System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting information provided by a user; means for obtaining data from a social networking service of a recipient; means for analyzing the obtained data to extract interests of the recipient; means for generating candidate gifts based on the analysis; and means for suggesting the generated candidate gifts to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When choosing a gift, it is extremely difficult to determine what kind of gift the recipient will like. With so many options available, determining which is the best option takes time and effort, which often leaves users feeling stressed. Furthermore, it is difficult to accurately understand the recipient's tastes and preferences, which can result in choosing an inappropriate gift. There is a need to solve these challenges and provide users with a better gift selection experience. [Means for solving the problem]

[0005] The above-mentioned problem is solved by a system that includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, and a means for suggesting the generated gift candidates to the user. This system analyzes the recipient's hobbies and preferences in detail through the user's input of information about the recipient and linking the recipient's social media account. Based on the analysis results, the system instantly generates gift candidates that are optimal for the recipient and suggests them to the user. As a result, the user can accurately select the perfect gift in a short amount of time.

[0006] "Means for inputting user-provided information" refers to the interface or device that allows a user to input basic information about the recipient via an application or website.

[0007] "Means for obtaining data from the recipient's social networking service" refers to APIs and data collection systems for obtaining data such as posts, preferences, and interests from the recipient's social media account.

[0008] "Means for analyzing acquired data and extracting the recipient's interests" refers to methods and devices that analyze data acquired from SNS using algorithms such as natural language processing and image analysis to identify the recipient's hobbies and preferences.

[0009] "Means for generating gift candidates based on the analysis results" refers to an algorithm or system that lists multiple gift candidates based on the analyzed information, combines them, and presents them to the user.

[0010] "Means for suggesting generated gift candidates to users" refers to an interface or system that displays the generated gift candidate list on the user's device and suggests the most suitable gift for the user.

[0011] "Means for purchasing and shipping the gift items selected by the user" refers to the online payment system and shipping management system that allows the user to complete the purchase process for the gift selected by the user and proceed with the shipping process. [Brief explanation of the drawings]

[0012] [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

[0013] 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.

[0014] First, the terms used in the following description will be explained.

[0015] 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).

[0016] 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.

[0017] 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.

[0018] 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.

[0019] 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."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] This invention relates to a system that suggests optimal gifts based on information about the recipient and their activity data on social networking services (SNS). This system is composed of multiple components, including a user terminal, a server, and various APIs.

[0034] Program processing description

[0035] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0036] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[0037] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[0038] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[0039] Finally, the server sends the optimized gift candidate list to the user terminal and suggests it to the user, who then displays the list to the user, allowing the user to select a desired item from the suggested gifts.

[0040] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0041] Specific examples

[0042] A specific example is given below.

[0043] scenario:

[0044] User "Yamada Hanako" wants to choose a birthday present for her 35-year-old friend Tanaka Taro.

[0045] 1. User device: Hanako Yamada accesses the application and enters Taro Tanaka's information (age 35, male, friend).

[0046] 2. User device: Hanako Yamada requests permission to access Taro Tanaka's Instagram account.

[0047] 3. User terminal: After obtaining permission to use, provide account information to the system.

[0048] 4. Server: Collects Tanaka Taro's posting data on "cooking," "sports," and "travel" via the SNS API.

[0049] 5. Server: Analyzes the text and image data and extracts Taro Tanaka's interests (e.g., sports equipment, kitchen gadgets, travel-related goods).

[0050] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[0051] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[0052] 8. Server: Sends the optimized gift candidate list to the user device.

[0053] 9. User device: Display suggested gift items for Hanako (e.g., jogging shoes, the latest blender, and a compact travel bag).

[0054] 10. User device: Hanako Yamada selects jogging shoes and completes the purchase process.

[0055] 11. Server: Notify the user and recipient once the purchase and delivery process is complete.

[0056] In this way, a system is provided that allows users to select the most suitable gift in a short amount of time without stress.

[0057] The processing flow will be explained below.

[0058] Step 1:

[0059] User device: The user accesses the Present Match AI and enters basic information about the person they want to give a gift to (name, age, gender, relationship, etc.).

[0060] Step 2:

[0061] User Device: The user selects the option to link the social networking service (SNS) account of the person to whom the gift is to be given.

[0062] Step 3:

[0063] User device: The user requests and receives approval for access to the recipient's social media account.

[0064] Step 4:

[0065] Server: Uses the SNS API to retrieve data such as the recipient's liked posts, shared articles, followed accounts, and post content.

[0066] Step 5:

[0067] Server: Analyzes the acquired SNS data using natural language processing (NLP) algorithms, tokenizes the text data, and uses topic modeling (e.g., LDA) to extract the recipient's areas of interest.

[0068] Step 6:

[0069] Server: Image and video data is analyzed using image recognition algorithms (e.g., CNN) to identify interest in specific brands and products.

[0070] Step 7:

[0071] Server: Based on the extracted areas of interest and other information, collect relevant gift suggestions from online marketplaces and APIs of specific gift shops.

[0072] Step 8:

[0073] Server: Obtains detailed information about each product (price, rating, category, etc.) and filters it according to the user's budget or special requirements.

[0074] Step 9:

[0075] Server: Sends the optimized gift candidate list to the user device.

[0076] Step 10:

[0077] User terminal: Display a list of suggested gifts to the user and allow the user to select the desired gift item.

[0078] Step 11:

[0079] User device: The user selects the gift item and begins the purchase process.

[0080] Step 12:

[0081] User terminal: Provides an interface for entering payment and shipping information.

[0082] Step 13:

[0083] Server: Once the purchase process is complete, we contact the partner gift shop or marketplace API to check stock availability and proceed with the delivery process.

[0084] Step 14:

[0085] Server: Sends purchase completion notification and shipping information to the user and recipient.

[0086] Step 15:

[0087] User device: Display purchase completion notification and shipping information to the user.

[0088] Example 1

[0089] 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."

[0090] Today's consumers often spend a lot of time and effort selecting gifts, which can be especially challenging when considering the recipient's preferences. Therefore, there is a need for a system that can suggest the best gift based on the recipient's interests. However, existing systems lack the ability to collect and analyze social media data, making it difficult to meet individual needs.

[0091] 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.

[0092] In this invention, the server includes means for inputting information provided by a user, means for acquiring data from the recipient's social networking service, means for analyzing the acquired data and extracting the recipient's interests, means for analyzing the data using natural language processing and image analysis algorithms, means for acquiring relevant gift candidates from online marketplaces and databases of specific gift shops based on the analysis results, means for filtering the gift candidates taking into account the user's budget and special requirements, and means for suggesting the generated gift candidates to the user, thereby enabling the user to select the most suitable gift in a short period of time.

[0093] "User" means an individual or organization that uses the system, inputs information through a terminal, and makes gift suggestions and makes purchases.

[0094] "Terminal" refers to a computer device or mobile device that a user accesses and that allows the input and display of information.

[0095] "Server" refers to the central device that manages the entire system, collects, analyzes, filters, and recommends optimal gifts.

[0096] A "social networking service" is an online platform that enables people to communicate over the internet and is subject to data collection.

