system

Abstract

Provide a system. [Solution] means for receiving a product search request; A means for requesting product information from APIs of multiple e-commerce platforms and obtaining price, shipping fee, and earned point information; A means for calculating the total amount based on the acquired price, shipping fee, and earned points information; A means of comparing the calculated totals and determining the most economical purchasing source; a means for outputting information on the determined supplier; 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, to find the most economical purchase from different e-commerce platforms (hereinafter referred to as "EC sites"), consumers had to visit each site individually and check the price, shipping fee, and points earned. This consumes a lot of time and effort, and is not efficient for consumers. There is a need to solve this problem and provide a system that allows consumers to quickly find the most economical purchase. [Means for solving the problem]

[0005] To solve these problems, the present invention provides the following means. First, it includes a means for receiving a product search request. Next, it includes a means for requesting product information from the APIs of multiple e-commerce sites and obtaining information on prices, shipping costs, and earned points. It also includes a means for calculating a total amount based on the obtained information on prices, shipping costs, and earned points. The calculation uses an algorithm that adds up the price and shipping costs and deducts the earned points. It then includes a means for comparing the calculated total amounts and determining the most economical purchasing source. Finally, it includes a means for outputting information on the determined purchasing source. This allows consumers to efficiently select the most economical purchasing source.

[0006] A "product search request" is a request entered by a user and sent to a server to retrieve specific product information.

[0007] An "e-commerce platform" is a website that allows the buying and selling of goods and services over the Internet.

[0008] "API" stands for Application Programming Interface, a means by which different software applications communicate with each other.

[0009] "Product information" refers to detailed data about a specific product, such as price, shipping fee, and earned points.

[0010] "Price" is the sales price set for the product.

[0011] "Shipping costs" are costs incurred in connection with the delivery of goods.

[0012] "Earned points" are points that are awarded to customers when they purchase a product, and can be used as monetary value for subsequent purchases.

[0013] "Total amount" refers to the final payment amount, which is the sum of the product price and shipping fee, minus the points earned.

[0014] A "purchase destination" is an e-commerce site that a consumer selects when purchasing a product.

[0015] "Comparison" is the act of contrasting multiple elements and determining their differences or merits.

[0016] "Output" is the act of displaying or communicating calculation results or decisions to the user. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] This invention relates to a system that compares the prices, shipping costs, and points earned on multiple e-commerce platforms (EC sites) when a user searches for a specific product, and presents the most economical purchase option. This system is implemented using the following means.

[0039] 1. Receiving a product search request

[0040] When a user enters a product name or product code into the search bar of the device and presses the search button, the device generates a product search request and sends it to the server, which then receives the product search request.

[0041] 2. Querying APIs of multiple e-commerce platforms

[0042] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce sites. Specifically, it calls the APIs of each e-commerce site to obtain the price, shipping fee, and earnable points information for the specified product.

[0043] 3. Obtaining price, shipping and point information

[0044] The server receives and analyzes the product information returned from each e-commerce site, extracting information such as price, shipping fee, and points, and then integrates and manages the data.

[0045] 4. Calculation of total amount

[0046] The server calculates the total price based on the information it has received. The total price is calculated using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This allows the lowest payment amount presented to the user.

[0047] 5. Determine the most economical purchase source

[0048] The server compares the calculated totals and determines the most economical purchase. The comparison is not a simple price comparison, but a comparison of the total amount taking into account all factors (price, shipping, points).

[0049] 6. Sending results to users

[0050] The server sends the information on the most economical purchasing site determined by the server to the user's device. The user's device receives this information and displays it on the screen. The displayed content includes the name of the recommended e-commerce site, the price, shipping fee, points information, and the total price.

[0051] Specific examples

[0052] For example, suppose a user searches for "smartphone" on their device. When the device sends a product search request to the server, the server calls the APIs of Rakuten Ichiba and Amazon to retrieve information from each. Rakuten Ichiba retrieves information such as price: 40,000 yen, shipping: 500 yen, and points: 1,000, while Amazon retrieves information such as price: 39,000 yen, shipping: 400 yen, and points: 800.

[0053] The server calculates the total amount based on this information. In the case of Rakuten Ichiba, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen. On the other hand, in the case of Amazon, the total amount is (39,000 yen + 400 yen) - 800 points = 38,600 yen.

[0054] The server compares these total prices and determines Amazon as the most economical place to purchase. Finally, the user's device displays the result: "Buying from Amazon is the best deal. Price: 39,000 yen, Shipping: 400 yen, Points: 800 points."

[0055] The above is an embodiment of the present invention. This system allows users to efficiently find the most economical purchase source, thereby saving a lot of time and effort.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] The user enters the product name or product code into the search bar on the device and presses the search button. The device generates a product search request based on the input information and sends it to the server.

[0059] Step 2:

[0060] The server receives the product search request sent from the terminal and extracts the product name and product code from the request body.

[0061] Step 3:

[0062] The server requests product information from the APIs of multiple e-commerce platforms, and then sends a request including the extracted product name and product code to the API endpoint of each e-commerce site.

[0063] Step 4:

[0064] The API of each e-commerce platform returns product information. For example, the response from Rakuten Ichiba and Amazon returns the price, shipping fee, and earned points information in JSON format.

[0065] Step 5:

[0066] The server receives and analyzes responses from each e-commerce platform, extracts price, shipping fee, and earned points from the JSON data, and manages all of this data together.

[0067] Step 6:

[0068] The server calculates the total amount based on the price, shipping fee, and earned points information. The server performs the following calculation for each e-commerce site: (price + shipping fee) - earned points. For example, in the case of Rakuten Ichiba, the total amount is (price 40,000 yen + shipping fee 500 yen) - 1,000 points = 39,500 yen.

[0069] Step 7:

[0070] The server determines the most economical purchase destination based on the total amount calculated. The server compares multiple total amounts and selects the purchase destination with the lowest total amount. For example, since the total amount on Amazon is 38,600 yen, Amazon is selected.

[0071] Step 8:

[0072] The server sends information about the most economical shopping destination to the user's terminal. The server generates a response containing detailed information about the selected shopping destination (price, shipping fee, points, total amount) and returns it to the terminal.

[0073] Step 9:

[0074] The device receives a response from the server. The device analyzes the received data and displays it on the screen in a format that is easy for the user to understand. For example, it might say, "Buying from Amazon is the best deal. Price: 39,000 yen, shipping: 400 yen, points: 800 points."

[0075] The above is the specific processing flow of this system, which allows users to easily find the most economical purchasing site from multiple e-commerce sites.

[0076] Example 1

[0077] 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."

[0078] In conventional e-commerce, users have to visit multiple e-commerce sites individually to compare prices, shipping costs, and points earned, which takes a lot of time and effort.In addition, there is also the problem that information needed to find the most economical purchase is scattered, making it difficult for users to make the best choice.

[0079] 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.

[0080] In this invention, the server includes means for receiving a product search request, means for requesting product information from data acquisition interfaces of multiple e-commerce sites and acquiring information on prices, shipping fees, and earned points, means for calculating a total amount based on the acquired information on prices, shipping fees, and earned points, means for comparing the calculated total amounts and determining the most economical purchasing source, and means for outputting information on the determined purchasing source, thereby enabling users to efficiently find the most economical purchasing source.

[0081] "Product Search Request" means a request containing information entered by a user to search for a particular product.

[0082] An "e-commerce site" is a platform for selling goods and services over the Internet.

[0083] A "data acquisition interface" is a program interface for communicating with an external system to acquire information.

[0084] "Product information" refers to detailed information such as product price, shipping fee, and earned points.

[0085] "Price" refers to the amount you pay to purchase a particular item.

[0086] "Shipping Costs" means any additional costs required to deliver a Product.

[0087] "Earned points" are points that can be acquired when purchasing a product and can be used for subsequent purchases.

[0088] "Total amount" refers to the final payment amount, which is the sum of the product price and shipping fee, minus the points earned.

[0089] The "most economical place to buy" is the site with the lowest total price and the most economical for the user.

[0090] "Means for outputting information" refers to a method or device for displaying or providing the processing results to the user.

[0091] This invention is a system that compares prices, shipping costs, and points earned on multiple e-commerce sites when a user searches for a specific product, and presents the most economical purchasing source. The following is a specific embodiment for implementing this system.

[0092] First, the user enters the product name or product code into the search bar of the device and presses the search button. This operation causes the device to generate a product search request and send it to the server. The server receives this product search request and requests product information from the data acquisition interfaces of multiple e-commerce sites (e.g., major domestic e-commerce sites and major international e-commerce sites).

[0093] Specifically, the server calls the API of each e-commerce site to obtain the price, shipping cost, and available points for the specified product. This process can use APIs such as those of Rakuten Ichiba or Amazon. The server receives the product information returned from each e-commerce site and parses it in JSON format. Information such as price, shipping cost, and points is extracted individually, and the data is integrated and managed.

[0094] The server then calculates the total amount based on the information obtained. This calculation is performed using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This ensures that the lowest payment amount is presented to the user. For example, consider a case where a price of 40,000 yen, shipping cost of 500 yen, and 1,000 points are obtained on Rakuten Market, and a price of 39,000 yen, shipping cost of 400 yen, and 800 points are obtained on a major international e-commerce site.

[0095] The server calculates the total price based on this information. In the case of Rakuten Ichiba, the total price is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen, and in the case of the major international e-commerce site, the total price is (39,000 yen + 400 yen) - 800 points = 38,600 yen. The server compares these total prices and determines the major international e-commerce site as the most economical purchase destination.

[0096] Finally, the server sends the information on the most economical purchasing site to the user's device. The device receives this information and displays it on the screen. The displayed information includes the name of the recommended e-commerce site, price, shipping fee, points information, and total amount. For example, the result may read, "Purchasing from a major international e-commerce site is the best value. Price: 39,000 yen, shipping fee: 400 yen, points: 800 points."

[0097] This system allows users to efficiently find the most economical purchases, thereby saving a lot of time and effort.

[0098] Examples of prompts include:

[0099] "I want to build a system that allows users to search for a specific product and compares prices, shipping costs, and reward points across multiple e-commerce sites to suggest the most economical purchase. Please explain the process by following these steps."

[0100] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0101] Step 1:

[0102] The user enters the product name or product code in the search bar of the device and presses the search button. This operation causes the device to generate a product search request and send it to the server.

[0103] Input: The product name or code entered by the user (e.g., "smartphone").

[0104] Output: Product search request (e.g., search request for "smartphone").

[0105] Specific operation: When a user enters "smartphone" and presses the search button, the device sends an HTTP POST request to the server, which includes the search key ("smartphone").

[0106] Step 2:

[0107] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce sites.

[0108] Input: Product search request (e.g., search request for "smartphone").

[0109] Output: Product information requests from each e-commerce site (e.g., requests to Rakuten Ichiba and Amazon).

[0110] Specific operation: The server analyzes the product search request and sends an HTTP GET request to the Rakuten Ichiba or Amazon API. The request includes the API key and search key.

[0111] Step 3:

[0112] The server receives and analyzes product information returned from multiple e-commerce sites, extracting individual data such as price, shipping fee, and points, and then integrates and manages them.

[0113] Input: Product information returned from each e-commerce site (e.g., responses from Rakuten Ichiba and Amazon).

[0114] Output: Parsed price, shipping fee, and points information (e.g., Rakuten Ichiba price: 40,000 yen, shipping fee: 500 yen, points: 1,000 points).

[0115] Specific operation: The server receives API responses from Rakuten Ichiba and Amazon in JSON format, extracts price, shipping fee, and points information, and stores the extracted information in an internal data structure.

[0116] Step 4:

[0117] The server calculates the total amount based on the information it has received, adding up the product price and shipping costs and using an algorithm to deduct the points earned.

[0118] Input: Parsed price, shipping fee, and points information (e.g., Rakuten Ichiba and Amazon information).

[0119] Output: Total amount for each candidate destination (e.g., Rakuten Market total amount: 39,500 yen, Amazon total amount: 38,600 yen).

[0120] Specific operation: The server calculates the total price (40,000 yen + 500 yen - 1,000 points = 39,500 yen) from the information on Rakuten (price 40,000 yen, shipping 500 yen, points 1,000), and the total price (39,000 yen + 400 yen - 800 points = 38,600 yen) from the information on Amazon (price 39,000 yen, shipping 400 yen, points 800).

[0121] Step 5:

[0122] The server compares the calculated totals and determines the most economical purchase.

[0123] Input: Total amount for each candidate (e.g., Rakuten Market total amount: 39,500 yen, Amazon total amount: 38,600 yen).

[0124] Output: Information on the most economical place to buy (e.g. Amazon is the most economical).

[0125] Specific operation: The server compares the total price of each candidate and selects the purchase destination (Amazon) with the lowest total price.

[0126] Step 6:

[0127] The server then sends the information on the most economical purchasing source to the user's device, which receives the information and displays it on the screen.

[0128] Input: Information on the most economical place to purchase (e.g., Amazon is the most economical).

[0129] Output: The result displayed on the user's screen (e.g., "Buying from Amazon is the best deal. Price: 39,000 yen, Shipping: 400 yen, Points: 800 points").

[0130] Specific operation: The server returns information on the most economical purchasing source in JSON format as an HTTP response, and the device parses the information and displays it on the screen.

[0131] This allows users to efficiently find the most economical purchases, saving them a lot of time and effort.

[0132] (Application example 1)

[0133] 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."

[0134] In conventional e-commerce, users have to compare multiple platforms themselves, making it difficult to efficiently find the most economical place to buy. In addition, there is a lack of a way for users to easily find the best place to buy even while on the move.

[0135] 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.

[0136] In this invention, the server includes means for receiving a product search request, means for requesting product information from APIs of multiple e-commerce platforms and acquiring price, shipping fee, and earned point information, and means for calculating the total amount based on the acquired price, shipping fee, and earned point information. This allows users to easily find the most economical purchase from multiple e-commerce sites using their mobile terminals.

[0137] A "product search request" is a request sent by a user via a terminal to obtain information about a product that the user is considering purchasing.

[0138] An "e-commerce platform" is an online marketplace for buying and selling goods and services over the Internet.

[0139] "API" stands for Application Programming Interface, an interface that defines the rules and protocols for different software systems to communicate with each other.

[0140] "Price" is the amount indicating the monetary value of the item being purchased.

[0141] "Shipping fee" refers to the cost of shipping purchased items to the user.

[0142] "Earned points" are points that are awarded to users in response to purchases and can be used as monetary value for future purchases.

[0143] "Total amount" means the final payment amount, which is the product price plus shipping fee and deduction of earned points.

[0144] A "mobile terminal" is a portable communication device such as a smartphone or tablet.

[0145] "Comparison" is the act of evaluating multiple options based on their respective characteristics and determining their relative merits.

[0146] The "most economical source" is the source that will result in the lowest expenditure for the user after taking into account all costs and benefits.

[0147] This invention is a system that compares prices, shipping costs, and points earned on multiple e-commerce platforms when a user searches for a specific product, and presents the most economical purchase option. This system allows users to efficiently decide where to purchase using their mobile terminals.

[0148] 1. System Configuration

[0149] The system consists of the following elements:

[0150] User device: A portable communication device such as a smartphone or tablet. This device has an interface for inputting product search requests.

[0151] Server: A central control unit that processes product search requests, queries multiple e-commerce platforms, aggregates and compares information, and determines the best purchasing location.

[0152] Multiple e-commerce platforms: Various online marketplaces, each providing pricing, shipping, and rewards information through APIs.

[0153] 2. Data Processing and Calculations

[0154] The system requires input from users, data acquisition from multiple e-commerce platforms, and data processing and calculation.

[0155] Receiving a product search request: When a user enters a product name or product code into the device's search bar and presses the search button, the device generates a product search request and sends it to the server.

[0156] Querying API: Based on the received product search request, the server requests product information from the APIs of multiple e-commerce platforms. Specifically, it calls the APIs of each e-commerce site to obtain the price, shipping fee, and available points information for the specified product.

[0157] Data acquisition and analysis: The server receives and analyzes the product information returned from each e-commerce site. Information such as price, shipping fee, and points is extracted individually, and the data is integrated and managed.

[0158] Calculating the total price: The server calculates the total price based on the information it has received. The total price is calculated using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This allows the lowest payment price to be presented to the user.

[0159] Determining the best supplier: The server compares the calculated totals and determines the most economical supplier.

[0160] Sending the results to the user: The server sends the information on the most economical purchasing site to the user's device. The user's device receives this information and displays it on the screen. The displayed content includes the name of the recommended e-commerce site, the price, shipping fee, points information, and the total price.

[0161] 3. Specific Examples

[0162] For example, suppose a user searches for "smartphone" on their device. When the device sends a product search request to the server, the server calls the APIs of multiple online marketplaces and obtains information on price, shipping, and points from each. Based on this information, the total price is calculated and the most economical purchase destination is determined. The "optimal purchase destination" is then displayed on the user's device.

[0163] Prompt Sentence Examples

[0164] "Please tell me the price of the smartphone, shipping costs, and points earned. Also, please do the same for multiple online marketplaces."

[0165] This allows users to easily and quickly find the most economical purchase, greatly improving user convenience.

[0166] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0167] Step 1:

[0168] The user enters the product name or product code into the device's search bar and presses the search button.

[0169] This operation generates a product search request, which is then sent to the server.

[0170] Input: Product name or product code

[0171] Data processing: Generating search requests

[0172] Output: Product search request

[0173] Step 2:

[0174] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce platforms.

[0175] Specifically, the server calls the API of each platform to obtain the price, shipping fee, and earned points information for the specified product.

[0176] Input: Product search request

[0177] Data processing: Creating and sending API requests

[0178] Output: Product information from each platform

[0179] Step 3:

[0180] The server receives and analyzes the product information returned from each e-commerce platform.

[0181] Through analysis, information such as price, shipping costs, and points is extracted individually, and each piece of data is integrated and managed.

[0182] Input: Product information from the platform

[0183] Data processing: Product information analysis and integration

[0184] Output: Consolidated product information

[0185] Step 4:

[0186] The server calculates the total amount based on each piece of information obtained.

[0187] The total price is calculated using an algorithm that adds up the product price and shipping costs and deducts the points earned.

[0188] Input: Integrated product information

[0189] Data processing: Calculate total amount (price + shipping fee - points)

[0190] Output: Total amount for each platform

[0191] Step 5:

[0192] The server compares the calculated totals and determines the most economical purchase.

[0193] Here, the total price of all platforms is compared and the purchase source with the lowest total price is selected.

[0194] Input: Total amount for each platform

[0195] Data processing: Comparing total amounts and selecting the best supplier

[0196] Output: Information on the most economical purchasing source

[0197] Step 6:

[0198] The server sends information on the most economical purchasing source determined by the server to the user's terminal.

[0199] The user's device receives this information and displays it on the screen, including the name of the recommended platform, the price, shipping fee, points information, and the total amount.

[0200] Input: Information on the most economical supplier

[0201] Data processing: transmission of information

[0202] Output: Supplier information displayed on the user's device

[0203] 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.

[0204] This invention relates to a system that provides product search results on an e-commerce platform while taking into account the user's emotions. In addition to the basic function of obtaining the price, shipping fee, and points for a product specified by the user from an e-commerce site and presenting the most economical purchasing options, this system also recognizes the user's emotions and filters or sorts the search results based on those emotions.

