[1583] means for receiving product information and collecting information such as price, availability, and shipping charges from a plurality of e-commerce sites on a communications network;

[1584] A means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products;

[1585] A means for listing the selected lowest priced product information and providing it to users;

[1586] A means for recognizing the emotional state of a user and providing product suggestions and notifications based on the emotion;

[1587] A system including:

[1588] (Claim 2)

[1589] 2. The system of claim 1, wherein the total amount calculation means includes means for totaling the product price and shipping cost.

[1590] (Claim 3)

[1591] 2. The system according to claim 1, further comprising means for periodically checking price fluctuations based on product information registered by the user and notifying the user when the price drops.

[1592] "Application example 2 when combining emotion engines"

[1593] (Claim 1)

[1594] A means for a user to input desired product information;

[1595] A means for receiving product information and collecting information such as price, availability, and shipping costs from multiple online stores on the Internet;

[1596] A means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products;

[1597] A means for listing the selected lowest priced product information and providing it to users;

[1598] A means for recognizing a user's emotions and providing optimal product suggestions and notifications based on the recognized emotions;

[1599] A means for evaluating the reliability of the collected information and filtering the product information based on the evaluation result;

[1600] A system including:

[1601] (Claim 2)

[1602] 2. The system of claim 1, wherein the total amount calculation means includes means for totaling the product price and shipping cost.

[1603] (Claim 3)

[1604] 2. The system according to claim 1, further comprising means for periodically checking price fluctuations based on product information registered by the user and notifying the user when the price drops. [Explanation of symbols]

[1605] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for a user to input desired product information; A means for receiving product information and collecting information such as price, availability, and shipping costs from multiple online stores on the Internet; A means for analyzing the collected information, calculating the total price of the products, and selecting the cheapest products; A means for listing the selected lowest priced product information and providing it to users; A system including:

2. 2. The system of claim 1, wherein the total calculation means includes means for totaling the product price and shipping cost.

3. 2. The system according to claim 1, further comprising means for periodically checking price fluctuations based on product information registered by the user and notifying the user when the price drops.

Images