[0097] "Data Acquisition Methods" refers to APIs and other technical methods for collecting the required information from social networking services.

[0098] "Natural language processing" refers to technology that analyzes acquired text data and understands the recipient's interests and concerns.

[0099] "Image analysis algorithm" refers to technology that analyzes acquired image data and recognizes characteristics such as specific brands and products.

[0100] "Analysis Results" refers to information about the recipient's interests and concerns obtained by analyzing information collected using data acquisition means using natural language processing and image analysis algorithms.

[0101] "Online marketplace" refers to an online commercial platform where various products can be purchased.

[0102] "Gift suggestion means" refers to a technical method for presenting gift candidates generated based on the analysis results to the user.

[0103] MODE FOR CARRYING OUT THE INVENTION

[0104] This invention is a system that suggests optimal gifts based on information about the recipient of a gift and the recipient's activity data on a social networking service. This system is composed of multiple components, including a user terminal, a server, and various APIs. Detailed embodiments are described below.

[0105] First, the user accesses the gift suggestion system using a device. The application home screen displays a "Gift Suggestion" option, and the user selects this option.

[0106] The user is presented with a form where they can enter basic information about the recipient, such as their name, age, gender, and relationship. Following this, the user selects the option to link their social media account. Here, the user obtains permission to access their social media account (e.g., Instagram, Facebook, etc.) and provides their account information to the system.

[0107] The device sends the basic information entered by the user and social media account information to a server, which then uses social media APIs (such as Instagram API and Facebook Graph API) to collect data such as the other person's "liked" posts, shared articles, accounts they follow, and post content.

[0108] The server analyzes the collected data using natural language processing (NLP) and image analysis algorithms. Specifically, it tokenizes text data and extracts multiple themes using LDA (Latent Dirichlet Allocation). Image data is analyzed using CNN (Convolutional Neural Networks) to extract interest in specific brands and products. This allows for highly accurate detection of a person's interests.

[0109] Based on the analysis results, the server searches for relevant gift suggestions from online marketplaces (e.g., Amazon API or Rakuten API) or specific gift shop APIs, filtering them based on the user's budget and special requirements (e.g., eco-friendly products or specific brands).

[0110] The server then generates a list of optimal gift options and sends it to the user's device, where the user can select the items they want from the list, including details such as images, prices, and ratings for each item.

[0111] When a user selects a gift item, the user's device displays a checkout screen where the user can enter payment and delivery information. The server receives the information, checks inventory, and completes the purchase via the marketplace API. Finally, the server sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0112] Specific examples

[0113] A specific example is given below.

[0114] scenario:

[0115] User A wants to give a birthday gift to friend B who is 35 years old:

[0116] 1. User A accesses the application and enters B's information (35 years old, male, friend).

[0117] 2. User A requests permission to access User B's Instagram account.

[0118] 3. After User A has been granted access, he / she provides his / her account information to the system.

[0119] 4. The server uses the SNS API to collect B's posts about "cooking," "sports," and "travel."

[0120] 5. The server analyzes the collected data and extracts B's interests (e.g., sports equipment, kitchen gadgets, travel-related products).

[0121] 6. The server uses the Amazon API or Rakuten API to search for related products and generate gift suggestions.

[0122] 7. The server filters the gift suggestions taking into account User A's budget and special requirements.

[0123] 8. The server sends the list of best gift candidates to User A's device.

[0124] 9. User A selects jogging shoes from the suggested gift items (e.g., jogging shoes, a new blender, and a compact travel bag) and completes the purchase.

[0125] 10. The server notifies User A and Recipient B once the purchase and delivery process is complete.

[0126] This system allows users to choose the perfect gift in a short amount of time.

[0127] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0128] Step 1:

[0129] The user accesses the gift suggestion system through a terminal and inputs basic information about the recipient (name, age, gender, relationship). The input data includes the user's basic information. The terminal then sends this information to the server.

[0130] Step 2:

[0131] The server receives the basic information sent by the user and displays a screen on the user's device that includes the option to allow SNS account linking. The SNS account linking screen is generated as the output.

[0132] Step 3:

[0133] The user grants permission to access the other person's social media account (e.g., Instagram, Facebook, etc.). The user enters their social media account information and completes authorization authentication. The social media account information is included as input data.

[0134] Step 4:

[0135] The device sends the basic information and SNS account information entered by the user to the server. The input data includes the basic information and SNS account information. The output is the completion of information transfer to the server.

[0136] Step 5:

[0137] The server uses SNS APIs (e.g., Instagram API, Facebook Graph API) to collect data such as posts that the other person has "liked," articles that they have shared, accounts they are following, and the content of their posts. SNS account information is used as input, and the other person's SNS data is collected as output. Specific operations include making a request to the SNS API, retrieving the data, and saving the data.

[0138] Step 6:

[0139] The data collected by the server is analyzed using natural language processing (NLP) and image analysis algorithms. Social media data is used as input. Specific operations include tokenizing text data, topic modeling using LDA (Latent Dirichlet Allocation), and image recognition using CNN (Convolutional Neural Network). The output is data indicating the other person's interests and concerns.

[0140] Step 7:

[0141] The server uses the analysis results to search for relevant gift suggestions from online marketplaces (e.g., Amazon API or Rakuten API) or specific gift shop APIs. The analysis results are used as input and a list of gift suggestions is generated as output. Specific operations include making a request to the API, gathering product information, and generating a gift suggestion list.

[0142] Step 8:

[0143] The server filters gift suggestions, taking into account the user's budget and special requirements (e.g., eco-friendly products or specific brands). The input includes user preferences and a list of suggestions. The output is an optimized list of gift suggestions. The specific operation involves running a filtering algorithm.

[0144] Step 9:

[0145] The server sends the best gift candidate list to the user device, which contains the filtered gift list as input, and displays the gift candidate list on the user device as output.

[0146] Step 10:

[0147] The user selects the desired item from the list and clicks the "Proceed to Checkout" button, including the gift wishlist as input.

[0148] Step 11:

[0149] The terminal displays a checkout screen where the user enters payment and shipping information. The input includes the user's payment and shipping information.

[0150] Step 12:

[0151] The server receives the entered payment information, checks inventory and processes the purchase via the marketplace API. The output is a purchase completion notification and shipping information. Specific operations include making a request to the API, checking inventory, processing the payment, and sending a notification email.

[0152] Step 13:

[0153] The server sends a purchase completion notification and shipping information to the user and recipient, respectively. The input contains the result of the purchase process. The output is the completion of the notification and shipping information.

[0154] (Application example 1)

[0155] 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."

[0156] With conventional gift selection systems, it was difficult to suggest gifts that accurately reflected the recipient's interests, and there were insufficient means to provide detailed information to users in an easy-to-understand manner. This made it difficult for users to quickly select the perfect gift for the recipient, and the selection and purchase process was stressful.

[0157] 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.

[0158] In this invention, the server includes a means for inputting information provided by the user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for displaying detailed information (price, rating, category, etc.) of the generated gift candidates, and a means for purchasing and shipping the gift item selected by the user, thereby enabling the user to quickly select the best gift for the recipient and complete the purchase procedure without stress.

[0159] "User" refers to an individual who uses the Gift Suggestion System.