[0205] 1. Receiving a product search request

[0206] When a user enters a product name or product code into the device's search bar and presses the search button, the device generates a product search request and sends it to the server. At this time, the device uses a camera and microphone to record the user's facial expressions and voice, and analyzes them with an emotion engine in order to simultaneously recognize the user's emotions.

[0207] 2. Emotion recognition using an emotion engine

[0208] The device sends the user's facial and voice data to the emotion engine, which then analyzes the data to recognize the user's emotions. Emotions are classified into positive, negative, and neutral categories. For example, if the user is smiling, the emotion engine recognizes the emotion as positive.

[0209] 3. Querying APIs of multiple e-commerce platforms

[0210] Based on the product search request, the server requests product information from the APIs of multiple e-commerce sites. The server then sends a request including the extracted product name and product code to the API endpoint of each e-commerce site.

[0211] 4. Obtaining price, shipping and point information

[0212] The API of each e-commerce platform returns product information, which is received and analyzed by the server. The server extracts the price, shipping fee, and earned points from the JSON data and integrates and manages the data.

[0213] 5. Calculation of total amount

[0214] The server calculates the total amount based on the price, shipping cost, and earned points information. The calculation uses an algorithm that adds up the product price and shipping cost and subtracts the earned points. For example, if the price on Rakuten Market is 40,000 yen, shipping cost is 500 yen, and the points are 1,000, the total amount will be (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0215] 6. Emotional purchasing decisions

[0216] The server compares the calculated totals and determines the most economical purchase. The user's emotional data is also taken into account. For example, if the user is expressing positive emotions, other factors (high reviews, fast delivery, etc.) that are comparable in price and shipping costs are also taken into account.

[0217] 7. Sending results to the user

[0218] The server sends information about the most economical shopping destination to the user's device. This information includes the selected shopping destination, price, shipping fee, points, and the reason for the recommendation based on emotion. For example, for a user who expresses positive emotion, the recommendation may include "This product has high ratings and will arrive quickly."

[0219] Specific examples

[0220] For example, suppose a user searches for "smartphone" on their device and smiles at the camera. The device sends a product search request to the server, and at the same time, the emotion engine analyzes the user's positive emotions. The server then calls the APIs of Rakuten Ichiba and Amazon to retrieve their respective information.

[0221] On Rakuten, the price is 40,000 yen, shipping is 500 yen, and points are 1,000, for a total of 39,500 yen, while on Amazon, the price is 39,000 yen, shipping is 400 yen, and points are 800, for a total of 38,600 yen. Because the user is smiling, which is recognized as a positive emotion, the server takes into account review ratings and delivery time, and selects Amazon, which has the highest enthusiastic ratings and is expected to deliver quickly.

[0222] Ultimately, the user's device will display a result such as, "Buying from Amazon is the best deal. Price: 39,000 yen, shipping: 400 yen, points: 800 points. High reviews and fast delivery."

[0223] This system allows users to efficiently and emotionally select the best shopping destination, improving their shopping experience.

[0224] The processing flow will be explained below.

[0225] Step 1:

[0226] The user enters the product name or product code into the device's search bar and presses the search button. The device generates a product search request based on this information and sends it to the server. At the same time, the device uses the camera and microphone to record the user's facial expressions and voice, and sends them to the emotion engine.

[0227] Step 2:

[0228] The emotion engine analyzes the user's recorded facial expressions and voice and classifies the user's emotion as positive, negative, or neutral. For example, if the user is smiling, the emotion engine will recognize it as positive.

[0229] Step 3:

[0230] The server receives the product search request sent from the terminal and extracts the product name and product code from the request body.

[0231] Step 4:

[0232] The server requests product information from the APIs of multiple e-commerce platforms. Specifically, it sends a request including the product name and product code to an API endpoint and makes a call to each platform to retrieve the data.

[0233] Step 5:

[0234] The API of each e-commerce platform returns product information. For example, Rakuten Ichiba returns data such as a price of 40,000 yen, shipping cost of 500 yen, and 1,000 points, while Amazon returns data such as a price of 39,000 yen, shipping cost of 400 yen, and 800 points.

[0235] Step 6:

[0236] The server analyzes the responses received from each platform and extracts the price, shipping fee, and earned points. The extracted data is organized and managed for each e-commerce platform.

[0237] Step 7:

[0238] The server calculates the total amount based on the price, shipping cost, and earned points information it has obtained. The server performs the calculation as follows: (price + shipping cost) - earned points. For example, in the case of Rakuten Ichiba, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen, and in the case of Amazon, it is (39,000 yen + 400 yen) - 800 points = 38,600 yen.

[0239] Step 8:

[0240] The server determines the most economical purchase based on the calculated total amount. Here, the user's emotional data is also taken into consideration. For example, if the user has a positive emotion, additional information such as product reviews and delivery speed is also included in the purchase decision.

[0241] Step 9:

[0242] The server sends information about the most economical purchasing destination to the user's device. This information includes the selected purchasing destination, price, shipping fee, points, and emotional reasons for the recommendation. For example, a result such as "Buying from Amazon is the best deal. Price: 39,000 yen, shipping fee: 400 yen, points: 800 points. It has high reviews and offers fast delivery" is sent.

[0243] Step 10:

[0244] The terminal receives the response from the server and analyzes it. The analyzed results are then displayed on the screen in a format that is easy for the user to understand. This allows the user to select the most economical and satisfying purchasing source.

[0245] The above is the specific processing flow of this system. By combining emotion engines, it is possible to make optimal product suggestions and purchase decisions based on the user's emotions.

[0246] Example 2

[0247] 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."

[0248] Conventional e-commerce platforms provide product search results based mainly on price, shipping costs, and points, and are unable to provide search results that take into account the user's emotions and purchasing intentions. This has led to a decrease in user purchasing satisfaction. There is also a need for a system that not only presents the most economical purchasing options, but also provides optimal search results that reflect the user's emotions.

[0249] 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 means for receiving a product search request, means for requesting product information from the APIs of multiple e-commerce platforms and acquiring information on prices, shipping costs, and earned points, means for calculating a total amount based on the acquired price, shipping costs, and earned points information, means for comparing the calculated total amounts and determining the most economical purchasing destination, means for recognizing user emotions, means for filtering or sorting search results based on the recognized user emotions, and means for outputting information on the determined purchasing destination. This makes it possible to select an optimal purchasing destination taking user emotions into consideration and provide high purchasing satisfaction.

[0250] A "product search request" is a request to the server to search for product information, which is generated when a user inputs a product name or product code into a terminal and presses a search button.

[0251] An "e-commerce platform" is an internet-based marketplace that connects multiple sellers and buyers, where goods and services are bought and sold.

[0252] "API" stands for Application Programming Interface, an interface for communication and data exchange between different software systems.

[0253] "Product Information" refers to data including product prices, shipping fees, points, and other related information.

[0254] "Price" refers to the amount of money required to purchase a particular product.

[0255] "Shipping cost" means the cost of transportation required to deliver the product.

[0256] "Earned points" are points awarded when purchasing a product, and can be used to purchase products or services at a later date.

[0257] "Total amount" refers to the actual amount to be paid, calculated by adding the product price and shipping fee and deducting the points earned.

[0258] "Emotions" indicate the user's psychological state and are classified into positive, negative, and neutral categories.

[0259] An "emotion engine" is software that analyzes a user's facial expressions and voice data to recognize the user's emotions.

[0260] "Filtering" is the operation of narrowing down data based on specific conditions.

[0261] "Sorting" is an operation for rearranging data in order based on specific conditions.

[0262] "Destination" refers to the e-commerce platform or merchant from which a user chooses to purchase goods.

[0263] "Search results" refers to a list of product information displayed in response to a user's search request.

[0264] This invention relates to a system that provides product search results on an e-commerce platform while taking user emotions into consideration. In addition to the basic function of obtaining the price, shipping fee, and points of a product specified by a user from an e-commerce site and presenting the most economical purchasing options, the system also recognizes the user's emotions and filters or sorts the search results based on those emotions.

[0265] The system includes means for receiving a product search request, means for requesting product information from APIs of multiple e-commerce platforms and obtaining information on prices, shipping fees, and earned points, means for calculating a total amount based on the obtained information on prices, shipping fees, and earned points, means for comparing the calculated total amounts and determining the most economical purchasing destination, means for recognizing user emotions, means for filtering or sorting search results based on the recognized user emotions, and means for outputting information on the determined purchasing destination.

[0266] The device generates a product search request based on the user's input and sends it to the server. The device is equipped with a search bar, camera, and microphone to record the user's facial expressions and voice. Specifically, the device's camera and microphone are used to monitor the user's facial expressions and voice in real time, and this data is sent to the emotion engine. The emotion engine uses a machine learning model to classify the user's emotion as positive, negative, or neutral.

[0267] The server sends a product information request to the APIs of multiple e-commerce platforms (e.g., major domestic e-commerce platforms and major international e-commerce platforms) based on the product search request received from the terminal. The product information obtained from the APIs of each platform is sent in JSON format or other data format, and includes the price, shipping fee, and earned points.

[0268] The server analyzes and extracts the price, shipping cost, and earned points from the API responses received from each platform, and calculates the total amount. This calculation uses an algorithm that adds up the price and shipping cost and subtracts the earned points. For example, on Rakuten Ichiba, if the price is 40,000 yen, shipping cost is 500 yen, and the points are 1,000, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0269] The server compares the calculated totals and considers the user's emotional data when determining the most economical purchasing platform. For example, if the user has a positive emotional state, the server will recommend a platform with high reviews and fast delivery by considering other factors (such as high reviews and fast delivery) with comparable prices and shipping costs.

[0270] The server sends information on the most economical and emotionally-based purchasing destinations to the user's terminal. This information includes the selected purchasing destination, price, shipping fee, points, and the reason for the recommendation based on emotion. For example, if the user has a positive emotion, the server can include a message such as "This product is highly rated and will arrive quickly."

[0271] Examples of prompts include:

[0272] "When a user smiles and searches their smartphone, choose the e-commerce site that offers the best deal and fastest delivery."

[0273] This system allows users to efficiently and emotionally select the best shopping destination, improving their shopping experience.

[0274] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0275] Step 1: Generate and submit a product search request

[0276] Input: The user enters the product name or product code into the device's search bar and presses the search button.

[0277] Specific operation: The user enters the product name (e.g., "smartphone") into the input form on the device and clicks the search button.

[0278] Data processing and calculation: The terminal generates a product search request based on the user's input and sends it to the server in the form of an HTTP request.

[0279] Output: Get the product search request received by the server.

[0280] Step 2: Acquire and analyze user emotion data

[0281] Input: At the same time as sending a product search request, the device's camera and microphone record the user's facial expressions and voice.

[0282] Specific operation: The device captures the user's facial expressions and voice in real time using the camera and microphone.

[0283] Data processing and calculation: The facial expression and voice data collected by the device is sent to the emotion engine, which uses a machine learning model to classify the user's emotion as positive, negative, or neutral.

[0284] Output: Classified emotion data is sent to the server.

[0285] Step 3: Request product information from the e-commerce platform

[0286] Input: Product search request sent from the device.

[0287] Specific operation: Based on the product search request, the server sends HTTP requests to the APIs of multiple e-commerce platforms.

[0288] Data processing and calculation: The API request includes the product name and product code, and the response is received from each platform in JSON format or other data format.

[0289] Output: Product information returned from each e-commerce platform.

[0290] Step 4: Obtain and analyze price, shipping, and points information

[0291] Input: The API response returned by the e-commerce platform.

[0292] Specific operation: The server analyzes the API response received and extracts the necessary data (price, shipping fee, points).

[0293] Data processing and calculation: The server extracts the price, shipping fee, and points from the JSON data in a unique format, and organizes and integrates them.

[0294] Output: Organized price, shipping, and points information.

[0295] Step 5: Calculate the total purchase amount

[0296] Input: Obtained price, shipping, and points information.

[0297] Specific operation: The server uses this data to calculate the total amount.

[0298] Data processing and calculation: An algorithm is used to add up the price and shipping cost and deduct points. For example, if the price is 40,000 yen, the shipping cost is 500 yen, and the points are 1,000 points, the total will be (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0299] Output: Calculated gross amount data.

[0300] Step 6: Emotional purchasing decisions

[0301] Input: Calculated total amount data and user sentiment data.

[0302] Specific operation: The server compares the total amount data and determines the most appropriate purchasing destination taking into account the user's feelings.

[0303] Data processing and calculation: For users who show positive sentiment, other factors such as review ratings and delivery times are taken into account.

[0304] Output: Information on the most appropriate purchasing platform (platform name, price, shipping fee, points, reason for recommendation).

[0305] Step 7: Send supplier information to users

[0306] Input: Determined supplier information.

[0307] Specific operation: The server transmits the determined supplier information to the terminal.

[0308] Data processing and calculation: Formatting information including the reason for recommendation (e.g., "high reviews and fast delivery expected").

[0309] Output: Information on the best places to buy displayed on the user's device.

[0310] (Application example 2)

[0311] 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."

[0312] Conventional e-commerce systems provide product search results without considering the user's feelings, making it difficult to optimize the user's purchasing experience. In particular, determining the most economical purchasing destination without considering the user's feelings about the searched product can reduce user satisfaction.

[0313] 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.

[0314] In this invention, the server includes means for receiving a product search request, means for requesting product information from the APIs of multiple e-commerce platforms and acquiring information on prices, shipping costs, and earned points, means for calculating the total amount based on the acquired price, shipping costs, and earned points, means for determining the most economical and suitable purchasing destination based on the calculated total amount and the user's emotions, means for outputting information on the determined purchasing destination, and means for acquiring the user's facial expressions and voice data using a camera and microphone and analyzing them with an emotion engine. This makes it possible to present the most suitable purchasing destination taking the user's emotions into consideration.

[0315] The "means for receiving a product search request" is a function that sends a product search request generated by the terminal to the server when a user inputs a product name or product code into the search bar and presses the search button.

[0316] "Means for requesting product information from the APIs of multiple e-commerce platforms and obtaining information on prices, shipping fees, and earned points" refers to a function in which a server sends requests to the API endpoints of multiple e-commerce platforms and obtains the product information of each.

[0317] The "means for calculating the total amount based on the acquired price, shipping fee, and earned point information" is a function that the server uses the price, shipping fee, and earned point information acquired from each e-commerce platform to calculate the total amount.

[0318] "Means for determining the most economical and suitable purchasing source based on the calculated total amount and the user's emotions" is a function that selects the most suitable purchasing source by taking into consideration the total amount calculated by the server and the user's emotional data.

[0319] The "means for outputting information on the determined supplier" is a function by which the server notifies the user of information on the most suitable supplier.

[0320] "Means for acquiring the user's facial expressions and voice data using a camera and microphone and analyzing it with an emotion engine" refers to a function that acquires the user's facial images and voice, sends them to the emotion engine for analysis, and recognizes the user's emotions.

[0321] The "emotion engine" is a system that analyzes the user's facial expressions and voice data and classifies them into emotional categories such as positive, negative, and neutral.

[0322] "Total Calculation" is the process of adding up the acquired price and shipping costs and subtracting earned points to determine the actual total cost of the item.

[0323] This invention relates to an electronic commerce system that provides product search results taking into account the user's emotions. When a user makes a product search request via a terminal, the system recognizes the user's emotions and presents the most suitable purchasing destination. This section explains each processing step for recognizing the user's emotions and presenting the most suitable purchasing destination.

[0324] System Configuration

[0325] 1. Hardware and Software:

[0326] Device: A device such as a smartphone or tablet that has a built-in camera and microphone.

[0327] Server: A central server for accessing APIs of multiple e-commerce platforms.

[0328] Emotion engine: A software library for analyzing a user's facial expressions and voice and classifying them into emotional categories.

[0329] Flask: Used as a web application framework.

[0330] Requests: A Python library for sending HTTP requests.

[0331] Program processing overview

[0332] The device generates a product search request and sends it to the server. When the user enters a product name or code into the search bar and presses the search button, the device uses a camera and microphone to record the user's facial expressions and voice data. This data is sent to the emotion engine, which classifies the user's emotion as positive, negative, or neutral.

[0333] The server requests product information from the APIs of multiple e-commerce platforms. It calculates the total price based on the obtained price, shipping cost, and earned points information, and also combines the user's emotional data to determine the most economical and suitable purchasing destination. Finally, the server sends the information of the selected purchasing destination to the user's device.

[0334] Specific examples

[0335] For example, if a user searches for "smartphone" on their device, the device records image data and audio of them smiling at the camera. This data is analyzed by the emotion engine and recognized as a positive emotion. The server then retrieves product data from multiple e-commerce platforms, comparing it with information such as a price of ¥40,000, shipping of ¥500, 1,000 points, and a total of ¥39,500 on Rakuten, or a price of ¥39,000, shipping of ¥400, 800 points, and a total of ¥38,600 on Amazon.

[0336] Because the user's sentiment is positive, the server selects the optimal purchasing source by taking into consideration not only price and shipping costs, but also reviews and delivery time. In this case, the server selects Amazon, which has high reviews and is expected to deliver quickly, and sends that information to the user's device.

[0337] Prompt Sentence Examples

[0338] The prompt text that is entered when a user searches for "smartphone" is as follows:

[0339] Text input: "Smartphone"

[0340] Emotion data: image data and audio data (indicating a smile)

[0341] This allows users to quickly and efficiently select the best place to purchase products based on their emotions, significantly improving the user's purchasing experience.

[0342] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0343] Step 1:

[0344] The user enters the product name or product code into the search bar of the device and presses the search button. At this time, the device's camera and microphone record the user's facial expression and voice data. The input data, which is the product name and the user's facial expression and voice data, is sent to the subsequent processing step.

[0345] Step 2:

[0346] The device sends the user's facial and voice data to the emotion engine, which analyzes it to recognize the user's emotions. Emotional data is classified as positive, negative, or neutral. The input data is the user's facial and voice data, and the output data is the emotion category (positive, negative, or neutral).

[0347] Step 3:

[0348] Based on the product search request, the server requests product information from the API endpoints of multiple e-commerce platforms. The input data is the product name, and the request is sent to each platform. The output data is the price, shipping fee, and earned points information obtained from each platform.

[0349] Step 4:

[0350] The server calculates the total amount based on the acquired price, shipping fee, and earned point information. The total amount is the sum of the price and shipping fee and the earned point amount. The input data are the price, shipping fee, and earned point information, and the output data is the calculated total amount.

[0351] Step 5:

[0352] The server determines the most economical and suitable purchasing destination based on the calculated total price and the user's sentiment. If the sentiment data is positive, it also takes into account reviews and delivery time in addition to price and shipping costs. The input data are the calculated total price and sentiment data, and the output data is information on the optimal purchasing destination.

[0353] Step 6:

[0354] The server sends the information on the optimal supplier it has determined to the user's terminal, which then displays this information to the user. The input data is the optimal supplier information, and the output data is the supplier information displayed to the user.

[0355] For example, if a user searches for "smartphone" and smiles at the camera, the device sends that data to the emotion engine, which recognizes it as a positive emotion. The server then retrieves product information from multiple platforms, calculates the total price, and determines the optimal purchasing source, taking into account the emotion data. In this case, the server selects a platform with high reviews and the potential for fast delivery, and notifies the user of that information.

[0356] Through the above steps, the user can quickly select the most suitable place to purchase products according to their emotions.

[0357] 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.