[0160] "Recipient" means the individual to whom you wish to send a Gift.

[0161] "Social Networking Service" refers to an online platform used by the Recipient that allows the Recipient to share their posts and activity data.

[0162] "Means for Obtaining Data" refers to the means for collecting the required data from the recipient's social networking service.

[0163] "Means for analyzing data" refers to means for extracting the recipient's interests and concerns using the acquired data.

[0164] The "means for generating gift candidates" refers to a means for generating gift candidates suitable for a recipient based on the analysis results.

[0165] "Detailed information" refers to specific information such as the price, rating, and category of the gift candidate.

[0166] "Purchase and Delivery Method" means the method by which a User purchases and completes the delivery process for the selected Gift.

[0167] This invention relates to a system that suggests optimal gifts based on information about the recipient and their activity data on social networking services (SNS). The system is composed of multiple components, including a user terminal, a server, and various APIs.

[0168] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0169] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, followed accounts, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests. Specifically, the server tokenizes the obtained text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. Furthermore, the server uses image recognition algorithms (e.g., CNN) to analyze posted images and extract interest in specific brands and products.

[0170] Next, based on the analysis results, the server retrieves relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, rating, category, etc.) and extracts gift suggestions that best fit the recipient's profile. This includes filtering based on the user's budget and special requirements. Finally, the server sends the optimized gift suggestion list to the user's device and makes suggestions to the user.

[0171] The user's device displays this list to the user, allowing them to select the desired gift item from the suggested gifts. After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0172] Specific examples

[0173] A specific example is given below.

[0174] scenario

[0175] A user wants to choose a birthday gift for a friend who is turning 35. The user accesses the application and enters the recipient's information (age, gender, friendship status). They also request permission to access the recipient's social media account and provide the account information to the system. The server collects the recipient's posts related to "cooking," "sports," and "travel" via the social media API. It analyzes the text and image data to extract the recipient's interests (e.g., sports equipment, kitchen gadgets, travel-related goods). It uses the marketplace API to obtain detailed information about related products and generate optimal gift suggestions. It filters the gift suggestions taking into account the user's budget and special requirements and sends the optimized gift suggestion list to the user's device. The user reviews the suggested gift items, selects a pair of jogging shoes, and completes the purchase. The server notifies the user and the recipient once the purchase and delivery process is complete.

[0176] Prompt Sentence Examples

[0177] Example input

[0178] "I'd like some suggestions for the perfect gift for my friend's birthday. Here are their social media accounts."

[0179] Example output

[0180] "Suggested gifts include: jogging shoes, a new blender, and a compact travel bag."

[0181] The specific hardware and software used includes social media APIs (e.g., Instagram API, Twitter API), natural language processing libraries (e.g., NLTK, spaCy), and image analysis models (e.g., ResNet50). Additionally, programming languages ​​such as Python and cloud services (e.g., AWS, Google Cloud) can be used for the server.

[0182] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0183] Step 1:

[0184] A user accesses the gift suggestion system using a device. The user enters basic information about the person they want to give a gift to (such as name, age, gender, and relationship). They also select the option to link the recipient's social media account. This information is sent from the device to the server. The input data (basic information, social media link) is stored on the server and used for analysis.

[0185] Step 2:

[0186] The server accesses the recipient's SNS account information and uses the API to obtain SNS data (liked posts, shared articles, followed accounts, post content, etc.). It obtains the recipient's activity data using the SNS API (e.g., Instagram API, Twitter API). The obtained data is divided into text data and image data. The input is data from the SNS API, and the output is text data and image data for analysis.

[0187] Step 3:

[0188] The server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests. Specifically, it tokenizes the text data and identifies areas of interest using topic modeling (e.g., LDA). It also analyzes posted images using image recognition algorithms (e.g., ResNet50) to extract interest in specific brands and products. The input is the text data and image data for analysis, and the output is the extracted recipient's interests.

[0189] Step 4:

[0190] Based on the analysis results, the server retrieves related gift suggestions from the APIs of online marketplaces or specific gift shops. It uses the APIs of online marketplaces (e.g., Amazon API, Rakuten Market API) to collect detailed information (price, rating, category, etc.) about related products. The input is the analysis results and data from the marketplace API, and the output is a list of gift suggestions.

[0191] Step 5:

[0192] The server filters gift suggestions based on the user's budget and special requirements, listing items that fit within a budget range or fall into a specific category. The input is a list of gift suggestions and user preferences, and the output is a filtered list of optimal gift suggestions.

[0193] Step 6:

[0194] The server sends the optimized gift candidate list to the user terminal. The user terminal displays this list to the user. The user can select desired items from the suggested gifts. The input is the optimized gift candidate list, and the output is the gift candidates presented to the user.

[0195] Step 7:

[0196] For the gift items selected by the user, the user device provides an interface to support the purchase process (input of payment information and delivery information). The user enters the required information and completes the purchase process. The input is the gift items selected by the user and payment and delivery information, and the output is the completion of the purchase process.

[0197] Step 8:

[0198] The server queries partner gift shops and marketplace APIs to check stock availability and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient. The input is purchase completion information, and the output is the stock availability result, the start of delivery procedures, and a completion notification.

[0199] 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.

[0200] This invention is a system that suggests the perfect gift based on information about the person a user wants to give a gift to and their activity data on social networking services (SNS), and further combines it with an emotion engine to recognize the user's emotions and improve the level of personalization of the suggested gifts. This system is composed of multiple components, including a user terminal, a server, various APIs, and an emotion engine.

[0201] Program processing description

[0202] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0203] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[0204] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[0205] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[0206] Furthermore, the present invention incorporates an emotion engine to recognize users' emotions in real time and optimize gift suggestions based on their emotions. The emotion engine uses a camera and microphone to analyze users' facial expressions, voice tone, and input content.

[0207] The emotion engine includes facial recognition software that reads emotions from a user's facial expressions and voice analysis software that analyzes emotions from a user's tone of voice, allowing the engine to analyze the user's emotional state (e.g., joy, surprise, interest, etc.) while browsing gift suggestions and prioritize gift suggestions based on the user's emotions.

[0208] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0209] Specific examples

[0210] A specific example is given below.

[0211] scenario:

[0212] A user named "Yamada Hanako" wants to choose a birthday present for her friend Tanaka Taro, who is 35. Furthermore, the gift is optimized taking into account Yamada Hanako's feelings.

[0213] 1. User device: Hanako Yamada accesses the application and enters Taro Tanaka's information (age 35, male, friend).

[0214] 2. User device: Hanako Yamada requests permission to access Taro Tanaka's Instagram account.

[0215] 3. User terminal: After obtaining permission to use, provide account information to the system.

[0216] 4. Server: Collects Tanaka Taro's posting data on "cooking," "sports," and "travel" via the SNS API.

[0217] 5. Server: Analyzes the text and image data and extracts Taro Tanaka's interests (e.g., sports equipment, kitchen gadgets, travel-related goods).

[0218] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[0219] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[0220] 8. Server: Use the emotion engine to analyze Hanako Yamada's emotional state while she browses gift suggestions and optimize gift suggestions based on her emotions.