[0358] 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.

[0359] 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.

[0360] [Second embodiment]

[0361] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0362] 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.

[0363] 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).

[0364] 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.

[0365] 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.

[0366] 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).

[0367] 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.

[0368] 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.

[0369] 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.

[0370] 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.

[0371] 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.

[0372] 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."

[0373] This invention relates to a system that compares the prices, shipping costs, and points earned on multiple e-commerce platforms (EC sites) when a user searches for a specific product, and presents the most economical purchase option. This system is implemented using the following means.

[0374] 1. Receiving a product search request

[0375] When a user enters a product name or product code into the search bar of the device and presses the search button, the device generates a product search request and sends it to the server, which then receives the product search request.

[0376] 2. Querying APIs of multiple e-commerce platforms

[0377] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce sites. Specifically, it calls the APIs of each e-commerce site to obtain the price, shipping fee, and earnable points information for the specified product.

[0378] 3. Obtaining price, shipping and point information

[0379] The server receives and analyzes the product information returned from each e-commerce site, extracting information such as price, shipping fee, and points, and then integrates and manages the data.

[0380] 4. Calculation of total amount

[0381] The server calculates the total price based on the information it has received. The total price is calculated using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This allows the lowest payment amount presented to the user.

[0382] 5. Determine the most economical purchase source

[0383] The server compares the calculated totals and determines the most economical purchase. The comparison is not a simple price comparison, but a comparison of the total amount taking into account all factors (price, shipping, points).

[0384] 6. Sending results to users

[0385] The server sends the information on the most economical purchasing site determined by the server to the user's device. The user's device receives this information and displays it on the screen. The displayed content includes the name of the recommended e-commerce site, the price, shipping fee, points information, and the total price.

[0386] Specific examples

[0387] For example, suppose a user searches for "smartphone" on their device. When the device sends a product search request to the server, the server calls the APIs of Rakuten Ichiba and Amazon to retrieve information from each. Rakuten Ichiba retrieves information such as price: 40,000 yen, shipping: 500 yen, and points: 1,000, while Amazon retrieves information such as price: 39,000 yen, shipping: 400 yen, and points: 800.

[0388] The server calculates the total amount based on this information. In the case of Rakuten Ichiba, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen. On the other hand, in the case of Amazon, the total amount is (39,000 yen + 400 yen) - 800 points = 38,600 yen.

[0389] The server compares these total prices and determines Amazon as the most economical place to purchase. Finally, the user's device displays the result: "Buying from Amazon is the best deal. Price: 39,000 yen, Shipping: 400 yen, Points: 800 points."

[0390] The above is an embodiment of the present invention. This system allows users to efficiently find the most economical purchase source, thereby saving a lot of time and effort.

[0391] The processing flow will be explained below.

[0392] Step 1:

[0393] The user enters the product name or product code into the search bar on the device and presses the search button. The device generates a product search request based on the input information and sends it to the server.

[0394] Step 2:

[0395] The server receives the product search request sent from the terminal and extracts the product name and product code from the request body.

[0396] Step 3:

[0397] The server requests product information from the APIs of multiple e-commerce platforms, and then sends a request including the extracted product name and product code to the API endpoint of each e-commerce site.

[0398] Step 4:

[0399] The API of each e-commerce platform returns product information. For example, the response from Rakuten Ichiba and Amazon returns the price, shipping fee, and earned points information in JSON format.

[0400] Step 5:

[0401] The server receives and analyzes responses from each e-commerce platform, extracts price, shipping fee, and earned points from the JSON data, and manages all of this data together.

[0402] Step 6:

[0403] The server calculates the total amount based on the price, shipping fee, and earned points information. The server performs the following calculation for each e-commerce site: (price + shipping fee) - earned points. For example, in the case of Rakuten Ichiba, the total amount is (price 40,000 yen + shipping fee 500 yen) - 1,000 points = 39,500 yen.

[0404] Step 7:

[0405] The server determines the most economical purchase destination based on the total amount calculated. The server compares multiple total amounts and selects the purchase destination with the lowest total amount. For example, since the total amount on Amazon is 38,600 yen, Amazon is selected.

[0406] Step 8:

[0407] The server sends information about the most economical shopping destination to the user's terminal. The server generates a response containing detailed information about the selected shopping destination (price, shipping fee, points, total amount) and returns it to the terminal.

[0408] Step 9:

[0409] The device receives a response from the server. The device analyzes the received data and displays it on the screen in a format that is easy for the user to understand. For example, it might say, "Buying from Amazon is the best deal. Price: 39,000 yen, shipping: 400 yen, points: 800 points."

[0410] The above is the specific processing flow of this system, which allows users to easily find the most economical purchasing site from multiple e-commerce sites.

[0411] Example 1

[0412] 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."

[0413] In conventional e-commerce, users have to visit multiple e-commerce sites individually to compare prices, shipping costs, and points earned, which takes a lot of time and effort.In addition, there is also the problem that information needed to find the most economical purchase is scattered, making it difficult for users to make the best choice.

[0414] 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.

[0415] In this invention, the server includes means for receiving a product search request, means for requesting product information from data acquisition interfaces of multiple e-commerce sites and acquiring information on prices, shipping fees, and earned points, means for calculating a total amount based on the acquired information on prices, shipping fees, and earned points, means for comparing the calculated total amounts and determining the most economical purchasing source, and means for outputting information on the determined purchasing source, thereby enabling users to efficiently find the most economical purchasing source.

[0416] "Product Search Request" means a request containing information entered by a user to search for a particular product.

[0417] An "e-commerce site" is a platform for selling goods and services over the Internet.

[0418] A "data acquisition interface" is a program interface for communicating with an external system to acquire information.

[0419] "Product information" refers to detailed information such as product price, shipping fee, and earned points.

[0420] "Price" refers to the amount you pay to purchase a particular item.

[0421] "Shipping Costs" means any additional costs required to deliver a Product.

[0422] "Earned points" are points that can be acquired when purchasing a product and can be used for subsequent purchases.

[0423] "Total amount" refers to the final payment amount, which is the sum of the product price and shipping fee, minus the points earned.

[0424] The "most economical place to buy" is the site with the lowest total price and the most economical for the user.

[0425] "Means for outputting information" refers to a method or device for displaying or providing the processing results to the user.

[0426] This invention is a system that compares prices, shipping costs, and points earned on multiple e-commerce sites when a user searches for a specific product, and presents the most economical purchasing source. The following is a specific embodiment for implementing this system.

[0427] First, the user enters the product name or product code into the search bar of the device and presses the search button. This operation causes the device to generate a product search request and send it to the server. The server receives this product search request and requests product information from the data acquisition interfaces of multiple e-commerce sites (e.g., major domestic e-commerce sites and major international e-commerce sites).

[0428] Specifically, the server calls the API of each e-commerce site to obtain the price, shipping cost, and available points for the specified product. This process can use APIs such as those of Rakuten Ichiba or Amazon. The server receives the product information returned from each e-commerce site and parses it in JSON format. Information such as price, shipping cost, and points is extracted individually, and the data is integrated and managed.

[0429] The server then calculates the total amount based on the information obtained. This calculation is performed using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This ensures that the lowest payment amount is presented to the user. For example, consider a case where a price of 40,000 yen, shipping cost of 500 yen, and 1,000 points are obtained on Rakuten Market, and a price of 39,000 yen, shipping cost of 400 yen, and 800 points are obtained on a major international e-commerce site.

[0430] The server calculates the total price based on this information. In the case of Rakuten Ichiba, the total price is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen, and in the case of the major international e-commerce site, the total price is (39,000 yen + 400 yen) - 800 points = 38,600 yen. The server compares these total prices and determines the major international e-commerce site as the most economical purchase destination.

[0431] Finally, the server sends the information on the most economical purchasing site to the user's device. The device receives this information and displays it on the screen. The displayed information includes the name of the recommended e-commerce site, price, shipping fee, points information, and total amount. For example, the result may read, "Purchasing from a major international e-commerce site is the best value. Price: 39,000 yen, shipping fee: 400 yen, points: 800 points."

[0432] This system allows users to efficiently find the most economical purchases, thereby saving a lot of time and effort.

[0433] Examples of prompts include:

[0434] "I want to build a system that allows users to search for a specific product and compares prices, shipping costs, and reward points across multiple e-commerce sites to suggest the most economical purchase. Please explain the process by following these steps."

[0435] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0436] Step 1:

[0437] The user enters the product name or product code in the search bar of the device and presses the search button. This operation causes the device to generate a product search request and send it to the server.

[0438] Input: The product name or code entered by the user (e.g., "smartphone").

[0439] Output: Product search request (e.g., search request for "smartphone").

[0440] Specific operation: When a user enters "smartphone" and presses the search button, the device sends an HTTP POST request to the server, which includes the search key ("smartphone").

[0441] Step 2:

[0442] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce sites.

[0443] Input: Product search request (e.g., search request for "smartphone").

[0444] Output: Product information requests from each e-commerce site (e.g., requests to Rakuten Ichiba and Amazon).

[0445] Specific operation: The server analyzes the product search request and sends an HTTP GET request to the Rakuten Ichiba or Amazon API. The request includes the API key and search key.

[0446] Step 3:

[0447] The server receives and analyzes product information returned from multiple e-commerce sites, extracting individual data such as price, shipping fee, and points, and then integrates and manages them.

[0448] Input: Product information returned from each e-commerce site (e.g., responses from Rakuten Ichiba and Amazon).

[0449] Output: Parsed price, shipping fee, and points information (e.g., Rakuten Ichiba price: 40,000 yen, shipping fee: 500 yen, points: 1,000 points).

[0450] Specific operation: The server receives API responses from Rakuten Ichiba and Amazon in JSON format, extracts price, shipping fee, and points information, and stores the extracted information in an internal data structure.

[0451] Step 4:

[0452] The server calculates the total amount based on the information it has received, adding up the product price and shipping costs and using an algorithm to deduct the points earned.

[0453] Input: Parsed price, shipping fee, and points information (e.g., Rakuten Ichiba and Amazon information).

[0454] Output: Total amount for each candidate destination (e.g., Rakuten Market total amount: 39,500 yen, Amazon total amount: 38,600 yen).

[0455] Specific operation: The server calculates the total price (40,000 yen + 500 yen - 1,000 points = 39,500 yen) from the information on Rakuten (price 40,000 yen, shipping 500 yen, points 1,000), and the total price (39,000 yen + 400 yen - 800 points = 38,600 yen) from the information on Amazon (price 39,000 yen, shipping 400 yen, points 800).

[0456] Step 5:

[0457] The server compares the calculated totals and determines the most economical purchase.

[0458] Input: Total amount for each candidate (e.g., Rakuten Market total amount: 39,500 yen, Amazon total amount: 38,600 yen).

[0459] Output: Information on the most economical place to buy (e.g. Amazon is the most economical).

[0460] Specific operation: The server compares the total price of each candidate and selects the purchase destination (Amazon) with the lowest total price.

[0461] Step 6:

[0462] The server then sends the information on the most economical purchasing source to the user's device, which receives the information and displays it on the screen.

[0463] Input: Information on the most economical place to purchase (e.g., Amazon is the most economical).

[0464] Output: The result displayed on the user's screen (e.g., "Buying from Amazon is the best deal. Price: 39,000 yen, Shipping: 400 yen, Points: 800 points").

[0465] Specific operation: The server returns information on the most economical purchasing source in JSON format as an HTTP response, and the device parses the information and displays it on the screen.

[0466] This allows users to efficiently find the most economical purchases, saving them a lot of time and effort.

[0467] (Application example 1)

[0468] 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."

[0469] In conventional e-commerce, users have to compare multiple platforms themselves, making it difficult to efficiently find the most economical place to buy. In addition, there is a lack of a way for users to easily find the best place to buy even while on the move.

[0470] 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.

[0471] In this invention, the server includes means for receiving a product search request, means for requesting product information from APIs of multiple e-commerce platforms and acquiring price, shipping fee, and earned point information, and means for calculating the total amount based on the acquired price, shipping fee, and earned point information. This allows users to easily find the most economical purchase from multiple e-commerce sites using their mobile terminals.

[0472] A "product search request" is a request sent by a user via a terminal to obtain information about a product that the user is considering purchasing.

[0473] An "e-commerce platform" is an online marketplace for buying and selling goods and services over the Internet.

[0474] "API" stands for Application Programming Interface, an interface that defines the rules and protocols for different software systems to communicate with each other.

[0475] "Price" is the amount indicating the monetary value of the item being purchased.

[0476] "Shipping fee" refers to the cost of shipping purchased items to the user.

[0477] "Earned points" are points that are awarded to users in response to purchases and can be used as monetary value for future purchases.

[0478] "Total amount" means the final payment amount, which is the product price plus shipping fee and deduction of earned points.

[0479] A "mobile terminal" is a portable communication device such as a smartphone or tablet.

[0480] "Comparison" is the act of evaluating multiple options based on their respective characteristics and determining their relative merits.

[0481] The "most economical source" is the source that will result in the lowest expenditure for the user after taking into account all costs and benefits.

[0482] This invention is a system that compares prices, shipping costs, and points earned on multiple e-commerce platforms when a user searches for a specific product, and presents the most economical purchase option. This system allows users to efficiently decide where to purchase using their mobile terminals.

[0483] 1. System Configuration

[0484] The system consists of the following elements:

[0485] User device: A portable communication device such as a smartphone or tablet. This device has an interface for inputting product search requests.

[0486] Server: A central control unit that processes product search requests, queries multiple e-commerce platforms, aggregates and compares information, and determines the best purchasing location.

[0487] Multiple e-commerce platforms: Various online marketplaces, each providing pricing, shipping, and rewards information through APIs.

[0488] 2. Data Processing and Calculations

[0489] The system requires input from users, data acquisition from multiple e-commerce platforms, and data processing and calculation.

[0490] Receiving a product search request: When a user enters a product name or product code into the device's search bar and presses the search button, the device generates a product search request and sends it to the server.

[0491] Querying API: Based on the received product search request, the server requests product information from the APIs of multiple e-commerce platforms. Specifically, it calls the APIs of each e-commerce site to obtain the price, shipping fee, and available points information for the specified product.

[0492] Data acquisition and analysis: The server receives and analyzes the product information returned from each e-commerce site. Information such as price, shipping fee, and points is extracted individually, and the data is integrated and managed.

[0493] Calculating the total price: The server calculates the total price based on the information it has received. The total price is calculated using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This allows the lowest payment price to be presented to the user.

[0494] Determining the best supplier: The server compares the calculated totals and determines the most economical supplier.

[0495] Sending the results to the user: The server sends the information on the most economical purchasing site to the user's device. The user's device receives this information and displays it on the screen. The displayed content includes the name of the recommended e-commerce site, the price, shipping fee, points information, and the total price.

[0496] 3. Specific Examples

[0497] For example, suppose a user searches for "smartphone" on their device. When the device sends a product search request to the server, the server calls the APIs of multiple online marketplaces and obtains information on price, shipping, and points from each. Based on this information, the total price is calculated and the most economical purchase destination is determined. The "optimal purchase destination" is then displayed on the user's device.

[0498] Prompt Sentence Examples

[0499] "Please tell me the price of the smartphone, shipping costs, and points earned. Also, please do the same for multiple online marketplaces."

[0500] This allows users to easily and quickly find the most economical purchase, greatly improving user convenience.

[0501] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0502] Step 1:

[0503] The user enters the product name or product code into the device's search bar and presses the search button.

[0504] This operation generates a product search request, which is then sent to the server.

[0505] Input: Product name or product code

[0506] Data processing: Generating search requests

[0507] Output: Product search request

[0508] Step 2:

[0509] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce platforms.

[0510] Specifically, the server calls the API of each platform to obtain the price, shipping fee, and earned points information for the specified product.

[0511] Input: Product search request

[0512] Data processing: Creating and sending API requests

[0513] Output: Product information from each platform

[0514] Step 3:

[0515] The server receives and analyzes the product information returned from each e-commerce platform.

[0516] Through analysis, information such as price, shipping costs, and points is extracted individually, and each piece of data is integrated and managed.

[0517] Input: Product information from the platform

[0518] Data processing: Product information analysis and integration

[0519] Output: Consolidated product information

[0520] Step 4:

[0521] The server calculates the total amount based on each piece of information obtained.

[0522] The total price is calculated using an algorithm that adds up the product price and shipping costs and deducts the points earned.

[0523] Input: Integrated product information

[0524] Data processing: Calculate total amount (price + shipping fee - points)

[0525] Output: Total amount for each platform

[0526] Step 5:

[0527] The server compares the calculated totals and determines the most economical purchase.

[0528] Here, the total price of all platforms is compared and the purchase source with the lowest total price is selected.

[0529] Input: Total amount for each platform

[0530] Data processing: Comparing total amounts and selecting the best supplier

[0531] Output: Information on the most economical purchasing source

[0532] Step 6:

[0533] The server sends information on the most economical purchasing source determined by the server to the user's terminal.

[0534] The user's device receives this information and displays it on the screen, including the name of the recommended platform, the price, shipping fee, points information, and the total amount.

[0535] Input: Information on the most economical supplier

[0536] Data processing: transmission of information

[0537] Output: Supplier information displayed on the user's device

[0538] 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.

[0539] This invention relates to a system that provides product search results on an e-commerce platform while taking into account the user's emotions. In addition to the basic function of obtaining the price, shipping fee, and points for a product specified by the user from an e-commerce site and presenting the most economical purchasing options, this system also recognizes the user's emotions and filters or sorts the search results based on those emotions.

[0540] 1. Receiving a product search request

[0541] When a user enters a product name or product code into the device's search bar and presses the search button, the device generates a product search request and sends it to the server. At this time, the device uses a camera and microphone to record the user's facial expressions and voice, and analyzes them with an emotion engine in order to simultaneously recognize the user's emotions.

[0542] 2. Emotion recognition using an emotion engine

[0543] The device sends the user's facial and voice data to the emotion engine, which then analyzes the data to recognize the user's emotions. Emotions are classified into positive, negative, and neutral categories. For example, if the user is smiling, the emotion engine recognizes the emotion as positive.

[0544] 3. Querying APIs of multiple e-commerce platforms

[0545] Based on the product search request, the server requests product information from the APIs of multiple e-commerce sites. The server then sends a request including the extracted product name and product code to the API endpoint of each e-commerce site.

[0546] 4. Obtaining price, shipping and point information

[0547] The API of each e-commerce platform returns product information, which is received and analyzed by the server. The server extracts the price, shipping fee, and earned points from the JSON data and integrates and manages the data.

[0548] 5. Calculation of total amount

[0549] The server calculates the total amount based on the price, shipping cost, and earned points information. The calculation uses an algorithm that adds up the product price and shipping cost and subtracts the earned points. For example, if the price on Rakuten Market is 40,000 yen, shipping cost is 500 yen, and the points are 1,000, the total amount will be (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0550] 6. Emotional purchasing decisions

[0551] The server compares the calculated totals and determines the most economical purchase. The user's emotional data is also taken into account. For example, if the user is expressing positive emotions, other factors (high reviews, fast delivery, etc.) that are comparable in price and shipping costs are also taken into account.

[0552] 7. Sending results to the user

[0553] The server sends information about the most economical shopping destination to the user's device. This information includes the selected shopping destination, price, shipping fee, points, and the reason for the recommendation based on emotion. For example, for a user who expresses positive emotion, the recommendation may include "This product has high ratings and will arrive quickly."