[0221] 9. Server: Sends the optimized gift candidate list to the user device.

[0222] 10. User device: Display suggested gift items for Hanako (e.g., jogging shoes, the latest blender, and a compact travel bag).

[0223] 11. User device: Hanako Yamada selects jogging shoes and completes the purchase process.

[0224] 12. Server: Notify the user and recipient once the purchase and delivery process is complete.

[0225] In this way, a system is provided that allows users to select the most suitable gift in a short time while taking their emotions into consideration.

[0226] The processing flow will be explained below.

[0227] Step 1:

[0228] User device: The user accesses the Present Match AI and enters basic information about the person they want to give a gift to (name, age, gender, relationship, etc.).

[0229] Step 2:

[0230] User Device: The user selects the option to link the social networking service (SNS) account of the person to whom the gift is to be given.

[0231] Step 3:

[0232] User device: The user requests and receives approval for access to the recipient's social media account.

[0233] Step 4:

[0234] Server: Uses the SNS API to retrieve data such as the recipient's liked posts, shared articles, followed accounts, and post content.

[0235] Step 5:

[0236] Server: Analyzes the acquired SNS data using natural language processing (NLP) algorithms, tokenizes the text data, and uses topic modeling (e.g., LDA) to extract the recipient's areas of interest.

[0237] Step 6:

[0238] Server: Image and video data is analyzed using image recognition algorithms (e.g., CNN) to identify interest in specific brands and products.

[0239] Step 7:

[0240] Server: Based on the extracted areas of interest and other information, collect relevant gift suggestions from online marketplaces and APIs of specific gift shops.

[0241] Step 8:

[0242] Server: Obtains detailed information about each product (price, rating, category, etc.) and filters it according to the user's budget or special requirements.

[0243] Step 9:

[0244] Server: Sends the optimized gift candidate list to the user device.

[0245] Step 10:

[0246] User terminal: Display a list of suggested gifts to the user and allow the user to select the desired gift item.

[0247] Step 11:

[0248] User device: The user selects the gift item and begins the purchase process.

[0249] Step 12:

[0250] User terminal: Provides an interface for entering payment and shipping information.

[0251] Step 13:

[0252] Server: Once the purchase process is complete, we contact the partner gift shop or marketplace API to check stock availability and proceed with the delivery process.

[0253] Step 14:

[0254] Server: Sends purchase completion notification and shipping information to the user and recipient.

[0255] Step 15:

[0256] User device: Display purchase completion notification and shipping information to the user.

[0257] Step 16:

[0258] Emotion Engine: Uses the camera and microphone to collect the user's facial expressions and tone of voice as they browse gift options.

[0259] Step 17:

[0260] Emotion engine: Analyzes collected data and recognizes the user's emotional state (e.g., joy, surprise, interest).

[0261] Step 18:

[0262] Emotion Engine: Based on the recognized emotional state, it reprioritizes the gift suggestion list and lists gifts that best fit the user's emotions.

[0263] Step 19:

[0264] User device: Display the re-prioritized gift idea list to the user.

[0265] Step 20:

[0266] User device: The user selects a gift from the reprioritized list and initiates the final purchase process.

[0267] Example 2

[0268] 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."

[0269] Conventional gift suggestion systems can generate gift candidates based on information provided by users and social media data, but they do not take the user's emotional state into account, resulting in a low level of personalized gift suggestions. Furthermore, the gift selection process cannot reflect the user's emotional changes in real time, making it difficult to suggest optimal gifts. Furthermore, the suggested gifts may not meet the user's expectations, resulting in a poor user experience.

[0270] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0271] In this invention, the server includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, a means for recognizing the user's emotions and optimizing the gift candidates, and a means for suggesting the generated gift candidates to the user, thereby enabling highly personalized gift suggestions that take the user's emotional state into consideration.

[0272] "Information provided by the user" refers to basic information about the recipient (such as name, age, gender, relationship, etc.) that the user enters into the system.

[0273] "Means of obtaining data from the recipient's social networking service" refers to a mechanism for accessing the recipient's social media account via an API or other means and collecting data such as posts, "likes," shared articles, and followed accounts.

[0274] "Means of analyzing the acquired data and extracting the recipient's interests and concerns" refers to methods of using natural language processing (NLP) and image analysis algorithms to identify the recipient's interests and areas of concern from the collected social media data.

[0275] "Means for generating gift suggestions based on analysis results" refers to a system that uses APIs of online marketplaces and gift shops to create a list of related products based on extracted interests.

[0276] "Means to recognize user emotions and optimize gift candidates" refers to a system that uses cameras and microphones to analyze the user's facial expressions and tone of voice in real time and adjusts the ranking of gift candidates based on the analysis results.

[0277] "Means for suggesting generated gift candidates to a user" refers to a system that transmits the optimized gift candidate list to a user terminal and displays it through a user interface.

[0278] "Means for purchasing and shipping gift items selected by the user" refers to a system that provides an interface for users to enter payment and shipping information for the gift selected by the user, and processes the items to be properly delivered after the purchase is completed.

[0279] "Methods of using recipient account information linked by the user" refers to methods of linking social media account information and collecting necessary data with the user's permission.

[0280] This invention relates to a system that suggests the perfect gift based on information about the person a user wants to give a gift to and their activity data on social networking services (SNS). Furthermore, this system is combined with an emotion engine, which can recognize the user's emotions and improve the level of personalization of the gifts it suggests. This system is composed of multiple components, including a user terminal, a server, various APIs, and the emotion engine.

[0281] The user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0282] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[0283] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[0284] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[0285] Furthermore, the present invention incorporates an emotion engine to recognize a user's emotions in real time and optimize gift suggestions based on those emotions. The emotion engine uses a camera and microphone to analyze a user's facial expressions, voice tone, and input content. The emotion engine includes facial expression recognition software that reads emotions from the user's facial expressions and voice analysis software that analyzes emotions from the user's voice tone. This allows the system to analyze the user's emotional state (e.g., joy, surprise, interest, etc.) while browsing gift suggestions and prioritize gift suggestions based on the user's emotions.

[0286] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0287] Specific examples

[0288] A specific example is given below.

[0289] scenario:

[0290] A user wants to choose a birthday gift for a friend, and further optimizes the gift by taking emotions into account.

[0291] 1. User device: The user accesses the application and enters their friend's information (age, gender, relationship, etc.).

[0292] 2. User device: The user requests permission to access a friend's social media account.

[0293] 3. User terminal: After obtaining permission to use, provide account information to the system.

[0294] 4. Server: Collects friends' posting data about "cooking," "sports," and "travel" via SNS API.

[0295] 5. Server: Analyzes text and image data to extract friends' interests (e.g., sports equipment, kitchen gadgets, travel-related items).

[0296] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[0297] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[0298] 8. Server: Uses an emotion engine to analyze the emotional state of the user while browsing gift suggestions and optimize gift suggestions based on that emotion.

[0299] 9. Server: Sends the optimized gift candidate list to the user device.

[0300] 10. User device: Display suggested gift items to the user (e.g., jogging shoes, the latest blender, a compact travel bag).

[0301] 11. User device: The user selects the jogging shoes and completes the purchase.

[0302] 12. Server: Notify the user and recipient once the purchase and delivery process is complete.

[0303] Example prompts for generative AI models

[0304] Below are some examples of specific prompt sentences.

[0305] Prompt Sentence Examples

[0306] A user accesses a system that suggests the best gift for a friend's birthday based on social media data and the user's emotions. Explain all the steps the system takes, including the information the user provides to the system, data analysis, and emotion recognition.

[0307] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0308] Step 1: Enter your user information

[0309] Users simply enter basic information about the recipient (such as name, age, gender, and relationship) into the device.

[0310] Input is basic information provided by the user.

[0311] The output is basic information stored on the device.

[0312] Specific behavior: The user enters basic information into the form and clicks the "Next" button.

[0313] Step 2: Obtain and send recipient's social media account information

[0314] Users simply select the option to request permission to link to the other person's social media account.

[0315] The input is the user's social media account information and link permission of the other person.

[0316] The output is the social media account information and permissions sent to the server.

[0317] Specific operation: The user allows access to the social networking account and sends the link information.

[0318] Step 3: Collect social media data

[0319] The server uses an API to access the recipient's social media account and collect the necessary data.

[0320] The input is the SNS account information sent to the server.

[0321] The output is collected social media data (likes, shared posts, followed accounts, post content, etc.).

[0322] Specific operation: The server calls the SNS API and obtains the recipient's activity data.

[0323] Step 4: Analyze the data

[0324] The server analyzes the collected social media data using natural language processing (NLP) and image analysis algorithms.

[0325] The input is collected social media data.

[0326] The output is an analysis that indicates the recipient's interests.

[0327] What it does: The server tokenizes the text data, identifies regions of interest using topic modeling (e.g., LDA), and analyzes the images using image recognition algorithms (e.g., CNN).

[0328] Step 5: Generate gift suggestions

[0329] Based on the analysis results, the server retrieves relevant gift suggestions from APIs of online marketplaces and gift shops.

[0330] Inputs are the analysis results and the user's budget and special requirements.

[0331] The output is a generated list of gift suggestions.

[0332] Specific operation: The server calls the product's API to obtain detailed information such as price, rating, category, etc.

[0333] Step 6: Emotion Engine in Action

[0334] The device uses a camera and microphone to collect the user's facial expressions and voice tone.

[0335] The input is the user's facial expression data and voice data.

[0336] The output is the analyzed emotion data.

[0337] How it works: The device uses facial recognition and voice analysis software to analyze emotions.

[0338] Step 7: Optimize and display gift ideas

[0339] The server prioritizes gift suggestions based on the user's emotional data.

[0340] The inputs are emotion data and a gift candidate list.

[0341] The output is an optimized gift suggestion list.

[0342] Specific operation: The server adjusts the priority of gift candidates based on the emotional data and sends the list to the user's device.

[0343] Step 8: Gift Selection and Checkout

[0344] Users simply select the most suitable item from the displayed gift options.

[0345] The input is an optimized gift suggestion list.

[0346] The output is the selected gift item.

[0347] What happens: The user adds the selected gift item to their cart and begins the checkout process.

[0348] Step 9: Purchase completion and notification

[0349] The server queries partner gift shops and marketplace APIs to check inventory and process shipping.

[0350] The input is the selected gift item and shipping information.

[0351] The output is a confirmation of purchase completion and shipping information.

[0352] What happens: The server sends a notification to the user and recipient once the purchase is complete.

[0353] (Application example 2)

[0354] 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."

[0355] Conventional gift suggestion systems suggest gifts by taking into account the recipient's information and social media data, but because they are unable to consider the user's emotions, it is difficult to suggest the optimal gift that is in line with the user's feelings. Furthermore, there are cases where the suggested gift does not perfectly match the recipient's interests. Therefore, there was a need for a system that could help users select a gift that satisfies them.

[0356] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, a means for suggesting the generated gift candidates to the user, and a means for recognizing the user's emotions in real time and optimizing the suggested gift candidates. This makes it possible to suggest optimal gifts based on the recipient's interests while taking the user's emotions into consideration.

[0357] The "means for inputting information provided by the user" refers to an input device and software that allows the user to input basic information about the recipient, budget, etc.

[0358] "Means for obtaining data from the recipient's social networking service" refers to the means of communication and software for accessing the recipient's social networking account information and obtaining data such as posts, likes, and shared articles via API.

[0359] "Means for analyzing acquired data and extracting the recipient's interests" refers to hardware and software that uses natural language processing and image analysis algorithms to analyze acquired SNS data and identify the recipient's areas of interest.

[0360] The "means for generating gift candidates based on the analysis results" refers to software that obtains related product information from the APIs of online marketplaces and gift shops based on the analyzed interests and generates gift candidates.

[0361] The "means for suggesting generated gift candidates to the user" refers to a display device and software for presenting the generated multiple gift candidates to the user and assisting in the selection.

[0362] "Means for recognizing a user's emotions in real time and optimizing suggested gift candidates" refers to hardware and software that uses a camera and microphone to analyze emotions from a user's facial expressions and tone of voice, and optimizes the prioritization of gift candidates based on the user's emotions.

[0363] This invention is realized by constructing a gift suggestion system using a user terminal and a server. This system includes means for inputting information provided by a user, means for acquiring data from the recipient's social networking service, means for analyzing the acquired data and extracting the recipient's interests, means for generating gift candidates based on the analysis results, means for suggesting the generated gift candidates to the user, and means for recognizing the user's emotions in real time and optimizing the suggested gift candidates.

[0364] First, the user device provides an input device and software that allows the user to input basic information about the recipient, their budget, etc. This input information is sent to the server. Meanwhile, the recipient's social media account information is also linked to the user, and the server obtains the recipient's posts, likes, shared articles, etc. through the social media API. The obtained data is then analyzed on the server using natural language processing tools (e.g., TextBlob) and image analysis algorithms (e.g., CNN) to extract the recipient's interests and concerns.

[0365] Based on the analysis results, the server retrieves relevant gift suggestions from online marketplace APIs and gift shop APIs, and obtains detailed information (price, rating, category, etc.). This generates gift suggestions that take into account the user's budget and special requirements. Furthermore, it uses an emotion engine (e.g., FER) to recognize the user's real-time emotions through the camera and microphone on the user's device. Based on this, the priority of gift suggestions is optimized and suggested to the user.

[0366] Specifically, the server begins with a step in which a user accesses the application and enters the recipient's basic information and social media account. For example, suppose a user named "Yamada Hanako" wants to choose a gift for a "friend (35 years old, male)." The user links her "Instagram account," and the server obtains the social media data. Analysis reveals that she is interested in "cooking," "sports," and "travel," and generates gift suggestions based on that. After that, the camera determines that Yamada Hanako's emotion is "joy," and sports and travel-related goods are prioritized as suggestions.

[0367] Example prompts to input to the generative AI model:

[0368] "Please enter the name and social media account of the person you would like to give the gift to:

[0369] Name: Yamada Hanako

[0370] Social Media Account: example_user

[0371] Next, enter your budget (e.g., 5000 yen):

[0372] Budget: 5,000 yen

[0373] Turn on the camera and start emotion recognition.