[0554] Specific examples

[0555] For example, suppose a user searches for "smartphone" on their device and smiles at the camera. The device sends a product search request to the server, and at the same time, the emotion engine analyzes the user's positive emotions. The server then calls the APIs of Rakuten Ichiba and Amazon to retrieve their respective information.

[0556] On Rakuten, the price is 40,000 yen, shipping is 500 yen, and points are 1,000, for a total of 39,500 yen, while on Amazon, the price is 39,000 yen, shipping is 400 yen, and points are 800, for a total of 38,600 yen. Because the user is smiling, which is recognized as a positive emotion, the server takes into account review ratings and delivery time, and selects Amazon, which has the highest enthusiastic ratings and is expected to deliver quickly.

[0557] Ultimately, the user's device will display a result such as, "Buying from Amazon is the best deal. Price: 39,000 yen, shipping: 400 yen, points: 800 points. High reviews and fast delivery."

[0558] This system allows users to efficiently and emotionally select the best shopping destination, improving their shopping experience.

[0559] The processing flow will be explained below.

[0560] Step 1:

[0561] The user enters the product name or product code into the device's search bar and presses the search button. The device generates a product search request based on this information and sends it to the server. At the same time, the device uses the camera and microphone to record the user's facial expressions and voice, and sends them to the emotion engine.

[0562] Step 2:

[0563] The emotion engine analyzes the user's recorded facial expressions and voice and classifies the user's emotion as positive, negative, or neutral. For example, if the user is smiling, the emotion engine will recognize it as positive.

[0564] Step 3:

[0565] The server receives the product search request sent from the terminal and extracts the product name and product code from the request body.

[0566] Step 4:

[0567] The server requests product information from the APIs of multiple e-commerce platforms. Specifically, it sends a request including the product name and product code to an API endpoint and makes a call to each platform to retrieve the data.

[0568] Step 5:

[0569] The API of each e-commerce platform returns product information. For example, Rakuten Ichiba returns data such as a price of 40,000 yen, shipping cost of 500 yen, and 1,000 points, while Amazon returns data such as a price of 39,000 yen, shipping cost of 400 yen, and 800 points.

[0570] Step 6:

[0571] The server analyzes the responses received from each platform and extracts the price, shipping fee, and earned points. The extracted data is organized and managed for each e-commerce platform.

[0572] Step 7:

[0573] The server calculates the total amount based on the price, shipping cost, and earned points information it has obtained. The server performs the calculation as follows: (price + shipping cost) - earned points. For example, in the case of Rakuten Ichiba, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen, and in the case of Amazon, it is (39,000 yen + 400 yen) - 800 points = 38,600 yen.

[0574] Step 8:

[0575] The server determines the most economical purchase based on the calculated total amount. Here, the user's emotional data is also taken into consideration. For example, if the user has a positive emotion, additional information such as product reviews and delivery speed is also included in the purchase decision.

[0576] Step 9:

[0577] The server sends information about the most economical purchasing destination to the user's device. This information includes the selected purchasing destination, price, shipping fee, points, and emotional reasons for the recommendation. For example, a result such as "Buying from Amazon is the best deal. Price: 39,000 yen, shipping fee: 400 yen, points: 800 points. It has high reviews and offers fast delivery" is sent.

[0578] Step 10:

[0579] The terminal receives the response from the server and analyzes it. The analyzed results are then displayed on the screen in a format that is easy for the user to understand. This allows the user to select the most economical and satisfying purchasing source.

[0580] The above is the specific processing flow of this system. By combining emotion engines, it is possible to make optimal product suggestions and purchase decisions based on the user's emotions.

[0581] Example 2

[0582] 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."

[0583] Conventional e-commerce platforms provide product search results based mainly on price, shipping costs, and points, and are unable to provide search results that take into account the user's emotions and purchasing intentions. This has led to a decrease in user purchasing satisfaction. There is also a need for a system that not only presents the most economical purchasing options, but also provides optimal search results that reflect the user's emotions.

[0584] 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 means for receiving a product search request, means for requesting product information from the APIs of multiple e-commerce platforms and acquiring information on prices, shipping costs, and earned points, means for calculating a total amount based on the acquired price, shipping costs, and earned points information, means for comparing the calculated total amounts and determining the most economical purchasing destination, means for recognizing user emotions, means for filtering or sorting search results based on the recognized user emotions, and means for outputting information on the determined purchasing destination. This makes it possible to select an optimal purchasing destination taking user emotions into consideration and provide high purchasing satisfaction.

[0585] A "product search request" is a request to the server to search for product information, which is generated when a user inputs a product name or product code into a terminal and presses a search button.

[0586] An "e-commerce platform" is an internet-based marketplace that connects multiple sellers and buyers, where goods and services are bought and sold.

[0587] "API" stands for Application Programming Interface, an interface for communication and data exchange between different software systems.

[0588] "Product Information" refers to data including product prices, shipping fees, points, and other related information.

[0589] "Price" refers to the amount of money required to purchase a particular product.

[0590] "Shipping cost" means the cost of transportation required to deliver the product.

[0591] "Earned points" are points awarded when purchasing a product, and can be used to purchase products or services at a later date.

[0592] "Total amount" refers to the actual amount to be paid, calculated by adding the product price and shipping fee and deducting the points earned.

[0593] "Emotions" indicate the user's psychological state and are classified into positive, negative, and neutral categories.

[0594] An "emotion engine" is software that analyzes a user's facial expressions and voice data to recognize the user's emotions.

[0595] "Filtering" is the operation of narrowing down data based on specific conditions.

[0596] "Sorting" is an operation for rearranging data in order based on specific conditions.

[0597] "Destination" refers to the e-commerce platform or merchant from which a user chooses to purchase goods.

[0598] "Search results" refers to a list of product information displayed in response to a user's search request.

[0599] This invention relates to a system that provides product search results on an e-commerce platform while taking user emotions into consideration. In addition to the basic function of obtaining the price, shipping fee, and points of a product specified by a user from an e-commerce site and presenting the most economical purchasing options, the system also recognizes the user's emotions and filters or sorts the search results based on those emotions.

[0600] The system includes means for receiving a product search request, means for requesting product information from APIs of multiple e-commerce platforms and obtaining information on prices, shipping fees, and earned points, means for calculating a total amount based on the obtained information on prices, shipping fees, and earned points, means for comparing the calculated total amounts and determining the most economical purchasing destination, means for recognizing user emotions, means for filtering or sorting search results based on the recognized user emotions, and means for outputting information on the determined purchasing destination.

[0601] The device generates a product search request based on the user's input and sends it to the server. The device is equipped with a search bar, camera, and microphone to record the user's facial expressions and voice. Specifically, the device's camera and microphone are used to monitor the user's facial expressions and voice in real time, and this data is sent to the emotion engine. The emotion engine uses a machine learning model to classify the user's emotion as positive, negative, or neutral.

[0602] The server sends a product information request to the APIs of multiple e-commerce platforms (e.g., major domestic e-commerce platforms and major international e-commerce platforms) based on the product search request received from the terminal. The product information obtained from the APIs of each platform is sent in JSON format or other data format, and includes the price, shipping fee, and earned points.

[0603] The server analyzes and extracts the price, shipping cost, and earned points from the API responses received from each platform, and calculates the total amount. This calculation uses an algorithm that adds up the price and shipping cost and subtracts the earned points. For example, on Rakuten Ichiba, if the price is 40,000 yen, shipping cost is 500 yen, and the points are 1,000, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0604] The server compares the calculated totals and considers the user's emotional data when determining the most economical purchasing platform. For example, if the user has a positive emotional state, the server will recommend a platform with high reviews and fast delivery by considering other factors (such as high reviews and fast delivery) with comparable prices and shipping costs.

[0605] The server sends information on the most economical and emotionally-based purchasing destinations to the user's terminal. This information includes the selected purchasing destination, price, shipping fee, points, and the reason for the recommendation based on emotion. For example, if the user has a positive emotion, the server can include a message such as "This product is highly rated and will arrive quickly."

[0606] Examples of prompts include:

[0607] "When a user smiles and searches their smartphone, choose the e-commerce site that offers the best deal and fastest delivery."

[0608] This system allows users to efficiently and emotionally select the best shopping destination, improving their shopping experience.

[0609] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0610] Step 1: Generate and submit a product search request

[0611] Input: The user enters the product name or product code into the device's search bar and presses the search button.

[0612] Specific operation: The user enters the product name (e.g., "smartphone") into the input form on the device and clicks the search button.

[0613] Data processing and calculation: The terminal generates a product search request based on the user's input and sends it to the server in the form of an HTTP request.

[0614] Output: Get the product search request received by the server.

[0615] Step 2: Acquire and analyze user emotion data

[0616] Input: At the same time as sending a product search request, the device's camera and microphone record the user's facial expressions and voice.

[0617] Specific operation: The device captures the user's facial expressions and voice in real time using the camera and microphone.

[0618] Data processing and calculation: The facial expression and voice data collected by the device is sent to the emotion engine, which uses a machine learning model to classify the user's emotion as positive, negative, or neutral.

[0619] Output: Classified emotion data is sent to the server.

[0620] Step 3: Request product information from the e-commerce platform

[0621] Input: Product search request sent from the device.

[0622] Specific operation: Based on the product search request, the server sends HTTP requests to the APIs of multiple e-commerce platforms.

[0623] Data processing and calculation: The API request includes the product name and product code, and the response is received from each platform in JSON format or other data format.

[0624] Output: Product information returned from each e-commerce platform.

[0625] Step 4: Obtain and analyze price, shipping, and points information

[0626] Input: The API response returned by the e-commerce platform.

[0627] Specific operation: The server analyzes the API response received and extracts the necessary data (price, shipping fee, points).

[0628] Data processing and calculation: The server extracts the price, shipping fee, and points from the JSON data in a unique format, and organizes and integrates them.

[0629] Output: Organized price, shipping, and points information.

[0630] Step 5: Calculate the total purchase amount

[0631] Input: Obtained price, shipping, and points information.

[0632] Specific operation: The server uses this data to calculate the total amount.

[0633] Data processing and calculation: An algorithm is used to add up the price and shipping cost and deduct points. For example, if the price is 40,000 yen, the shipping cost is 500 yen, and the points are 1,000 points, the total will be (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0634] Output: Calculated gross amount data.

[0635] Step 6: Emotional purchasing decisions

[0636] Input: Calculated total amount data and user sentiment data.

[0637] Specific operation: The server compares the total amount data and determines the most appropriate purchasing destination taking into account the user's feelings.

[0638] Data processing and calculation: For users who show positive sentiment, other factors such as review ratings and delivery times are taken into account.

[0639] Output: Information on the most appropriate purchasing platform (platform name, price, shipping fee, points, reason for recommendation).

[0640] Step 7: Send supplier information to users

[0641] Input: Determined supplier information.

[0642] Specific operation: The server transmits the determined supplier information to the terminal.

[0643] Data processing and calculation: Formatting information including the reason for recommendation (e.g., "high reviews and fast delivery expected").

[0644] Output: Information on the best places to buy displayed on the user's device.

[0645] (Application example 2)

[0646] 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."

[0647] Conventional e-commerce systems provide product search results without considering the user's feelings, making it difficult to optimize the user's purchasing experience. In particular, determining the most economical purchasing destination without considering the user's feelings about the searched product can reduce user satisfaction.

[0648] 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.

[0649] In this invention, the server includes means for receiving a product search request, means for requesting product information from the APIs of multiple e-commerce platforms and acquiring information on prices, shipping costs, and earned points, means for calculating the total amount based on the acquired price, shipping costs, and earned points, means for determining the most economical and suitable purchasing destination based on the calculated total amount and the user's emotions, means for outputting information on the determined purchasing destination, and means for acquiring the user's facial expressions and voice data using a camera and microphone and analyzing them with an emotion engine. This makes it possible to present the most suitable purchasing destination taking the user's emotions into consideration.

[0650] The "means for receiving a product search request" is a function that sends a product search request generated by the terminal to the server when a user inputs a product name or product code into the search bar and presses the search button.

[0651] "Means for requesting product information from the APIs of multiple e-commerce platforms and obtaining information on prices, shipping fees, and earned points" refers to a function in which a server sends requests to the API endpoints of multiple e-commerce platforms and obtains the product information of each.

[0652] The "means for calculating the total amount based on the acquired price, shipping fee, and earned point information" is a function that the server uses the price, shipping fee, and earned point information acquired from each e-commerce platform to calculate the total amount.

[0653] "Means for determining the most economical and suitable purchasing source based on the calculated total amount and the user's emotions" is a function that selects the most suitable purchasing source by taking into consideration the total amount calculated by the server and the user's emotional data.

[0654] The "means for outputting information on the determined supplier" is a function by which the server notifies the user of information on the most suitable supplier.

[0655] "Means for acquiring the user's facial expressions and voice data using a camera and microphone and analyzing it with an emotion engine" refers to a function that acquires the user's facial images and voice, sends them to the emotion engine for analysis, and recognizes the user's emotions.

[0656] The "emotion engine" is a system that analyzes the user's facial expressions and voice data and classifies them into emotional categories such as positive, negative, and neutral.

[0657] "Total Calculation" is the process of adding up the acquired price and shipping costs and subtracting earned points to determine the actual total cost of the item.

[0658] This invention relates to an electronic commerce system that provides product search results taking into account the user's emotions. When a user makes a product search request via a terminal, the system recognizes the user's emotions and presents the most suitable purchasing destination. This section explains each processing step for recognizing the user's emotions and presenting the most suitable purchasing destination.

[0659] System Configuration

[0660] 1. Hardware and Software:

[0661] Device: A device such as a smartphone or tablet that has a built-in camera and microphone.

[0662] Server: A central server for accessing APIs of multiple e-commerce platforms.

[0663] Emotion engine: A software library for analyzing a user's facial expressions and voice and classifying them into emotional categories.

[0664] Flask: Used as a web application framework.

[0665] Requests: A Python library for sending HTTP requests.

[0666] Program processing overview

[0667] The device generates a product search request and sends it to the server. When the user enters a product name or code into the search bar and presses the search button, the device uses a camera and microphone to record the user's facial expressions and voice data. This data is sent to the emotion engine, which classifies the user's emotion as positive, negative, or neutral.

[0668] The server requests product information from the APIs of multiple e-commerce platforms. It calculates the total price based on the obtained price, shipping cost, and earned points information, and also combines the user's emotional data to determine the most economical and suitable purchasing destination. Finally, the server sends the information of the selected purchasing destination to the user's device.

[0669] Specific examples

[0670] For example, if a user searches for "smartphone" on their device, the device records image data and audio of them smiling at the camera. This data is analyzed by the emotion engine and recognized as a positive emotion. The server then retrieves product data from multiple e-commerce platforms, comparing it with information such as a price of ¥40,000, shipping of ¥500, 1,000 points, and a total of ¥39,500 on Rakuten, or a price of ¥39,000, shipping of ¥400, 800 points, and a total of ¥38,600 on Amazon.

[0671] Because the user's sentiment is positive, the server selects the optimal purchasing source by taking into consideration not only price and shipping costs, but also reviews and delivery time. In this case, the server selects Amazon, which has high reviews and is expected to deliver quickly, and sends that information to the user's device.

[0672] Prompt Sentence Examples

[0673] The prompt text that is entered when a user searches for "smartphone" is as follows:

[0674] Text input: "Smartphone"

[0675] Emotion data: image data and audio data (indicating a smile)

[0676] This allows users to quickly and efficiently select the best place to purchase products based on their emotions, significantly improving the user's purchasing experience.

[0677] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0678] Step 1:

[0679] The user enters the product name or product code into the search bar of the device and presses the search button. At this time, the device's camera and microphone record the user's facial expression and voice data. The input data, which is the product name and the user's facial expression and voice data, is sent to the subsequent processing step.

[0680] Step 2:

[0681] The device sends the user's facial and voice data to the emotion engine, which analyzes it to recognize the user's emotions. Emotional data is classified as positive, negative, or neutral. The input data is the user's facial and voice data, and the output data is the emotion category (positive, negative, or neutral).

[0682] Step 3:

[0683] Based on the product search request, the server requests product information from the API endpoints of multiple e-commerce platforms. The input data is the product name, and the request is sent to each platform. The output data is the price, shipping fee, and earned points information obtained from each platform.

[0684] Step 4:

[0685] The server calculates the total amount based on the acquired price, shipping fee, and earned point information. The total amount is the sum of the price and shipping fee and the earned point amount. The input data are the price, shipping fee, and earned point information, and the output data is the calculated total amount.

[0686] Step 5:

[0687] The server determines the most economical and suitable purchasing destination based on the calculated total price and the user's sentiment. If the sentiment data is positive, it also takes into account reviews and delivery time in addition to price and shipping costs. The input data are the calculated total price and sentiment data, and the output data is information on the optimal purchasing destination.

[0688] Step 6:

[0689] The server sends the information on the optimal supplier it has determined to the user's terminal, which then displays this information to the user. The input data is the optimal supplier information, and the output data is the supplier information displayed to the user.

[0690] For example, if a user searches for "smartphone" and smiles at the camera, the device sends that data to the emotion engine, which recognizes it as a positive emotion. The server then retrieves product information from multiple platforms, calculates the total price, and determines the optimal purchasing source, taking into account the emotion data. In this case, the server selects a platform with high reviews and the potential for fast delivery, and notifies the user of that information.

[0691] Through the above steps, the user can quickly select the most suitable place to purchase products according to their emotions.

[0692] 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.

[0693] 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.

[0694] 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.

[0695] [Third embodiment]

[0696] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0697] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0698] 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).

[0699] 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.

[0700] 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.

[0701] 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).

[0702] 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.

[0703] 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.

[0704] 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.

[0705] 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.

[0706] 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.

[0707] 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."

[0708] This invention relates to a system that compares the prices, shipping costs, and points earned on multiple e-commerce platforms (EC sites) when a user searches for a specific product, and presents the most economical purchase option. This system is implemented using the following means.

[0709] 1. Receiving a product search request

[0710] When a user enters a product name or product code into the search bar of the device and presses the search button, the device generates a product search request and sends it to the server, which then receives the product search request.

[0711] 2. Querying APIs of multiple e-commerce platforms

[0712] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce sites. Specifically, it calls the APIs of each e-commerce site to obtain the price, shipping fee, and earnable points information for the specified product.

[0713] 3. Obtaining price, shipping and point information

[0714] The server receives and analyzes the product information returned from each e-commerce site, extracting information such as price, shipping fee, and points, and then integrates and manages the data.

[0715] 4. Calculation of total amount

[0716] The server calculates the total price based on the information it has received. The total price is calculated using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This allows the lowest payment amount presented to the user.

[0717] 5. Determine the most economical purchase source

[0718] The server compares the calculated totals and determines the most economical purchase. The comparison is not a simple price comparison, but a comparison of the total amount taking into account all factors (price, shipping, points).

[0719] 6. Sending results to users

[0720] The server sends the information on the most economical purchasing site determined by the server to the user's device. The user's device receives this information and displays it on the screen. The displayed content includes the name of the recommended e-commerce site, the price, shipping fee, points information, and the total price.