[0374] ...

[0375] We're optimizing gift suggestions...

[0376] Perfect gift idea list:

[0377] 1. Jogging shoes

[0378] 2. Modern Blender

[0379] 3. Compact travel bag

[0380] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0381] Step 1:

[0382] The user enters the basic information and social media account information of the person they want to give the gift to.

[0383] Input: Name, age, gender, relationship, SNS account information

[0384] Output: The acquired information is sent from the device to the server.

[0385] Specific operation: When a user enters the required information into the input form on the terminal and clicks the send button, the terminal sends this information to the server.

[0386] Step 2:

[0387] The server accesses the recipient's SNS account and obtains the recipient's posted data, etc., via the SNS API.

[0388] Input: Recipient's SNS account information

[0389] Output: Post data of recipients, such as likes and shared posts, obtained from the SNS API

[0390] What it does: The server sends an API request to the linked social media account and receives data from the social media platform in response.

[0391] Step 3:

[0392] The server analyzes the acquired SNS data using natural language processing and image analysis algorithms to extract the recipient's interests and concerns.

[0393] Input: SNS data (text and images)

[0394] Output: A list of keywords related to the recipient's interests

[0395] How it works: The server uses TextBlob to analyze text and topic modeling to identify areas of interest, and uses CNN to analyze image data and extract interest in specific brands and products.

[0396] Step 4:

[0397] The server retrieves gift suggestions from the online marketplace API or gift shop API based on the analysis results.

[0398] Input: List of keywords of interest

[0399] Output: A list of related gift ideas and detailed information about each item

[0400] Specific operation: The server sends a request including keywords to the marketplace API and receives related product information in response.

[0401] Step 5:

[0402] The server filters gift suggestions, taking into account the user's budget and special requirements.

[0403] Input: Gift idea list, user budget information, special requirements

[0404] Output: A filtered list of gift ideas

[0405] What happens: The server checks the details of each product and selects the appropriate product based on the user's budget and requirements.

[0406] Step 6:

[0407] The terminal uses the user's camera and microphone to recognize the user's emotions in real time.

[0408] Input: User's facial and voice data

[0409] Output: User's emotional state (e.g., happy, surprised, etc.)

[0410] Specific operation: The device collects data in real time from the camera and microphone and analyzes the data using FER and voice analysis software.

[0411] Step 7:

[0412] The server optimizes the prioritization of gift candidates based on the user's emotional state.

[0413] Input: A filtered list of gift ideas, the user's emotional state

[0414] Output: Optimized list of gift ideas

[0415] Specific operation: The server takes into account the user's emotions and prioritizes placing the most suitable gifts at the top of the list.

[0416] Step 8:

[0417] The terminal displays the optimized gift candidate list to the user, and the user selects a gift.

[0418] Input: A list of optimized gift ideas

[0419] Output: Gift items selected by the user

[0420] Specific operation: The device displays a list of gift options on the screen, and the user selects the desired item.

[0421] Step 9:

[0422] The server processes the purchase and delivery of the selected gift item.

[0423] Input: Gift items selected by user, payment information, shipping information

[0424] Output: Purchase confirmation message, delivery confirmation message

[0425] Specific operation: The server accesses the marketplace API to complete the purchase, confirms the shipping information, and notifies the user and recipient.

[0426] 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.

[0427] 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.

[0428] 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.

[0429] [Second embodiment]

[0430] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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."

[0442] This invention relates to a system that suggests optimal gifts based on information about the recipient and their activity data on social networking services (SNS). This system is composed of multiple components, including a user terminal, a server, and various APIs.

[0443] Program processing description

[0444] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0445] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[0446] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[0447] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[0448] Finally, the server sends the optimized gift candidate list to the user terminal and suggests it to the user, who then displays the list to the user, allowing the user to select a desired item from the suggested gifts.

[0449] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0450] Specific examples

[0451] A specific example is given below.

[0452] scenario:

[0453] User "Yamada Hanako" wants to choose a birthday present for her 35-year-old friend Tanaka Taro.

[0454] 1. User device: Hanako Yamada accesses the application and enters Taro Tanaka's information (age 35, male, friend).

[0455] 2. User device: Hanako Yamada requests permission to access Taro Tanaka's Instagram account.

[0456] 3. User terminal: After obtaining permission to use, provide account information to the system.

[0457] 4. Server: Collects Tanaka Taro's posting data on "cooking," "sports," and "travel" via the SNS API.

[0458] 5. Server: Analyzes the text and image data and extracts Taro Tanaka's interests (e.g., sports equipment, kitchen gadgets, travel-related goods).

[0459] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[0460] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[0461] 8. Server: Sends the optimized gift candidate list to the user device.

[0462] 9. User device: Display suggested gift items for Hanako (e.g., jogging shoes, the latest blender, and a compact travel bag).

[0463] 10. User device: Hanako Yamada selects jogging shoes and completes the purchase process.

[0464] 11. Server: Notify the user and recipient once the purchase and delivery process is complete.

[0465] In this way, a system is provided that allows users to select the most suitable gift in a short amount of time without stress.

[0466] The processing flow will be explained below.

[0467] Step 1:

[0468] User device: The user accesses the Present Match AI and enters basic information about the person they want to give a gift to (name, age, gender, relationship, etc.).

[0469] Step 2:

[0470] User Device: The user selects the option to link the social networking service (SNS) account of the person to whom the gift is to be given.

[0471] Step 3:

[0472] User device: The user requests and receives approval for access to the recipient's social media account.

[0473] Step 4:

[0474] Server: Uses the SNS API to retrieve data such as the recipient's liked posts, shared articles, followed accounts, and post content.

[0475] Step 5:

[0476] Server: Analyzes the acquired SNS data using natural language processing (NLP) algorithms, tokenizes the text data, and uses topic modeling (e.g., LDA) to extract the recipient's areas of interest.

[0477] Step 6:

[0478] Server: Image and video data is analyzed using image recognition algorithms (e.g., CNN) to identify interest in specific brands and products.

[0479] Step 7:

[0480] Server: Based on the extracted areas of interest and other information, collect relevant gift suggestions from online marketplaces and APIs of specific gift shops.

[0481] Step 8:

[0482] Server: Obtains detailed information about each product (price, rating, category, etc.) and filters it according to the user's budget or special requirements.

[0483] Step 9:

[0484] Server: Sends the optimized gift candidate list to the user device.

[0485] Step 10:

[0486] User terminal: Display a list of suggested gifts to the user and allow the user to select the desired gift item.

[0487] Step 11:

[0488] User device: The user selects the gift item and begins the purchase process.

[0489] Step 12:

[0490] User terminal: Provides an interface for entering payment and shipping information.

[0491] Step 13:

[0492] Server: Once the purchase process is complete, we contact the partner gift shop or marketplace API to check stock availability and proceed with the delivery process.

[0493] Step 14:

[0494] Server: Sends purchase completion notification and shipping information to the user and recipient.

[0495] Step 15:

[0496] User device: Display purchase completion notification and shipping information to the user.

[0497] Example 1

[0498] 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."