[0721] Specific examples

[0722] For example, suppose a user searches for "smartphone" on their device. When the device sends a product search request to the server, the server calls the APIs of Rakuten Ichiba and Amazon to retrieve information from each. Rakuten Ichiba retrieves information such as price: 40,000 yen, shipping: 500 yen, and points: 1,000, while Amazon retrieves information such as price: 39,000 yen, shipping: 400 yen, and points: 800.

[0723] The server calculates the total amount based on this information. In the case of Rakuten Ichiba, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen. On the other hand, in the case of Amazon, the total amount is (39,000 yen + 400 yen) - 800 points = 38,600 yen.

[0724] The server compares these total prices and determines Amazon as the most economical place to purchase. Finally, the user's device displays the result: "Buying from Amazon is the best deal. Price: 39,000 yen, Shipping: 400 yen, Points: 800 points."

[0725] The above is an embodiment of the present invention. This system allows users to efficiently find the most economical purchase source, thereby saving a lot of time and effort.

[0726] The processing flow will be explained below.

[0727] Step 1:

[0728] The user enters the product name or product code into the search bar on the device and presses the search button. The device generates a product search request based on the input information and sends it to the server.

[0729] Step 2:

[0730] The server receives the product search request sent from the terminal and extracts the product name and product code from the request body.

[0731] Step 3:

[0732] The server requests product information from the APIs of multiple e-commerce platforms, and then sends a request including the extracted product name and product code to the API endpoint of each e-commerce site.

[0733] Step 4:

[0734] The API of each e-commerce platform returns product information. For example, the response from Rakuten Ichiba and Amazon returns the price, shipping fee, and earned points information in JSON format.

[0735] Step 5:

[0736] The server receives and analyzes responses from each e-commerce platform, extracts price, shipping fee, and earned points from the JSON data, and manages all of this data together.

[0737] Step 6:

[0738] The server calculates the total amount based on the price, shipping fee, and earned points information. The server performs the following calculation for each e-commerce site: (price + shipping fee) - earned points. For example, in the case of Rakuten Ichiba, the total amount is (price 40,000 yen + shipping fee 500 yen) - 1,000 points = 39,500 yen.

[0739] Step 7:

[0740] The server determines the most economical purchase destination based on the total amount calculated. The server compares multiple total amounts and selects the purchase destination with the lowest total amount. For example, since the total amount on Amazon is 38,600 yen, Amazon is selected.

[0741] Step 8:

[0742] The server sends information about the most economical shopping destination to the user's terminal. The server generates a response containing detailed information about the selected shopping destination (price, shipping fee, points, total amount) and returns it to the terminal.

[0743] Step 9:

[0744] The device receives a response from the server. The device analyzes the received data and displays it on the screen in a format that is easy for the user to understand. For example, it might say, "Buying from Amazon is the best deal. Price: 39,000 yen, shipping: 400 yen, points: 800 points."

[0745] The above is the specific processing flow of this system, which allows users to easily find the most economical purchasing site from multiple e-commerce sites.

[0746] Example 1

[0747] 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."

[0748] In conventional e-commerce, users have to visit multiple e-commerce sites individually to compare prices, shipping costs, and points earned, which takes a lot of time and effort.In addition, there is also the problem that information needed to find the most economical purchase is scattered, making it difficult for users to make the best choice.

[0749] 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.

[0750] In this invention, the server includes means for receiving a product search request, means for requesting product information from data acquisition interfaces of multiple e-commerce sites and acquiring information on prices, shipping fees, and earned points, means for calculating a total amount based on the acquired information on prices, shipping fees, and earned points, means for comparing the calculated total amounts and determining the most economical purchasing source, and means for outputting information on the determined purchasing source, thereby enabling users to efficiently find the most economical purchasing source.

[0751] "Product Search Request" means a request containing information entered by a user to search for a particular product.

[0752] An "e-commerce site" is a platform for selling goods and services over the Internet.

[0753] A "data acquisition interface" is a program interface for communicating with an external system to acquire information.

[0754] "Product information" refers to detailed information such as product price, shipping fee, and earned points.

[0755] "Price" refers to the amount you pay to purchase a particular item.

[0756] "Shipping Costs" means any additional costs required to deliver a Product.

[0757] "Earned points" are points that can be acquired when purchasing a product and can be used for subsequent purchases.

[0758] "Total amount" refers to the final payment amount, which is the sum of the product price and shipping fee, minus the points earned.

[0759] The "most economical place to buy" is the site with the lowest total price and the most economical for the user.

[0760] "Means for outputting information" refers to a method or device for displaying or providing the processing results to the user.

[0761] This invention is a system that compares prices, shipping costs, and points earned on multiple e-commerce sites when a user searches for a specific product, and presents the most economical purchasing source. The following is a specific embodiment for implementing this system.

[0762] First, the user enters the product name or product code into the search bar of the device and presses the search button. This operation causes the device to generate a product search request and send it to the server. The server receives this product search request and requests product information from the data acquisition interfaces of multiple e-commerce sites (e.g., major domestic e-commerce sites and major international e-commerce sites).

[0763] Specifically, the server calls the API of each e-commerce site to obtain the price, shipping cost, and available points for the specified product. This process can use APIs such as those of Rakuten Ichiba or Amazon. The server receives the product information returned from each e-commerce site and parses it in JSON format. Information such as price, shipping cost, and points is extracted individually, and the data is integrated and managed.

[0764] The server then calculates the total amount based on the information obtained. This calculation is performed using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This ensures that the lowest payment amount is presented to the user. For example, consider a case where a price of 40,000 yen, shipping cost of 500 yen, and 1,000 points are obtained on Rakuten Market, and a price of 39,000 yen, shipping cost of 400 yen, and 800 points are obtained on a major international e-commerce site.

[0765] The server calculates the total price based on this information. In the case of Rakuten Ichiba, the total price is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen, and in the case of the major international e-commerce site, the total price is (39,000 yen + 400 yen) - 800 points = 38,600 yen. The server compares these total prices and determines the major international e-commerce site as the most economical purchase destination.

[0766] Finally, the server sends the information on the most economical purchasing site to the user's device. The device receives this information and displays it on the screen. The displayed information includes the name of the recommended e-commerce site, price, shipping fee, points information, and total amount. For example, the result may read, "Purchasing from a major international e-commerce site is the best value. Price: 39,000 yen, shipping fee: 400 yen, points: 800 points."

[0767] This system allows users to efficiently find the most economical purchases, thereby saving a lot of time and effort.

[0768] Examples of prompts include:

[0769] "I want to build a system that allows users to search for a specific product and compares prices, shipping costs, and reward points across multiple e-commerce sites to suggest the most economical purchase. Please explain the process by following these steps."

[0770] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0771] Step 1:

[0772] The user enters the product name or product code in the search bar of the device and presses the search button. This operation causes the device to generate a product search request and send it to the server.

[0773] Input: The product name or code entered by the user (e.g., "smartphone").

[0774] Output: Product search request (e.g., search request for "smartphone").

[0775] Specific operation: When a user enters "smartphone" and presses the search button, the device sends an HTTP POST request to the server, which includes the search key ("smartphone").

[0776] Step 2:

[0777] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce sites.

[0778] Input: Product search request (e.g., search request for "smartphone").

[0779] Output: Product information requests from each e-commerce site (e.g., requests to Rakuten Ichiba and Amazon).

[0780] Specific operation: The server analyzes the product search request and sends an HTTP GET request to the Rakuten Ichiba or Amazon API. The request includes the API key and search key.

[0781] Step 3:

[0782] The server receives and analyzes product information returned from multiple e-commerce sites, extracting individual data such as price, shipping fee, and points, and then integrates and manages them.

[0783] Input: Product information returned from each e-commerce site (e.g., responses from Rakuten Ichiba and Amazon).

[0784] Output: Parsed price, shipping fee, and points information (e.g., Rakuten Ichiba price: 40,000 yen, shipping fee: 500 yen, points: 1,000 points).

[0785] Specific operation: The server receives API responses from Rakuten Ichiba and Amazon in JSON format, extracts price, shipping fee, and points information, and stores the extracted information in an internal data structure.

[0786] Step 4:

[0787] The server calculates the total amount based on the information it has received, adding up the product price and shipping costs and using an algorithm to deduct the points earned.

[0788] Input: Parsed price, shipping fee, and points information (e.g., Rakuten Ichiba and Amazon information).

[0789] Output: Total amount for each candidate destination (e.g., Rakuten Market total amount: 39,500 yen, Amazon total amount: 38,600 yen).

[0790] Specific operation: The server calculates the total price (40,000 yen + 500 yen - 1,000 points = 39,500 yen) from the information on Rakuten (price 40,000 yen, shipping 500 yen, points 1,000), and the total price (39,000 yen + 400 yen - 800 points = 38,600 yen) from the information on Amazon (price 39,000 yen, shipping 400 yen, points 800).

[0791] Step 5:

[0792] The server compares the calculated totals and determines the most economical purchase.

[0793] Input: Total amount for each candidate (e.g., Rakuten Market total amount: 39,500 yen, Amazon total amount: 38,600 yen).

[0794] Output: Information on the most economical place to buy (e.g. Amazon is the most economical).

[0795] Specific operation: The server compares the total price of each candidate and selects the purchase destination (Amazon) with the lowest total price.

[0796] Step 6:

[0797] The server then sends the information on the most economical purchasing source to the user's device, which receives the information and displays it on the screen.

[0798] Input: Information on the most economical place to purchase (e.g., Amazon is the most economical).

[0799] Output: The result displayed on the user's screen (e.g., "Buying from Amazon is the best deal. Price: 39,000 yen, Shipping: 400 yen, Points: 800 points").

[0800] Specific operation: The server returns information on the most economical purchasing source in JSON format as an HTTP response, and the device parses the information and displays it on the screen.

[0801] This allows users to efficiently find the most economical purchases, saving them a lot of time and effort.

[0802] (Application example 1)

[0803] 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."

[0804] In conventional e-commerce, users have to compare multiple platforms themselves, making it difficult to efficiently find the most economical place to buy. In addition, there is a lack of a way for users to easily find the best place to buy even while on the move.

[0805] 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.

[0806] In this invention, the server includes means for receiving a product search request, means for requesting product information from APIs of multiple e-commerce platforms and acquiring price, shipping fee, and earned point information, and means for calculating the total amount based on the acquired price, shipping fee, and earned point information. This allows users to easily find the most economical purchase from multiple e-commerce sites using their mobile terminals.

[0807] A "product search request" is a request sent by a user via a terminal to obtain information about a product that the user is considering purchasing.

[0808] An "e-commerce platform" is an online marketplace for buying and selling goods and services over the Internet.

[0809] "API" stands for Application Programming Interface, an interface that defines the rules and protocols for different software systems to communicate with each other.

[0810] "Price" is the amount indicating the monetary value of the item being purchased.

[0811] "Shipping fee" refers to the cost of shipping purchased items to the user.

[0812] "Earned points" are points that are awarded to users in response to purchases and can be used as monetary value for future purchases.

[0813] "Total amount" means the final payment amount, which is the product price plus shipping fee and deduction of earned points.

[0814] A "mobile terminal" is a portable communication device such as a smartphone or tablet.

[0815] "Comparison" is the act of evaluating multiple options based on their respective characteristics and determining their relative merits.

[0816] The "most economical source" is the source that will result in the lowest expenditure for the user after taking into account all costs and benefits.

[0817] This invention is a system that compares prices, shipping costs, and points earned on multiple e-commerce platforms when a user searches for a specific product, and presents the most economical purchase option. This system allows users to efficiently decide where to purchase using their mobile terminals.

[0818] 1. System Configuration

[0819] The system consists of the following elements:

[0820] User device: A portable communication device such as a smartphone or tablet. This device has an interface for inputting product search requests.

[0821] Server: A central control unit that processes product search requests, queries multiple e-commerce platforms, aggregates and compares information, and determines the best purchasing location.

[0822] Multiple e-commerce platforms: Various online marketplaces, each providing pricing, shipping, and rewards information through APIs.

[0823] 2. Data Processing and Calculations

[0824] The system requires input from users, data acquisition from multiple e-commerce platforms, and data processing and calculation.

[0825] Receiving a product search request: When a user enters a product name or product code into the device's search bar and presses the search button, the device generates a product search request and sends it to the server.

[0826] Querying API: Based on the received product search request, the server requests product information from the APIs of multiple e-commerce platforms. Specifically, it calls the APIs of each e-commerce site to obtain the price, shipping fee, and available points information for the specified product.

[0827] Data acquisition and analysis: The server receives and analyzes the product information returned from each e-commerce site. Information such as price, shipping fee, and points is extracted individually, and the data is integrated and managed.

[0828] Calculating the total price: The server calculates the total price based on the information it has received. The total price is calculated using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This allows the lowest payment price to be presented to the user.

[0829] Determining the best supplier: The server compares the calculated totals and determines the most economical supplier.

[0830] Sending the results to the user: The server sends the information on the most economical purchasing site to the user's device. The user's device receives this information and displays it on the screen. The displayed content includes the name of the recommended e-commerce site, the price, shipping fee, points information, and the total price.

[0831] 3. Specific Examples

[0832] For example, suppose a user searches for "smartphone" on their device. When the device sends a product search request to the server, the server calls the APIs of multiple online marketplaces and obtains information on price, shipping, and points from each. Based on this information, the total price is calculated and the most economical purchase destination is determined. The "optimal purchase destination" is then displayed on the user's device.

[0833] Prompt Sentence Examples

[0834] "Please tell me the price of the smartphone, shipping costs, and points earned. Also, please do the same for multiple online marketplaces."

[0835] This allows users to easily and quickly find the most economical purchase, greatly improving user convenience.

[0836] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0837] Step 1:

[0838] The user enters the product name or product code into the device's search bar and presses the search button.

[0839] This operation generates a product search request, which is then sent to the server.

[0840] Input: Product name or product code

[0841] Data processing: Generating search requests

[0842] Output: Product search request

[0843] Step 2:

[0844] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce platforms.

[0845] Specifically, the server calls the API of each platform to obtain the price, shipping fee, and earned points information for the specified product.

[0846] Input: Product search request

[0847] Data processing: Creating and sending API requests

[0848] Output: Product information from each platform

[0849] Step 3:

[0850] The server receives and analyzes the product information returned from each e-commerce platform.

[0851] Through analysis, information such as price, shipping costs, and points is extracted individually, and each piece of data is integrated and managed.

[0852] Input: Product information from the platform

[0853] Data processing: Product information analysis and integration

[0854] Output: Consolidated product information

[0855] Step 4:

[0856] The server calculates the total amount based on each piece of information obtained.

[0857] The total price is calculated using an algorithm that adds up the product price and shipping costs and deducts the points earned.

[0858] Input: Integrated product information

[0859] Data processing: Calculate total amount (price + shipping fee - points)

[0860] Output: Total amount for each platform

[0861] Step 5:

[0862] The server compares the calculated totals and determines the most economical purchase.

[0863] Here, the total price of all platforms is compared and the purchase source with the lowest total price is selected.

[0864] Input: Total amount for each platform

[0865] Data processing: Comparing total amounts and selecting the best supplier

[0866] Output: Information on the most economical purchasing source

[0867] Step 6:

[0868] The server sends information on the most economical purchasing source determined by the server to the user's terminal.

[0869] The user's device receives this information and displays it on the screen, including the name of the recommended platform, the price, shipping fee, points information, and the total amount.

[0870] Input: Information on the most economical supplier

[0871] Data processing: transmission of information

[0872] Output: Supplier information displayed on the user's device

[0873] 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.

[0874] This invention relates to a system that provides product search results on an e-commerce platform while taking into account the user's emotions. In addition to the basic function of obtaining the price, shipping fee, and points for a product specified by the user from an e-commerce site and presenting the most economical purchasing options, this system also recognizes the user's emotions and filters or sorts the search results based on those emotions.

[0875] 1. Receiving a product search request

[0876] When a user enters a product name or product code into the device's search bar and presses the search button, the device generates a product search request and sends it to the server. At this time, the device uses a camera and microphone to record the user's facial expressions and voice, and analyzes them with an emotion engine in order to simultaneously recognize the user's emotions.

[0877] 2. Emotion recognition using an emotion engine

[0878] The device sends the user's facial and voice data to the emotion engine, which then analyzes the data to recognize the user's emotions. Emotions are classified into positive, negative, and neutral categories. For example, if the user is smiling, the emotion engine recognizes the emotion as positive.

[0879] 3. Querying APIs of multiple e-commerce platforms

[0880] Based on the product search request, the server requests product information from the APIs of multiple e-commerce sites. The server then sends a request including the extracted product name and product code to the API endpoint of each e-commerce site.

[0881] 4. Obtaining price, shipping and point information

[0882] The API of each e-commerce platform returns product information, which is received and analyzed by the server. The server extracts the price, shipping fee, and earned points from the JSON data and integrates and manages the data.

[0883] 5. Calculation of total amount

[0884] The server calculates the total amount based on the price, shipping cost, and earned points information. The calculation uses an algorithm that adds up the product price and shipping cost and subtracts the earned points. For example, if the price on Rakuten Market is 40,000 yen, shipping cost is 500 yen, and the points are 1,000, the total amount will be (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0885] 6. Emotional purchasing decisions

[0886] The server compares the calculated totals and determines the most economical purchase. The user's emotional data is also taken into account. For example, if the user is expressing positive emotions, other factors (high reviews, fast delivery, etc.) that are comparable in price and shipping costs are also taken into account.

[0887] 7. Sending results to the user

[0888] The server sends information about the most economical shopping destination to the user's device. This information includes the selected shopping destination, price, shipping fee, points, and the reason for the recommendation based on emotion. For example, for a user who expresses positive emotion, the recommendation may include "This product has high ratings and will arrive quickly."

[0889] Specific examples

[0890] For example, suppose a user searches for "smartphone" on their device and smiles at the camera. The device sends a product search request to the server, and at the same time, the emotion engine analyzes the user's positive emotions. The server then calls the APIs of Rakuten Ichiba and Amazon to retrieve their respective information.

[0891] On Rakuten, the price is 40,000 yen, shipping is 500 yen, and points are 1,000, for a total of 39,500 yen, while on Amazon, the price is 39,000 yen, shipping is 400 yen, and points are 800, for a total of 38,600 yen. Because the user is smiling, which is recognized as a positive emotion, the server takes into account review ratings and delivery time, and selects Amazon, which has the highest enthusiastic ratings and is expected to deliver quickly.

[0892] Ultimately, the user's device will display a result such as, "Buying from Amazon is the best deal. Price: 39,000 yen, shipping: 400 yen, points: 800 points. High reviews and fast delivery."

[0893] This system allows users to efficiently and emotionally select the best shopping destination, improving their shopping experience.

[0894] The processing flow will be explained below.

[0895] Step 1:

[0896] The user enters the product name or product code into the device's search bar and presses the search button. The device generates a product search request based on this information and sends it to the server. At the same time, the device uses the camera and microphone to record the user's facial expressions and voice, and sends them to the emotion engine.

[0897] Step 2:

[0898] The emotion engine analyzes the user's recorded facial expressions and voice and classifies the user's emotion as positive, negative, or neutral. For example, if the user is smiling, the emotion engine will recognize it as positive.

[0899] Step 3:

[0900] The server receives the product search request sent from the terminal and extracts the product name and product code from the request body.

[0901] Step 4:

[0902] The server requests product information from the APIs of multiple e-commerce platforms. Specifically, it sends a request including the product name and product code to an API endpoint and makes a call to each platform to retrieve the data.