[0499] Today's consumers often spend a lot of time and effort selecting gifts, which can be especially challenging when considering the recipient's preferences. Therefore, there is a need for a system that can suggest the best gift based on the recipient's interests. However, existing systems lack the ability to collect and analyze social media data, making it difficult to meet individual needs.

[0500] 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.

[0501] In this invention, the server includes means for inputting information provided by a user, means for acquiring data from the recipient's social networking service, means for analyzing the acquired data and extracting the recipient's interests, means for analyzing the data using natural language processing and image analysis algorithms, means for acquiring relevant gift candidates from online marketplaces and databases of specific gift shops based on the analysis results, means for filtering the gift candidates taking into account the user's budget and special requirements, and means for suggesting the generated gift candidates to the user, thereby enabling the user to select the most suitable gift in a short period of time.

[0502] "User" means an individual or organization that uses the system, inputs information through a terminal, and makes gift suggestions and makes purchases.

[0503] "Terminal" refers to a computer device or mobile device that a user accesses and that allows the input and display of information.

[0504] "Server" refers to the central device that manages the entire system, collects, analyzes, filters, and recommends optimal gifts.

[0505] A "social networking service" is an online platform that enables people to communicate over the internet and is subject to data collection.

[0506] "Data Acquisition Methods" refers to APIs and other technical methods for collecting the required information from social networking services.

[0507] "Natural language processing" refers to technology that analyzes acquired text data and understands the recipient's interests and concerns.

[0508] "Image analysis algorithm" refers to technology that analyzes acquired image data and recognizes characteristics such as specific brands and products.

[0509] "Analysis Results" refers to information about the recipient's interests and concerns obtained by analyzing information collected using data acquisition means using natural language processing and image analysis algorithms.

[0510] "Online marketplace" refers to an online commercial platform where various products can be purchased.

[0511] "Gift suggestion means" refers to a technical method for presenting gift candidates generated based on the analysis results to the user.

[0512] MODE FOR CARRYING OUT THE INVENTION

[0513] This invention is a system that suggests optimal gifts based on information about the recipient of a gift and the recipient's activity data on a social networking service. This system is composed of multiple components, including a user terminal, a server, and various APIs. Detailed embodiments are described below.

[0514] First, the user accesses the gift suggestion system using a device. The application home screen displays a "Gift Suggestion" option, and the user selects this option.

[0515] The user is presented with a form where they can enter basic information about the recipient, such as their name, age, gender, and relationship. Following this, the user selects the option to link their social media account. Here, the user obtains permission to access their social media account (e.g., Instagram, Facebook, etc.) and provides their account information to the system.

[0516] The device sends the basic information entered by the user and social media account information to a server, which then uses social media APIs (such as Instagram API and Facebook Graph API) to collect data such as the other person's "liked" posts, shared articles, accounts they follow, and post content.

[0517] The server analyzes the collected data using natural language processing (NLP) and image analysis algorithms. Specifically, it tokenizes text data and extracts multiple themes using LDA (Latent Dirichlet Allocation). Image data is analyzed using CNN (Convolutional Neural Networks) to extract interest in specific brands and products. This allows for highly accurate detection of a person's interests.

[0518] Based on the analysis results, the server searches for relevant gift suggestions from online marketplaces (e.g., Amazon API or Rakuten API) or specific gift shop APIs, filtering them based on the user's budget and special requirements (e.g., eco-friendly products or specific brands).

[0519] The server then generates a list of optimal gift options and sends it to the user's device, where the user can select the items they want from the list, including details such as images, prices, and ratings for each item.

[0520] When a user selects a gift item, the user's device displays a checkout screen where the user can enter payment and delivery information. The server receives the information, checks inventory, and completes the purchase via the marketplace API. Finally, the server sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0521] Specific examples

[0522] A specific example is given below.

[0523] scenario:

[0524] User A wants to give a birthday gift to friend B who is 35 years old:

[0525] 1. User A accesses the application and enters B's information (35 years old, male, friend).

[0526] 2. User A requests permission to access User B's Instagram account.

[0527] 3. After User A has been granted access, he / she provides his / her account information to the system.

[0528] 4. The server uses the SNS API to collect B's posts about "cooking," "sports," and "travel."

[0529] 5. The server analyzes the collected data and extracts B's interests (e.g., sports equipment, kitchen gadgets, travel-related products).

[0530] 6. The server uses the Amazon API or Rakuten API to search for related products and generate gift suggestions.

[0531] 7. The server filters the gift suggestions taking into account User A's budget and special requirements.

[0532] 8. The server sends the list of best gift candidates to User A's device.

[0533] 9. User A selects jogging shoes from the suggested gift items (e.g., jogging shoes, a new blender, and a compact travel bag) and completes the purchase.

[0534] 10. The server notifies User A and Recipient B once the purchase and delivery process is complete.

[0535] This system allows users to choose the perfect gift in a short amount of time.

[0536] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0537] Step 1:

[0538] The user accesses the gift suggestion system through a terminal and inputs basic information about the recipient (name, age, gender, relationship). The input data includes the user's basic information. The terminal then sends this information to the server.

[0539] Step 2:

[0540] The server receives the basic information sent by the user and displays a screen on the user's device that includes the option to allow SNS account linking. The SNS account linking screen is generated as the output.

[0541] Step 3:

[0542] The user grants permission to access the other person's social media account (e.g., Instagram, Facebook, etc.). The user enters their social media account information and completes authorization authentication. The social media account information is included as input data.

[0543] Step 4:

[0544] The device sends the basic information and SNS account information entered by the user to the server. The input data includes the basic information and SNS account information. The output is the completion of information transfer to the server.

[0545] Step 5:

[0546] The server uses SNS APIs (e.g., Instagram API, Facebook Graph API) to collect data such as posts that the other person has "liked," articles that they have shared, accounts they are following, and the content of their posts. SNS account information is used as input, and the other person's SNS data is collected as output. Specific operations include making a request to the SNS API, retrieving the data, and saving the data.

[0547] Step 6:

[0548] The data collected by the server is analyzed using natural language processing (NLP) and image analysis algorithms. Social media data is used as input. Specific operations include tokenizing text data, topic modeling using LDA (Latent Dirichlet Allocation), and image recognition using CNN (Convolutional Neural Network). The output is data indicating the other person's interests and concerns.

[0549] Step 7:

[0550] The server uses the analysis results to search for relevant gift suggestions from online marketplaces (e.g., Amazon API or Rakuten API) or specific gift shop APIs. The analysis results are used as input and a list of gift suggestions is generated as output. Specific operations include making a request to the API, gathering product information, and generating a gift suggestion list.

[0551] Step 8:

[0552] The server filters gift suggestions, taking into account the user's budget and special requirements (e.g., eco-friendly products or specific brands). The input includes user preferences and a list of suggestions. The output is an optimized list of gift suggestions. The specific operation involves running a filtering algorithm.

[0553] Step 9:

[0554] The server sends the best gift candidate list to the user device, which contains the filtered gift list as input, and displays the gift candidate list on the user device as output.

[0555] Step 10:

[0556] The user selects the desired item from the list and clicks the "Proceed to Checkout" button, including the gift wishlist as input.