[0903] Step 5:

[0904] The API of each e-commerce platform returns product information. For example, Rakuten Ichiba returns data such as a price of 40,000 yen, shipping cost of 500 yen, and 1,000 points, while Amazon returns data such as a price of 39,000 yen, shipping cost of 400 yen, and 800 points.

[0905] Step 6:

[0906] The server analyzes the responses received from each platform and extracts the price, shipping fee, and earned points. The extracted data is organized and managed for each e-commerce platform.

[0907] Step 7:

[0908] The server calculates the total amount based on the price, shipping cost, and earned points information it has obtained. The server performs the calculation as follows: (price + shipping cost) - earned points. For example, in the case of Rakuten Ichiba, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen, and in the case of Amazon, it is (39,000 yen + 400 yen) - 800 points = 38,600 yen.

[0909] Step 8:

[0910] The server determines the most economical purchase based on the calculated total amount. Here, the user's emotional data is also taken into consideration. For example, if the user has a positive emotion, additional information such as product reviews and delivery speed is also included in the purchase decision.

[0911] Step 9:

[0912] The server sends information about the most economical purchasing destination to the user's device. This information includes the selected purchasing destination, price, shipping fee, points, and emotional reasons for the recommendation. For example, a result such as "Buying from Amazon is the best deal. Price: 39,000 yen, shipping fee: 400 yen, points: 800 points. It has high reviews and offers fast delivery" is sent.

[0913] Step 10:

[0914] The terminal receives the response from the server and analyzes it. The analyzed results are then displayed on the screen in a format that is easy for the user to understand. This allows the user to select the most economical and satisfying purchasing source.

[0915] The above is the specific processing flow of this system. By combining emotion engines, it is possible to make optimal product suggestions and purchase decisions based on the user's emotions.

[0916] Example 2

[0917] 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."

[0918] Conventional e-commerce platforms provide product search results based mainly on price, shipping costs, and points, and are unable to provide search results that take into account the user's emotions and purchasing intentions. This has led to a decrease in user purchasing satisfaction. There is also a need for a system that not only presents the most economical purchasing options, but also provides optimal search results that reflect the user's emotions.

[0919] 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 means for receiving a product search request, means for requesting product information from the APIs of multiple e-commerce platforms and acquiring information on prices, shipping costs, and earned points, means for calculating a total amount based on the acquired price, shipping costs, and earned points information, means for comparing the calculated total amounts and determining the most economical purchasing destination, means for recognizing user emotions, means for filtering or sorting search results based on the recognized user emotions, and means for outputting information on the determined purchasing destination. This makes it possible to select an optimal purchasing destination taking user emotions into consideration and provide high purchasing satisfaction.

[0920] A "product search request" is a request to the server to search for product information, which is generated when a user inputs a product name or product code into a terminal and presses a search button.

[0921] An "e-commerce platform" is an internet-based marketplace that connects multiple sellers and buyers, where goods and services are bought and sold.

[0922] "API" stands for Application Programming Interface, an interface for communication and data exchange between different software systems.

[0923] "Product Information" refers to data including product prices, shipping fees, points, and other related information.

[0924] "Price" refers to the amount of money required to purchase a particular product.

[0925] "Shipping cost" means the cost of transportation required to deliver the product.

[0926] "Earned points" are points awarded when purchasing a product, and can be used to purchase products or services at a later date.

[0927] "Total amount" refers to the actual amount to be paid, calculated by adding the product price and shipping fee and deducting the points earned.

[0928] "Emotions" indicate the user's psychological state and are classified into positive, negative, and neutral categories.

[0929] An "emotion engine" is software that analyzes a user's facial expressions and voice data to recognize the user's emotions.

[0930] "Filtering" is the operation of narrowing down data based on specific conditions.

[0931] "Sorting" is an operation for rearranging data in order based on specific conditions.

[0932] "Destination" refers to the e-commerce platform or merchant from which a user chooses to purchase goods.

[0933] "Search results" refers to a list of product information displayed in response to a user's search request.

[0934] This invention relates to a system that provides product search results on an e-commerce platform while taking user emotions into consideration. In addition to the basic function of obtaining the price, shipping fee, and points of a product specified by a user from an e-commerce site and presenting the most economical purchasing options, the system also recognizes the user's emotions and filters or sorts the search results based on those emotions.

[0935] The system includes means for receiving a product search request, means for requesting product information from APIs of multiple e-commerce platforms and obtaining information on prices, shipping fees, and earned points, means for calculating a total amount based on the obtained information on prices, shipping fees, and earned points, means for comparing the calculated total amounts and determining the most economical purchasing destination, means for recognizing user emotions, means for filtering or sorting search results based on the recognized user emotions, and means for outputting information on the determined purchasing destination.

[0936] The device generates a product search request based on the user's input and sends it to the server. The device is equipped with a search bar, camera, and microphone to record the user's facial expressions and voice. Specifically, the device's camera and microphone are used to monitor the user's facial expressions and voice in real time, and this data is sent to the emotion engine. The emotion engine uses a machine learning model to classify the user's emotion as positive, negative, or neutral.

[0937] The server sends a product information request to the APIs of multiple e-commerce platforms (e.g., major domestic e-commerce platforms and major international e-commerce platforms) based on the product search request received from the terminal. The product information obtained from the APIs of each platform is sent in JSON format or other data format, and includes the price, shipping fee, and earned points.

[0938] The server analyzes and extracts the price, shipping cost, and earned points from the API responses received from each platform, and calculates the total amount. This calculation uses an algorithm that adds up the price and shipping cost and subtracts the earned points. For example, on Rakuten Ichiba, if the price is 40,000 yen, shipping cost is 500 yen, and the points are 1,000, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0939] The server compares the calculated totals and considers the user's emotional data when determining the most economical purchasing platform. For example, if the user has a positive emotional state, the server will recommend a platform with high reviews and fast delivery by considering other factors (such as high reviews and fast delivery) with comparable prices and shipping costs.

[0940] The server sends information on the most economical and emotionally-based purchasing destinations to the user's terminal. This information includes the selected purchasing destination, price, shipping fee, points, and the reason for the recommendation based on emotion. For example, if the user has a positive emotion, the server can include a message such as "This product is highly rated and will arrive quickly."

[0941] Examples of prompts include:

[0942] "When a user smiles and searches their smartphone, choose the e-commerce site that offers the best deal and fastest delivery."

[0943] This system allows users to efficiently and emotionally select the best shopping destination, improving their shopping experience.

[0944] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0945] Step 1: Generate and submit a product search request

[0946] Input: The user enters the product name or product code into the device's search bar and presses the search button.

[0947] Specific operation: The user enters the product name (e.g., "smartphone") into the input form on the device and clicks the search button.

[0948] Data processing and calculation: The terminal generates a product search request based on the user's input and sends it to the server in the form of an HTTP request.

[0949] Output: Get the product search request received by the server.

[0950] Step 2: Acquire and analyze user emotion data

[0951] Input: At the same time as sending a product search request, the device's camera and microphone record the user's facial expressions and voice.

[0952] Specific operation: The device captures the user's facial expressions and voice in real time using the camera and microphone.

[0953] Data processing and calculation: The facial expression and voice data collected by the device is sent to the emotion engine, which uses a machine learning model to classify the user's emotion as positive, negative, or neutral.

[0954] Output: Classified emotion data is sent to the server.

[0955] Step 3: Request product information from the e-commerce platform

[0956] Input: Product search request sent from the device.

[0957] Specific operation: Based on the product search request, the server sends HTTP requests to the APIs of multiple e-commerce platforms.

[0958] Data processing and calculation: The API request includes the product name and product code, and the response is received from each platform in JSON format or other data format.

[0959] Output: Product information returned from each e-commerce platform.

[0960] Step 4: Obtain and analyze price, shipping, and points information

[0961] Input: The API response returned by the e-commerce platform.

[0962] Specific operation: The server analyzes the API response received and extracts the necessary data (price, shipping fee, points).

[0963] Data processing and calculation: The server extracts the price, shipping fee, and points from the JSON data in a unique format, and organizes and integrates them.

[0964] Output: Organized price, shipping, and points information.

[0965] Step 5: Calculate the total purchase amount

[0966] Input: Obtained price, shipping, and points information.

[0967] Specific operation: The server uses this data to calculate the total amount.

[0968] Data processing and calculation: An algorithm is used to add up the price and shipping cost and deduct points. For example, if the price is 40,000 yen, the shipping cost is 500 yen, and the points are 1,000 points, the total will be (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[0969] Output: Calculated gross amount data.

[0970] Step 6: Emotional purchasing decisions

[0971] Input: Calculated total amount data and user sentiment data.

[0972] Specific operation: The server compares the total amount data and determines the most appropriate purchasing destination taking into account the user's feelings.

[0973] Data processing and calculation: For users who show positive sentiment, other factors such as review ratings and delivery times are taken into account.

[0974] Output: Information on the most appropriate purchasing platform (platform name, price, shipping fee, points, reason for recommendation).

[0975] Step 7: Send supplier information to users

[0976] Input: Determined supplier information.

[0977] Specific operation: The server transmits the determined supplier information to the terminal.

[0978] Data processing and calculation: Formatting information including the reason for recommendation (e.g., "high reviews and fast delivery expected").

[0979] Output: Information on the best places to buy displayed on the user's device.

[0980] (Application example 2)

[0981] 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."

[0982] Conventional e-commerce systems provide product search results without considering the user's feelings, making it difficult to optimize the user's purchasing experience. In particular, determining the most economical purchasing destination without considering the user's feelings about the searched product can reduce user satisfaction.

[0983] 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.

[0984] In this invention, the server includes means for receiving a product search request, means for requesting product information from the APIs of multiple e-commerce platforms and acquiring information on prices, shipping costs, and earned points, means for calculating the total amount based on the acquired price, shipping costs, and earned points, means for determining the most economical and suitable purchasing destination based on the calculated total amount and the user's emotions, means for outputting information on the determined purchasing destination, and means for acquiring the user's facial expressions and voice data using a camera and microphone and analyzing them with an emotion engine. This makes it possible to present the most suitable purchasing destination taking the user's emotions into consideration.

[0985] The "means for receiving a product search request" is a function that sends a product search request generated by the terminal to the server when a user inputs a product name or product code into the search bar and presses the search button.

[0986] "Means for requesting product information from the APIs of multiple e-commerce platforms and obtaining information on prices, shipping fees, and earned points" refers to a function in which a server sends requests to the API endpoints of multiple e-commerce platforms and obtains the product information of each.

[0987] The "means for calculating the total amount based on the acquired price, shipping fee, and earned point information" is a function that the server uses the price, shipping fee, and earned point information acquired from each e-commerce platform to calculate the total amount.

[0988] "Means for determining the most economical and suitable purchasing source based on the calculated total amount and the user's emotions" is a function that selects the most suitable purchasing source by taking into consideration the total amount calculated by the server and the user's emotional data.

[0989] The "means for outputting information on the determined supplier" is a function by which the server notifies the user of information on the most suitable supplier.

[0990] "Means for acquiring the user's facial expressions and voice data using a camera and microphone and analyzing it with an emotion engine" refers to a function that acquires the user's facial images and voice, sends them to the emotion engine for analysis, and recognizes the user's emotions.

[0991] The "emotion engine" is a system that analyzes the user's facial expressions and voice data and classifies them into emotional categories such as positive, negative, and neutral.

[0992] "Total Calculation" is the process of adding up the acquired price and shipping costs and subtracting earned points to determine the actual total cost of the item.

[0993] This invention relates to an electronic commerce system that provides product search results taking into account the user's emotions. When a user makes a product search request via a terminal, the system recognizes the user's emotions and presents the most suitable purchasing destination. This section explains each processing step for recognizing the user's emotions and presenting the most suitable purchasing destination.

[0994] System Configuration

[0995] 1. Hardware and Software:

[0996] Device: A device such as a smartphone or tablet that has a built-in camera and microphone.

[0997] Server: A central server for accessing APIs of multiple e-commerce platforms.

[0998] Emotion engine: A software library for analyzing a user's facial expressions and voice and classifying them into emotional categories.

[0999] Flask: Used as a web application framework.

[1000] Requests: A Python library for sending HTTP requests.

[1001] Program processing overview

[1002] The device generates a product search request and sends it to the server. When the user enters a product name or code into the search bar and presses the search button, the device uses a camera and microphone to record the user's facial expressions and voice data. This data is sent to the emotion engine, which classifies the user's emotion as positive, negative, or neutral.

[1003] The server requests product information from the APIs of multiple e-commerce platforms. It calculates the total price based on the obtained price, shipping cost, and earned points information, and also combines the user's emotional data to determine the most economical and suitable purchasing destination. Finally, the server sends the information of the selected purchasing destination to the user's device.

[1004] Specific examples

[1005] For example, if a user searches for "smartphone" on their device, the device records image data and audio of them smiling at the camera. This data is analyzed by the emotion engine and recognized as a positive emotion. The server then retrieves product data from multiple e-commerce platforms, comparing it with information such as a price of ¥40,000, shipping of ¥500, 1,000 points, and a total of ¥39,500 on Rakuten, or a price of ¥39,000, shipping of ¥400, 800 points, and a total of ¥38,600 on Amazon.

[1006] Because the user's sentiment is positive, the server selects the optimal purchasing source by taking into consideration not only price and shipping costs, but also reviews and delivery time. In this case, the server selects Amazon, which has high reviews and is expected to deliver quickly, and sends that information to the user's device.

[1007] Prompt Sentence Examples

[1008] The prompt text that is entered when a user searches for "smartphone" is as follows:

[1009] Text input: "Smartphone"

[1010] Emotion data: image data and audio data (indicating a smile)

[1011] This allows users to quickly and efficiently select the best place to purchase products based on their emotions, significantly improving the user's purchasing experience.

[1012] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1013] Step 1:

[1014] The user enters the product name or product code into the search bar of the device and presses the search button. At this time, the device's camera and microphone record the user's facial expression and voice data. The input data, which is the product name and the user's facial expression and voice data, is sent to the subsequent processing step.

[1015] Step 2:

[1016] The device sends the user's facial and voice data to the emotion engine, which analyzes it to recognize the user's emotions. Emotional data is classified as positive, negative, or neutral. The input data is the user's facial and voice data, and the output data is the emotion category (positive, negative, or neutral).

[1017] Step 3:

[1018] Based on the product search request, the server requests product information from the API endpoints of multiple e-commerce platforms. The input data is the product name, and the request is sent to each platform. The output data is the price, shipping fee, and earned points information obtained from each platform.

[1019] Step 4:

[1020] The server calculates the total amount based on the acquired price, shipping fee, and earned point information. The total amount is the sum of the price and shipping fee and the earned point amount. The input data are the price, shipping fee, and earned point information, and the output data is the calculated total amount.

[1021] Step 5:

[1022] The server determines the most economical and suitable purchasing destination based on the calculated total price and the user's sentiment. If the sentiment data is positive, it also takes into account reviews and delivery time in addition to price and shipping costs. The input data are the calculated total price and sentiment data, and the output data is information on the optimal purchasing destination.

[1023] Step 6:

[1024] The server sends the information on the optimal supplier it has determined to the user's terminal, which then displays this information to the user. The input data is the optimal supplier information, and the output data is the supplier information displayed to the user.

[1025] For example, if a user searches for "smartphone" and smiles at the camera, the device sends that data to the emotion engine, which recognizes it as a positive emotion. The server then retrieves product information from multiple platforms, calculates the total price, and determines the optimal purchasing source, taking into account the emotion data. In this case, the server selects a platform with high reviews and the potential for fast delivery, and notifies the user of that information.

[1026] Through the above steps, the user can quickly select the most suitable place to purchase products according to their emotions.

[1027] 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.

[1028] 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.

[1029] 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.

[1030] [Fourth embodiment]

[1031] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1032] 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.

[1033] 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).

[1034] 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.

[1035] 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.

[1036] 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).

[1037] 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.

[1038] 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.

[1039] 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.

[1040] 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.

[1041] 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.

[1042] 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.

[1043] 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."

[1044] This invention relates to a system that compares the prices, shipping costs, and points earned on multiple e-commerce platforms (EC sites) when a user searches for a specific product, and presents the most economical purchase option. This system is implemented using the following means.

[1045] 1. Receiving a product search request

[1046] When a user enters a product name or product code into the search bar of the device and presses the search button, the device generates a product search request and sends it to the server, which then receives the product search request.

[1047] 2. Querying APIs of multiple e-commerce platforms

[1048] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce sites. Specifically, it calls the APIs of each e-commerce site to obtain the price, shipping fee, and earnable points information for the specified product.

[1049] 3. Obtaining price, shipping and point information

[1050] The server receives and analyzes the product information returned from each e-commerce site, extracting information such as price, shipping fee, and points, and then integrates and manages the data.

[1051] 4. Calculation of total amount

[1052] The server calculates the total price based on the information it has received. The total price is calculated using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This allows the lowest payment amount presented to the user.

[1053] 5. Determine the most economical purchase source

[1054] The server compares the calculated totals and determines the most economical purchase. The comparison is not a simple price comparison, but a comparison of the total amount taking into account all factors (price, shipping, points).

[1055] 6. Sending results to users

[1056] The server sends the information on the most economical purchasing site determined by the server to the user's device. The user's device receives this information and displays it on the screen. The displayed content includes the name of the recommended e-commerce site, the price, shipping fee, points information, and the total price.

[1057] Specific examples

[1058] For example, suppose a user searches for "smartphone" on their device. When the device sends a product search request to the server, the server calls the APIs of Rakuten Ichiba and Amazon to retrieve information from each. Rakuten Ichiba retrieves information such as price: 40,000 yen, shipping: 500 yen, and points: 1,000, while Amazon retrieves information such as price: 39,000 yen, shipping: 400 yen, and points: 800.

[1059] The server calculates the total amount based on this information. In the case of Rakuten Ichiba, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen. On the other hand, in the case of Amazon, the total amount is (39,000 yen + 400 yen) - 800 points = 38,600 yen.

[1060] The server compares these total prices and determines Amazon as the most economical place to purchase. Finally, the user's device displays the result: "Buying from Amazon is the best deal. Price: 39,000 yen, Shipping: 400 yen, Points: 800 points."

[1061] The above is an embodiment of the present invention. This system allows users to efficiently find the most economical purchase source, thereby saving a lot of time and effort.

[1062] The processing flow will be explained below.

[1063] Step 1:

[1064] The user enters the product name or product code into the search bar on the device and presses the search button. The device generates a product search request based on the input information and sends it to the server.

[1065] Step 2:

[1066] The server receives the product search request sent from the terminal and extracts the product name and product code from the request body.

[1067] Step 3:

[1068] The server requests product information from the APIs of multiple e-commerce platforms, and then sends a request including the extracted product name and product code to the API endpoint of each e-commerce site.

[1069] Step 4:

[1070] The API of each e-commerce platform returns product information. For example, the response from Rakuten Ichiba and Amazon returns the price, shipping fee, and earned points information in JSON format.

[1071] Step 5:

[1072] The server receives and analyzes responses from each e-commerce platform, extracts price, shipping fee, and earned points from the JSON data, and manages all of this data together.

[1073] Step 6:

[1074] The server calculates the total amount based on the price, shipping fee, and earned points information. The server performs the following calculation for each e-commerce site: (price + shipping fee) - earned points. For example, in the case of Rakuten Ichiba, the total amount is (price 40,000 yen + shipping fee 500 yen) - 1,000 points = 39,500 yen.

[1075] Step 7:

[1076] The server determines the most economical purchase destination based on the total amount calculated. The server compares multiple total amounts and selects the purchase destination with the lowest total amount. For example, since the total amount on Amazon is 38,600 yen, Amazon is selected.

[1077] Step 8:

[1078] The server sends information about the most economical shopping destination to the user's terminal. The server generates a response containing detailed information about the selected shopping destination (price, shipping fee, points, total amount) and returns it to the terminal.

[1079] Step 9:

[1080] The device receives a response from the server. The device analyzes the received data and displays it on the screen in a format that is easy for the user to understand. For example, it might say, "Buying from Amazon is the best deal. Price: 39,000 yen, shipping: 400 yen, points: 800 points."

[1081] The above is the specific processing flow of this system, which allows users to easily find the most economical purchasing site from multiple e-commerce sites.

[1082] Example 1

[1083] 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."

[1084] In conventional e-commerce, users have to visit multiple e-commerce sites individually to compare prices, shipping costs, and points earned, which takes a lot of time and effort.In addition, there is also the problem that information needed to find the most economical purchase is scattered, making it difficult for users to make the best choice.

[1085] 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.

[1086] In this invention, the server includes means for receiving a product search request, means for requesting product information from data acquisition interfaces of multiple e-commerce sites and acquiring information on prices, shipping fees, and earned points, means for calculating a total amount based on the acquired information on prices, shipping fees, and earned points, means for comparing the calculated total amounts and determining the most economical purchasing source, and means for outputting information on the determined purchasing source, thereby enabling users to efficiently find the most economical purchasing source.

[1087] "Product Search Request" means a request containing information entered by a user to search for a particular product.

[1088] An "e-commerce site" is a platform for selling goods and services over the Internet.

[1089] A "data acquisition interface" is a program interface for communicating with an external system to acquire information.

[1090] "Product information" refers to detailed information such as product price, shipping fee, and earned points.

[1091] "Price" refers to the amount you pay to purchase a particular item.

[1092] "Shipping Costs" means any additional costs required to deliver a Product.

[1093] "Earned points" are points that can be acquired when purchasing a product and can be used for subsequent purchases.

[1094] "Total amount" refers to the final payment amount, which is the sum of the product price and shipping fee, minus the points earned.

[1095] The "most economical place to buy" is the site with the lowest total price and the most economical for the user.

[1096] "Means for outputting information" refers to a method or device for displaying or providing the processing results to the user.

[1097] This invention is a system that compares prices, shipping costs, and points earned on multiple e-commerce sites when a user searches for a specific product, and presents the most economical purchasing source. The following is a specific embodiment for implementing this system.

[1098] First, the user enters the product name or product code into the search bar of the device and presses the search button. This operation causes the device to generate a product search request and send it to the server. The server receives this product search request and requests product information from the data acquisition interfaces of multiple e-commerce sites (e.g., major domestic e-commerce sites and major international e-commerce sites).

[1099] Specifically, the server calls the API of each e-commerce site to obtain the price, shipping cost, and available points for the specified product. This process can use APIs such as those of Rakuten Ichiba or Amazon. The server receives the product information returned from each e-commerce site and parses it in JSON format. Information such as price, shipping cost, and points is extracted individually, and the data is integrated and managed.

[1100] The server then calculates the total amount based on the information obtained. This calculation is performed using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This ensures that the lowest payment amount is presented to the user. For example, consider a case where a price of 40,000 yen, shipping cost of 500 yen, and 1,000 points are obtained on Rakuten Market, and a price of 39,000 yen, shipping cost of 400 yen, and 800 points are obtained on a major international e-commerce site.

[1101] The server calculates the total price based on this information. In the case of Rakuten Ichiba, the total price is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen, and in the case of the major international e-commerce site, the total price is (39,000 yen + 400 yen) - 800 points = 38,600 yen. The server compares these total prices and determines the major international e-commerce site as the most economical purchase destination.

[1102] Finally, the server sends the information on the most economical purchasing site to the user's device. The device receives this information and displays it on the screen. The displayed information includes the name of the recommended e-commerce site, price, shipping fee, points information, and total amount. For example, the result may read, "Purchasing from a major international e-commerce site is the best value. Price: 39,000 yen, shipping fee: 400 yen, points: 800 points."

[1103] This system allows users to efficiently find the most economical purchases, thereby saving a lot of time and effort.

[1104] Examples of prompts include:

[1105] "I want to build a system that allows users to search for a specific product and compares prices, shipping costs, and reward points across multiple e-commerce sites to suggest the most economical purchase. Please explain the process by following these steps."

[1106] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1107] Step 1:

[1108] The user enters the product name or product code in the search bar of the device and presses the search button. This operation causes the device to generate a product search request and send it to the server.

[1109] Input: The product name or code entered by the user (e.g., "smartphone").

[1110] Output: Product search request (e.g., search request for "smartphone").

[1111] Specific operation: When a user enters "smartphone" and presses the search button, the device sends an HTTP POST request to the server, which includes the search key ("smartphone").

[1112] Step 2:

[1113] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce sites.

[1114] Input: Product search request (e.g., search request for "smartphone").

[1115] Output: Product information requests from each e-commerce site (e.g., requests to Rakuten Ichiba and Amazon).

[1116] Specific operation: The server analyzes the product search request and sends an HTTP GET request to the Rakuten Ichiba or Amazon API. The request includes the API key and search key.

[1117] Step 3:

[1118] The server receives and analyzes product information returned from multiple e-commerce sites, extracting individual data such as price, shipping fee, and points, and then integrates and manages them.

[1119] Input: Product information returned from each e-commerce site (e.g., responses from Rakuten Ichiba and Amazon).

[1120] Output: Parsed price, shipping fee, and points information (e.g., Rakuten Ichiba price: 40,000 yen, shipping fee: 500 yen, points: 1,000 points).

[1121] Specific operation: The server receives API responses from Rakuten Ichiba and Amazon in JSON format, extracts price, shipping fee, and points information, and stores the extracted information in an internal data structure.

[1122] Step 4:

[1123] The server calculates the total amount based on the information it has received, adding up the product price and shipping costs and using an algorithm to deduct the points earned.

[1124] Input: Parsed price, shipping fee, and points information (e.g., Rakuten Ichiba and Amazon information).

[1125] Output: Total amount for each candidate destination (e.g., Rakuten Market total amount: 39,500 yen, Amazon total amount: 38,600 yen).

[1126] Specific operation: The server calculates the total price (40,000 yen + 500 yen - 1,000 points = 39,500 yen) from the information on Rakuten (price 40,000 yen, shipping 500 yen, points 1,000), and the total price (39,000 yen + 400 yen - 800 points = 38,600 yen) from the information on Amazon (price 39,000 yen, shipping 400 yen, points 800).

[1127] Step 5:

[1128] The server compares the calculated totals and determines the most economical purchase.

[1129] Input: Total amount for each candidate (e.g., Rakuten Market total amount: 39,500 yen, Amazon total amount: 38,600 yen).

[1130] Output: Information on the most economical place to buy (e.g. Amazon is the most economical).

[1131] Specific operation: The server compares the total price of each candidate and selects the purchase destination (Amazon) with the lowest total price.

[1132] Step 6:

[1133] The server then sends the information on the most economical purchasing source to the user's device, which receives the information and displays it on the screen.

[1134] Input: Information on the most economical place to purchase (e.g., Amazon is the most economical).

[1135] Output: The result displayed on the user's screen (e.g., "Buying from Amazon is the best deal. Price: 39,000 yen, Shipping: 400 yen, Points: 800 points").

[1136] Specific operation: The server returns information on the most economical purchasing source in JSON format as an HTTP response, and the device parses the information and displays it on the screen.

[1137] This allows users to efficiently find the most economical purchases, saving them a lot of time and effort.

[1138] (Application example 1)

[1139] 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."

[1140] In conventional e-commerce, users have to compare multiple platforms themselves, making it difficult to efficiently find the most economical place to buy. In addition, there is a lack of a way for users to easily find the best place to buy even while on the move.

[1141] 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.

[1142] In this invention, the server includes means for receiving a product search request, means for requesting product information from APIs of multiple e-commerce platforms and acquiring price, shipping fee, and earned point information, and means for calculating the total amount based on the acquired price, shipping fee, and earned point information. This allows users to easily find the most economical purchase from multiple e-commerce sites using their mobile terminals.

[1143] A "product search request" is a request sent by a user via a terminal to obtain information about a product that the user is considering purchasing.

[1144] An "e-commerce platform" is an online marketplace for buying and selling goods and services over the Internet.

[1145] "API" stands for Application Programming Interface, an interface that defines the rules and protocols for different software systems to communicate with each other.

[1146] "Price" is the amount indicating the monetary value of the item being purchased.

[1147] "Shipping fee" refers to the cost of shipping purchased items to the user.

[1148] "Earned points" are points that are awarded to users in response to purchases and can be used as monetary value for future purchases.

[1149] "Total amount" means the final payment amount, which is the product price plus shipping fee and deduction of earned points.

[1150] A "mobile terminal" is a portable communication device such as a smartphone or tablet.

[1151] "Comparison" is the act of evaluating multiple options based on their respective characteristics and determining their relative merits.

[1152] The "most economical source" is the source that will result in the lowest expenditure for the user after taking into account all costs and benefits.

[1153] This invention is a system that compares prices, shipping costs, and points earned on multiple e-commerce platforms when a user searches for a specific product, and presents the most economical purchase option. This system allows users to efficiently decide where to purchase using their mobile terminals.

[1154] 1. System Configuration

[1155] The system consists of the following elements:

[1156] User device: A portable communication device such as a smartphone or tablet. This device has an interface for inputting product search requests.

[1157] Server: A central control unit that processes product search requests, queries multiple e-commerce platforms, aggregates and compares information, and determines the best purchasing location.

[1158] Multiple e-commerce platforms: Various online marketplaces, each providing pricing, shipping, and rewards information through APIs.

[1159] 2. Data Processing and Calculations

[1160] The system requires input from users, data acquisition from multiple e-commerce platforms, and data processing and calculation.

[1161] Receiving a product search request: When a user enters a product name or product code into the device's search bar and presses the search button, the device generates a product search request and sends it to the server.

[1162] Querying API: Based on the received product search request, the server requests product information from the APIs of multiple e-commerce platforms. Specifically, it calls the APIs of each e-commerce site to obtain the price, shipping fee, and available points information for the specified product.

[1163] Data acquisition and analysis: The server receives and analyzes the product information returned from each e-commerce site. Information such as price, shipping fee, and points is extracted individually, and the data is integrated and managed.

[1164] Calculating the total price: The server calculates the total price based on the information it has received. The total price is calculated using an algorithm that adds up the product price and shipping costs and subtracts the points earned. This allows the lowest payment price to be presented to the user.

[1165] Determining the best supplier: The server compares the calculated totals and determines the most economical supplier.

[1166] Sending the results to the user: The server sends the information on the most economical purchasing site to the user's device. The user's device receives this information and displays it on the screen. The displayed content includes the name of the recommended e-commerce site, the price, shipping fee, points information, and the total price.

[1167] 3. Specific Examples

[1168] For example, suppose a user searches for "smartphone" on their device. When the device sends a product search request to the server, the server calls the APIs of multiple online marketplaces and obtains information on price, shipping, and points from each. Based on this information, the total price is calculated and the most economical purchase destination is determined. The "optimal purchase destination" is then displayed on the user's device.

[1169] Prompt Sentence Examples

[1170] "Please tell me the price of the smartphone, shipping costs, and points earned. Also, please do the same for multiple online marketplaces."

[1171] This allows users to easily and quickly find the most economical purchase, greatly improving user convenience.

[1172] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1173] Step 1:

[1174] The user enters the product name or product code into the device's search bar and presses the search button.

[1175] This operation generates a product search request, which is then sent to the server.

[1176] Input: Product name or product code

[1177] Data processing: Generating search requests

[1178] Output: Product search request

[1179] Step 2:

[1180] Based on the received product search request, the server requests product information from the APIs of multiple e-commerce platforms.

[1181] Specifically, the server calls the API of each platform to obtain the price, shipping fee, and earned points information for the specified product.

[1182] Input: Product search request

[1183] Data processing: Creating and sending API requests

[1184] Output: Product information from each platform

[1185] Step 3:

[1186] The server receives and analyzes the product information returned from each e-commerce platform.

[1187] Through analysis, information such as price, shipping costs, and points is extracted individually, and each piece of data is integrated and managed.

[1188] Input: Product information from the platform

[1189] Data processing: Product information analysis and integration

[1190] Output: Consolidated product information

[1191] Step 4:

[1192] The server calculates the total amount based on each piece of information obtained.

[1193] The total price is calculated using an algorithm that adds up the product price and shipping costs and deducts the points earned.

[1194] Input: Integrated product information

[1195] Data processing: Calculate total amount (price + shipping fee - points)

[1196] Output: Total amount for each platform

[1197] Step 5:

[1198] The server compares the calculated totals and determines the most economical purchase.

[1199] Here, the total price of all platforms is compared and the purchase source with the lowest total price is selected.

[1200] Input: Total amount for each platform

[1201] Data processing: Comparing total amounts and selecting the best supplier

[1202] Output: Information on the most economical purchasing source

[1203] Step 6:

[1204] The server sends information on the most economical purchasing source determined by the server to the user's terminal.

[1205] The user's device receives this information and displays it on the screen, including the name of the recommended platform, the price, shipping fee, points information, and the total amount.

[1206] Input: Information on the most economical supplier

[1207] Data processing: transmission of information

[1208] Output: Supplier information displayed on the user's device

[1209] 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.

[1210] This invention relates to a system that provides product search results on an e-commerce platform while taking into account the user's emotions. In addition to the basic function of obtaining the price, shipping fee, and points for a product specified by the user from an e-commerce site and presenting the most economical purchasing options, this system also recognizes the user's emotions and filters or sorts the search results based on those emotions.

[1211] 1. Receiving a product search request

[1212] When a user enters a product name or product code into the device's search bar and presses the search button, the device generates a product search request and sends it to the server. At this time, the device uses a camera and microphone to record the user's facial expressions and voice, and analyzes them with an emotion engine in order to simultaneously recognize the user's emotions.

[1213] 2. Emotion recognition using an emotion engine

[1214] The device sends the user's facial and voice data to the emotion engine, which then analyzes the data to recognize the user's emotions. Emotions are classified into positive, negative, and neutral categories. For example, if the user is smiling, the emotion engine recognizes the emotion as positive.

[1215] 3. Querying APIs of multiple e-commerce platforms

[1216] Based on the product search request, the server requests product information from the APIs of multiple e-commerce sites. The server then sends a request including the extracted product name and product code to the API endpoint of each e-commerce site.

[1217] 4. Obtaining price, shipping and point information

[1218] The API of each e-commerce platform returns product information, which is received and analyzed by the server. The server extracts the price, shipping fee, and earned points from the JSON data and integrates and manages the data.

[1219] 5. Calculation of total amount

[1220] The server calculates the total amount based on the price, shipping cost, and earned points information. The calculation uses an algorithm that adds up the product price and shipping cost and subtracts the earned points. For example, if the price on Rakuten Market is 40,000 yen, shipping cost is 500 yen, and the points are 1,000, the total amount will be (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[1221] 6. Emotional purchasing decisions

[1222] The server compares the calculated totals and determines the most economical purchase. The user's emotional data is also taken into account. For example, if the user is expressing positive emotions, other factors (high reviews, fast delivery, etc.) that are comparable in price and shipping costs are also taken into account.

[1223] 7. Sending results to the user

[1224] The server sends information about the most economical shopping destination to the user's device. This information includes the selected shopping destination, price, shipping fee, points, and the reason for the recommendation based on emotion. For example, for a user who expresses positive emotion, the recommendation may include "This product has high ratings and will arrive quickly."

[1225] Specific examples

[1226] For example, suppose a user searches for "smartphone" on their device and smiles at the camera. The device sends a product search request to the server, and at the same time, the emotion engine analyzes the user's positive emotions. The server then calls the APIs of Rakuten Ichiba and Amazon to retrieve their respective information.

[1227] On Rakuten, the price is 40,000 yen, shipping is 500 yen, and points are 1,000, for a total of 39,500 yen, while on Amazon, the price is 39,000 yen, shipping is 400 yen, and points are 800, for a total of 38,600 yen. Because the user is smiling, which is recognized as a positive emotion, the server takes into account review ratings and delivery time, and selects Amazon, which has the highest enthusiastic ratings and is expected to deliver quickly.

[1228] Ultimately, the user's device will display a result such as, "Buying from Amazon is the best deal. Price: 39,000 yen, shipping: 400 yen, points: 800 points. High reviews and fast delivery."

[1229] This system allows users to efficiently and emotionally select the best shopping destination, improving their shopping experience.

[1230] The processing flow will be explained below.

[1231] Step 1:

[1232] The user enters the product name or product code into the device's search bar and presses the search button. The device generates a product search request based on this information and sends it to the server. At the same time, the device uses the camera and microphone to record the user's facial expressions and voice, and sends them to the emotion engine.

[1233] Step 2:

[1234] The emotion engine analyzes the user's recorded facial expressions and voice and classifies the user's emotion as positive, negative, or neutral. For example, if the user is smiling, the emotion engine will recognize it as positive.

[1235] Step 3:

[1236] The server receives the product search request sent from the terminal and extracts the product name and product code from the request body.

[1237] Step 4:

[1238] The server requests product information from the APIs of multiple e-commerce platforms. Specifically, it sends a request including the product name and product code to an API endpoint and makes a call to each platform to retrieve the data.

[1239] Step 5:

[1240] The API of each e-commerce platform returns product information. For example, Rakuten Ichiba returns data such as a price of 40,000 yen, shipping cost of 500 yen, and 1,000 points, while Amazon returns data such as a price of 39,000 yen, shipping cost of 400 yen, and 800 points.

[1241] Step 6:

[1242] The server analyzes the responses received from each platform and extracts the price, shipping fee, and earned points. The extracted data is organized and managed for each e-commerce platform.

[1243] Step 7:

[1244] The server calculates the total amount based on the price, shipping cost, and earned points information it has obtained. The server performs the calculation as follows: (price + shipping cost) - earned points. For example, in the case of Rakuten Ichiba, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen, and in the case of Amazon, it is (39,000 yen + 400 yen) - 800 points = 38,600 yen.

[1245] Step 8:

[1246] The server determines the most economical purchase based on the calculated total amount. Here, the user's emotional data is also taken into consideration. For example, if the user has a positive emotion, additional information such as product reviews and delivery speed is also included in the purchase decision.

[1247] Step 9:

[1248] The server sends information about the most economical purchasing destination to the user's device. This information includes the selected purchasing destination, price, shipping fee, points, and emotional reasons for the recommendation. For example, a result such as "Buying from Amazon is the best deal. Price: 39,000 yen, shipping fee: 400 yen, points: 800 points. It has high reviews and offers fast delivery" is sent.

[1249] Step 10:

[1250] The terminal receives the response from the server and analyzes it. The analyzed results are then displayed on the screen in a format that is easy for the user to understand. This allows the user to select the most economical and satisfying purchasing source.

[1251] The above is the specific processing flow of this system. By combining emotion engines, it is possible to make optimal product suggestions and purchase decisions based on the user's emotions.

[1252] Example 2

[1253] 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."

[1254] Conventional e-commerce platforms provide product search results based mainly on price, shipping costs, and points, and are unable to provide search results that take into account the user's emotions and purchasing intentions. This has led to a decrease in user purchasing satisfaction. There is also a need for a system that not only presents the most economical purchasing options, but also provides optimal search results that reflect the user's emotions.

[1255] 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 means for receiving a product search request, means for requesting product information from the APIs of multiple e-commerce platforms and acquiring information on prices, shipping costs, and earned points, means for calculating a total amount based on the acquired price, shipping costs, and earned points information, means for comparing the calculated total amounts and determining the most economical purchasing destination, means for recognizing user emotions, means for filtering or sorting search results based on the recognized user emotions, and means for outputting information on the determined purchasing destination. This makes it possible to select an optimal purchasing destination taking user emotions into consideration and provide high purchasing satisfaction.

[1256] A "product search request" is a request to the server to search for product information, which is generated when a user inputs a product name or product code into a terminal and presses a search button.

[1257] An "e-commerce platform" is an internet-based marketplace that connects multiple sellers and buyers, where goods and services are bought and sold.

[1258] "API" stands for Application Programming Interface, an interface for communication and data exchange between different software systems.

[1259] "Product Information" refers to data including product prices, shipping fees, points, and other related information.

[1260] "Price" refers to the amount of money required to purchase a particular product.

[1261] "Shipping cost" means the cost of transportation required to deliver the product.

[1262] "Earned points" are points awarded when purchasing a product, and can be used to purchase products or services at a later date.

[1263] "Total amount" refers to the actual amount to be paid, calculated by adding the product price and shipping fee and deducting the points earned.

[1264] "Emotions" indicate the user's psychological state and are classified into positive, negative, and neutral categories.

[1265] An "emotion engine" is software that analyzes a user's facial expressions and voice data to recognize the user's emotions.

[1266] "Filtering" is the operation of narrowing down data based on specific conditions.

[1267] "Sorting" is an operation for rearranging data in order based on specific conditions.

[1268] "Destination" refers to the e-commerce platform or merchant from which a user chooses to purchase goods.

[1269] "Search results" refers to a list of product information displayed in response to a user's search request.

[1270] This invention relates to a system that provides product search results on an e-commerce platform while taking user emotions into consideration. In addition to the basic function of obtaining the price, shipping fee, and points of a product specified by a user from an e-commerce site and presenting the most economical purchasing options, the system also recognizes the user's emotions and filters or sorts the search results based on those emotions.

[1271] The system includes means for receiving a product search request, means for requesting product information from APIs of multiple e-commerce platforms and obtaining information on prices, shipping fees, and earned points, means for calculating a total amount based on the obtained information on prices, shipping fees, and earned points, means for comparing the calculated total amounts and determining the most economical purchasing destination, means for recognizing user emotions, means for filtering or sorting search results based on the recognized user emotions, and means for outputting information on the determined purchasing destination.

[1272] The device generates a product search request based on the user's input and sends it to the server. The device is equipped with a search bar, camera, and microphone to record the user's facial expressions and voice. Specifically, the device's camera and microphone are used to monitor the user's facial expressions and voice in real time, and this data is sent to the emotion engine. The emotion engine uses a machine learning model to classify the user's emotion as positive, negative, or neutral.

[1273] The server sends a product information request to the APIs of multiple e-commerce platforms (e.g., major domestic e-commerce platforms and major international e-commerce platforms) based on the product search request received from the terminal. The product information obtained from the APIs of each platform is sent in JSON format or other data format, and includes the price, shipping fee, and earned points.

[1274] The server analyzes and extracts the price, shipping cost, and earned points from the API responses received from each platform, and calculates the total amount. This calculation uses an algorithm that adds up the price and shipping cost and subtracts the earned points. For example, on Rakuten Ichiba, if the price is 40,000 yen, shipping cost is 500 yen, and the points are 1,000, the total amount is (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[1275] The server compares the calculated totals and considers the user's emotional data when determining the most economical purchasing platform. For example, if the user has a positive emotional state, the server will recommend a platform with high reviews and fast delivery by considering other factors (such as high reviews and fast delivery) with comparable prices and shipping costs.

[1276] The server sends information on the most economical and emotionally-based purchasing destinations to the user's terminal. This information includes the selected purchasing destination, price, shipping fee, points, and the reason for the recommendation based on emotion. For example, if the user has a positive emotion, the server can include a message such as "This product is highly rated and will arrive quickly."

[1277] Examples of prompts include:

[1278] "When a user smiles and searches their smartphone, choose the e-commerce site that offers the best deal and fastest delivery."

[1279] This system allows users to efficiently and emotionally select the best shopping destination, improving their shopping experience.

[1280] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1281] Step 1: Generate and submit a product search request

[1282] Input: The user enters the product name or product code into the device's search bar and presses the search button.

[1283] Specific operation: The user enters the product name (e.g., "smartphone") into the input form on the device and clicks the search button.

[1284] Data processing and calculation: The terminal generates a product search request based on the user's input and sends it to the server in the form of an HTTP request.

[1285] Output: Get the product search request received by the server.

[1286] Step 2: Acquire and analyze user emotion data

[1287] Input: At the same time as sending a product search request, the device's camera and microphone record the user's facial expressions and voice.

[1288] Specific operation: The device captures the user's facial expressions and voice in real time using the camera and microphone.

[1289] Data processing and calculation: The facial expression and voice data collected by the device is sent to the emotion engine, which uses a machine learning model to classify the user's emotion as positive, negative, or neutral.

[1290] Output: Classified emotion data is sent to the server.

[1291] Step 3: Request product information from the e-commerce platform

[1292] Input: Product search request sent from the device.

[1293] Specific operation: Based on the product search request, the server sends HTTP requests to the APIs of multiple e-commerce platforms.

[1294] Data processing and calculation: The API request includes the product name and product code, and the response is received from each platform in JSON format or other data format.

[1295] Output: Product information returned from each e-commerce platform.

[1296] Step 4: Obtain and analyze price, shipping, and points information

[1297] Input: The API response returned by the e-commerce platform.

[1298] Specific operation: The server analyzes the API response received and extracts the necessary data (price, shipping fee, points).

[1299] Data processing and calculation: The server extracts the price, shipping fee, and points from the JSON data in a unique format, and organizes and integrates them.

[1300] Output: Organized price, shipping, and points information.

[1301] Step 5: Calculate the total purchase amount

[1302] Input: Obtained price, shipping, and points information.

[1303] Specific operation: The server uses this data to calculate the total amount.

[1304] Data processing and calculation: An algorithm is used to add up the price and shipping cost and deduct points. For example, if the price is 40,000 yen, the shipping cost is 500 yen, and the points are 1,000 points, the total will be (40,000 yen + 500 yen) - 1,000 points = 39,500 yen.

[1305] Output: Calculated gross amount data.

[1306] Step 6: Emotional purchasing decisions

[1307] Input: Calculated total amount data and user sentiment data.

[1308] Specific operation: The server compares the total amount data and determines the most appropriate purchasing destination taking into account the user's feelings.

[1309] Data processing and calculation: For users who show positive sentiment, other factors such as review ratings and delivery times are taken into account.

[1310] Output: Information on the most appropriate purchasing platform (platform name, price, shipping fee, points, reason for recommendation).

[1311] Step 7: Send supplier information to users

[1312] Input: Determined supplier information.

[1313] Specific operation: The server transmits the determined supplier information to the terminal.

[1314] Data processing and calculation: Formatting information including the reason for recommendation (e.g., "high reviews and fast delivery expected").

[1315] Output: Information on the best places to buy displayed on the user's device.

[1316] (Application example 2)

[1317] 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."

[1318] Conventional e-commerce systems provide product search results without considering the user's feelings, making it difficult to optimize the user's purchasing experience. In particular, determining the most economical purchasing destination without considering the user's feelings about the searched product can reduce user satisfaction.

[1319] 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.

[1320] In this invention, the server includes means for receiving a product search request, means for requesting product information from the APIs of multiple e-commerce platforms and acquiring information on prices, shipping costs, and earned points, means for calculating the total amount based on the acquired price, shipping costs, and earned points, means for determining the most economical and suitable purchasing destination based on the calculated total amount and the user's emotions, means for outputting information on the determined purchasing destination, and means for acquiring the user's facial expressions and voice data using a camera and microphone and analyzing them with an emotion engine. This makes it possible to present the most suitable purchasing destination taking the user's emotions into consideration.

[1321] The "means for receiving a product search request" is a function that sends a product search request generated by the terminal to the server when a user inputs a product name or product code into the search bar and presses the search button.

[1322] "Means for requesting product information from the APIs of multiple e-commerce platforms and obtaining information on prices, shipping fees, and earned points" refers to a function in which a server sends requests to the API endpoints of multiple e-commerce platforms and obtains the product information of each.

[1323] The "means for calculating the total amount based on the acquired price, shipping fee, and earned point information" is a function that the server uses the price, shipping fee, and earned point information acquired from each e-commerce platform to calculate the total amount.

[1324] "Means for determining the most economical and suitable purchasing source based on the calculated total amount and the user's emotions" is a function that selects the most suitable purchasing source by taking into consideration the total amount calculated by the server and the user's emotional data.

[1325] The "means for outputting information on the determined supplier" is a function by which the server notifies the user of information on the most suitable supplier.

[1326] "Means for acquiring the user's facial expressions and voice data using a camera and microphone and analyzing it with an emotion engine" refers to a function that acquires the user's facial images and voice, sends them to the emotion engine for analysis, and recognizes the user's emotions.

[1327] The "emotion engine" is a system that analyzes the user's facial expressions and voice data and classifies them into emotional categories such as positive, negative, and neutral.

[1328] "Total Calculation" is the process of adding up the acquired price and shipping costs and subtracting earned points to determine the actual total cost of the item.

[1329] This invention relates to an electronic commerce system that provides product search results taking into account the user's emotions. When a user makes a product search request via a terminal, the system recognizes the user's emotions and presents the most suitable purchasing destination. This section explains each processing step for recognizing the user's emotions and presenting the most suitable purchasing destination.

[1330] System Configuration

[1331] 1. Hardware and Software:

[1332] Device: A device such as a smartphone or tablet that has a built-in camera and microphone.

[1333] Server: A central server for accessing APIs of multiple e-commerce platforms.

[1334] Emotion engine: A software library for analyzing a user's facial expressions and voice and classifying them into emotional categories.

[1335] Flask: Used as a web application framework.

[1336] Requests: A Python library for sending HTTP requests.

[1337] Program processing overview

[1338] The device generates a product search request and sends it to the server. When the user enters a product name or code into the search bar and presses the search button, the device uses a camera and microphone to record the user's facial expressions and voice data. This data is sent to the emotion engine, which classifies the user's emotion as positive, negative, or neutral.

[1339] The server requests product information from the APIs of multiple e-commerce platforms. It calculates the total price based on the obtained price, shipping cost, and earned points information, and also combines the user's emotional data to determine the most economical and suitable purchasing destination. Finally, the server sends the information of the selected purchasing destination to the user's device.

[1340] Specific examples

[1341] For example, if a user searches for "smartphone" on their device, the device records image data and audio of them smiling at the camera. This data is analyzed by the emotion engine and recognized as a positive emotion. The server then retrieves product data from multiple e-commerce platforms, comparing it with information such as a price of ¥40,000, shipping of ¥500, 1,000 points, and a total of ¥39,500 on Rakuten, or a price of ¥39,000, shipping of ¥400, 800 points, and a total of ¥38,600 on Amazon.

[1342] Because the user's sentiment is positive, the server selects the optimal purchasing source by taking into consideration not only price and shipping costs, but also reviews and delivery time. In this case, the server selects Amazon, which has high reviews and is expected to deliver quickly, and sends that information to the user's device.

[1343] Prompt Sentence Examples

[1344] The prompt text that is entered when a user searches for "smartphone" is as follows:

[1345] Text input: "Smartphone"

[1346] Emotion data: image data and audio data (indicating a smile)

[1347] This allows users to quickly and efficiently select the best place to purchase products based on their emotions, significantly improving the user's purchasing experience.

[1348] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1349] Step 1:

[1350] The user enters the product name or product code into the search bar of the device and presses the search button. At this time, the device's camera and microphone record the user's facial expression and voice data. The input data, which is the product name and the user's facial expression and voice data, is sent to the subsequent processing step.

[1351] Step 2:

[1352] The device sends the user's facial and voice data to the emotion engine, which analyzes it to recognize the user's emotions. Emotional data is classified as positive, negative, or neutral. The input data is the user's facial and voice data, and the output data is the emotion category (positive, negative, or neutral).

[1353] Step 3:

[1354] Based on the product search request, the server requests product information from the API endpoints of multiple e-commerce platforms. The input data is the product name, and the request is sent to each platform. The output data is the price, shipping fee, and earned points information obtained from each platform.

[1355] Step 4:

[1356] The server calculates the total amount based on the acquired price, shipping fee, and earned point information. The total amount is the sum of the price and shipping fee and the earned point amount. The input data are the price, shipping fee, and earned point information, and the output data is the calculated total amount.

[1357] Step 5:

[1358] The server determines the most economical and suitable purchasing destination based on the calculated total price and the user's sentiment. If the sentiment data is positive, it also takes into account reviews and delivery time in addition to price and shipping costs. The input data are the calculated total price and sentiment data, and the output data is information on the optimal purchasing destination.

[1359] Step 6:

[1360] The server sends the information on the optimal supplier it has determined to the user's terminal, which then displays this information to the user. The input data is the optimal supplier information, and the output data is the supplier information displayed to the user.

[1361] For example, if a user searches for "smartphone" and smiles at the camera, the device sends that data to the emotion engine, which recognizes it as a positive emotion. The server then retrieves product information from multiple platforms, calculates the total price, and determines the optimal purchasing source, taking into account the emotion data. In this case, the server selects a platform with high reviews and the potential for fast delivery, and notifies the user of that information.

[1362] Through the above steps, the user can quickly select the most suitable place to purchase products according to their emotions.

[1363] 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.

[1364] 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.

[1365] 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.

[1366] 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.

[1367] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1368] 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.

[1369] 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).

[1370] 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.

[1371] 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."

[1372] 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.

[1373] 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).

[1374] 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.

[1375] 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.

[1376] 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.

[1377] 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.

[1378] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1379] 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.

[1380] 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.

[1381] 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.

[1382] 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.

[1383] 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.

[1384] The following is further disclosed regarding the above embodiment.

[1385] (Claim 1)

[1386] means for receiving a product search request;

[1387] A means for requesting product information from APIs of multiple e-commerce platforms and obtaining price, shipping fee, and earned point information;

[1388] A means for calculating the total amount based on the acquired price, shipping fee, and earned points information;

[1389] A means of comparing the calculated totals and determining the most economical purchasing source;

[1390] a means for outputting information on the determined supplier;

[1391] A system including:

[1392] (Claim 2)

[1393] The system of claim 1, wherein the total amount is calculated using an algorithm that adds up the price and shipping costs and subtracts the points earned.

[1394] (Claim 3)

[1395] 2. The system of claim 1, wherein the plurality of e-commerce platforms include at least one major domestic e-commerce platform and one major international e-commerce platform.

[1396] "Example 1"

[1397] (Claim 1)

[1398] means for receiving a product search request;

[1399] a means for requesting product information from data acquisition interfaces of a plurality of e-commerce sites and acquiring price, shipping fee, and earned point information;

[1400] A means for calculating the total amount based on the acquired price, shipping fee, and earned points information;

[1401] A means to compare the calculated totals and determine the most economical purchase source;

[1402] a means for outputting information on the determined supplier;

[1403] A system including:

[1404] (Claim 2)

[1405] The system of claim 1, wherein the total amount is calculated using an algorithm that adds up the price and shipping costs and subtracts the points earned.

[1406] (Claim 3)

[1407] 2. The system of claim 1, wherein the plurality of e-commerce sites include at least one major national e-commerce site and one major international e-commerce site.

[1408] "Application Example 1"

[1409] (Claim 1)

[1410] means for receiving a product search request;

[1411] A means for requesting product information from APIs of multiple e-commerce platforms and obtaining price, shipping fee, and earned point information;

[1412] A means for calculating the total amount based on the acquired price, shipping fee, and earned points information;

[1413] A means of comparing the calculated totals and determining the most economical purchasing source;

[1414] means for outputting information about the determined supplier to a mobile terminal;

[1415] A system including:

[1416] (Claim 2)

[1417] The system of claim 1, wherein the total amount is calculated using an algorithm that adds up the price and shipping costs and subtracts the points earned.

[1418] (Claim 3)

[1419] 2. The system of claim 1, wherein the plurality of e-commerce platforms include at least one major domestic e-commerce platform and one major international e-commerce platform.

[1420] "Example 2: Combining Emotion Engines"

[1421] (Claim 1)

[1422] means for receiving a product search request;

[1423] A means for requesting product information from APIs of multiple e-commerce platforms and obtaining price, shipping fee, and earned point information;

[1424] A means for calculating the total amount based on the acquired price, shipping fee, and earned points information;

[1425] A means of comparing the calculated totals and determining the most economical purchasing source;

[1426] means for recognizing a user's emotion;

[1427] means for filtering or sorting search results based on the recognized user sentiment;

[1428] a means for outputting information on the determined supplier;

[1429] A system including:

[1430] (Claim 2)

[1431] The system of claim 1, wherein the total amount is calculated using an algorithm that adds up the price and shipping costs and subtracts the points earned.

[1432] (Claim 3)

[1433] 2. The system of claim 1, wherein the plurality of e-commerce platforms include at least one major domestic e-commerce platform and one major international e-commerce platform.

[1434] "Application example 2 when combining emotion engines"

[1435] (Claim 1)

[1436] means for receiving a product search request;

[1437] A means for requesting product information from APIs of multiple e-commerce platforms and obtaining price, shipping fee, and earned point information;

[1438] A means for calculating the total amount based on the acquired price, shipping fee, and earned points information;

[1439] A means for determining the most economical and suitable purchasing destination based on the calculated total amount and the user's feelings;

[1440] a means for outputting information on the determined supplier;

[1441] A system including:

[1442] (Claim 2)

[1443] The system of claim 1, wherein the total amount is calculated using an algorithm that adds up the price and shipping costs and subtracts the points earned.

[1444] (Claim 3)

[1445] 2. The system according to claim 1, further comprising means for acquiring facial expressions and voice data of a user using a camera and a microphone and analyzing the data with an emotion engine.

[1446] (Claim 4)

[1447] 2. The system of claim 1, wherein the plurality of e-commerce platforms include at least one major domestic e-commerce platform and one major international e-commerce platform. [Explanation of symbols]

[1448] 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. means for receiving a product search request; A means for requesting product information from APIs of multiple e-commerce platforms and obtaining price, shipping fee, and earned point information; A means for calculating the total amount based on the acquired price, shipping fee, and earned points information; A means of comparing the calculated totals and determining the most economical purchasing source; a means for outputting information on the determined supplier; A system including:

2. 2. The system of claim 1, wherein the total amount is calculated by adding up the price and shipping cost and subtracting the points earned.

3. The system of claim 1 , wherein the plurality of e-commerce platforms include at least one major domestic e-commerce platform and one major international e-commerce platform.

Images