[0557] Step 11:

[0558] The terminal displays a checkout screen where the user enters payment and shipping information. The input includes the user's payment and shipping information.

[0559] Step 12:

[0560] The server receives the entered payment information, checks inventory and processes the purchase via the marketplace API. The output is a purchase completion notification and shipping information. Specific operations include making a request to the API, checking inventory, processing the payment, and sending a notification email.

[0561] Step 13:

[0562] The server sends a purchase completion notification and shipping information to the user and recipient, respectively. The input contains the result of the purchase process. The output is the completion of the notification and shipping information.

[0563] (Application example 1)

[0564] 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."

[0565] With conventional gift selection systems, it was difficult to suggest gifts that accurately reflected the recipient's interests, and there were insufficient means to provide detailed information to users in an easy-to-understand manner. This made it difficult for users to quickly select the perfect gift for the recipient, and the selection and purchase process was stressful.

[0566] 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.

[0567] In this invention, the server includes a means for inputting information provided by the user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for displaying detailed information (price, rating, category, etc.) of the generated gift candidates, and a means for purchasing and shipping the gift item selected by the user, thereby enabling the user to quickly select the best gift for the recipient and complete the purchase procedure without stress.

[0568] "User" refers to an individual who uses the Gift Suggestion System.

[0569] "Recipient" means the individual to whom you wish to send a Gift.

[0570] "Social Networking Service" refers to an online platform used by the Recipient that allows the Recipient to share their posts and activity data.

[0571] "Means for Obtaining Data" refers to the means for collecting the required data from the recipient's social networking service.

[0572] "Means for analyzing data" refers to means for extracting the recipient's interests and concerns using the acquired data.

[0573] The "means for generating gift candidates" refers to a means for generating gift candidates suitable for a recipient based on the analysis results.

[0574] "Detailed information" refers to specific information such as the price, rating, and category of the gift candidate.

[0575] "Purchase and Delivery Method" means the method by which a User purchases and completes the delivery process for the selected Gift.

[0576] This invention relates to a system that suggests optimal gifts based on information about the recipient and their activity data on social networking services (SNS). The system is composed of multiple components, including a user terminal, a server, and various APIs.

[0577] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0578] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, followed accounts, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests. Specifically, the server tokenizes the obtained text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. Furthermore, the server uses image recognition algorithms (e.g., CNN) to analyze posted images and extract interest in specific brands and products.

[0579] Next, based on the analysis results, the server retrieves relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, rating, category, etc.) and extracts gift suggestions that best fit the recipient's profile. This includes filtering based on the user's budget and special requirements. Finally, the server sends the optimized gift suggestion list to the user's device and makes suggestions to the user.

[0580] The user's device displays this list to the user, allowing them to select the desired gift item from the suggested gifts. After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0581] Specific examples

[0582] A specific example is given below.

[0583] scenario

[0584] A user wants to choose a birthday gift for a friend who is turning 35. The user accesses the application and enters the recipient's information (age, gender, friendship status). They also request permission to access the recipient's social media account and provide the account information to the system. The server collects the recipient's posts related to "cooking," "sports," and "travel" via the social media API. It analyzes the text and image data to extract the recipient's interests (e.g., sports equipment, kitchen gadgets, travel-related goods). It uses the marketplace API to obtain detailed information about related products and generate optimal gift suggestions. It filters the gift suggestions taking into account the user's budget and special requirements and sends the optimized gift suggestion list to the user's device. The user reviews the suggested gift items, selects a pair of jogging shoes, and completes the purchase. The server notifies the user and the recipient once the purchase and delivery process is complete.

[0585] Prompt Sentence Examples

[0586] Example input

[0587] "I'd like some suggestions for the perfect gift for my friend's birthday. Here are their social media accounts."

[0588] Example output

[0589] "Suggested gifts include: jogging shoes, a new blender, and a compact travel bag."

[0590] The specific hardware and software used includes social media APIs (e.g., Instagram API, Twitter API), natural language processing libraries (e.g., NLTK, spaCy), and image analysis models (e.g., ResNet50). Additionally, programming languages ​​such as Python and cloud services (e.g., AWS, Google Cloud) can be used for the server.

[0591] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0592] Step 1:

[0593] A user accesses the gift suggestion system using a device. The user enters basic information about the person they want to give a gift to (such as name, age, gender, and relationship). They also select the option to link the recipient's social media account. This information is sent from the device to the server. The input data (basic information, social media link) is stored on the server and used for analysis.

[0594] Step 2:

[0595] The server accesses the recipient's SNS account information and uses the API to obtain SNS data (liked posts, shared articles, followed accounts, post content, etc.). It obtains the recipient's activity data using the SNS API (e.g., Instagram API, Twitter API). The obtained data is divided into text data and image data. The input is data from the SNS API, and the output is text data and image data for analysis.

[0596] Step 3:

[0597] The server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests. Specifically, it tokenizes the text data and identifies areas of interest using topic modeling (e.g., LDA). It also analyzes posted images using image recognition algorithms (e.g., ResNet50) to extract interest in specific brands and products. The input is the text data and image data for analysis, and the output is the extracted recipient's interests.

[0598] Step 4:

[0599] Based on the analysis results, the server retrieves related gift suggestions from the APIs of online marketplaces or specific gift shops. It uses the APIs of online marketplaces (e.g., Amazon API, Rakuten Market API) to collect detailed information (price, rating, category, etc.) about related products. The input is the analysis results and data from the marketplace API, and the output is a list of gift suggestions.

[0600] Step 5:

[0601] The server filters gift suggestions based on the user's budget and special requirements, listing items that fit within a budget range or fall into a specific category. The input is a list of gift suggestions and user preferences, and the output is a filtered list of optimal gift suggestions.

[0602] Step 6:

[0603] The server sends the optimized gift candidate list to the user terminal. The user terminal displays this list to the user. The user can select desired items from the suggested gifts. The input is the optimized gift candidate list, and the output is the gift candidates presented to the user.

[0604] Step 7:

[0605] For the gift items selected by the user, the user device provides an interface to support the purchase process (input of payment information and delivery information). The user enters the required information and completes the purchase process. The input is the gift items selected by the user and payment and delivery information, and the output is the completion of the purchase process.

[0606] Step 8:

[0607] The server queries partner gift shops and marketplace APIs to check stock availability and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient. The input is purchase completion information, and the output is the stock availability result, the start of delivery procedures, and a completion notification.

[0608] 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.

[0609] This invention is a system that suggests the perfect gift based on information about the person a user wants to give a gift to and their activity data on social networking services (SNS), and further combines it with an emotion engine to recognize the user's emotions and improve the level of personalization of the suggested gifts. This system is composed of multiple components, including a user terminal, a server, various APIs, and an emotion engine.

[0610] Program processing description

[0611] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0612] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[0613] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[0614] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[0615] Furthermore, the present invention incorporates an emotion engine to recognize users' emotions in real time and optimize gift suggestions based on their emotions. The emotion engine uses a camera and microphone to analyze users' facial expressions, voice tone, and input content.

[0616] The emotion engine includes facial recognition software that reads emotions from a user's facial expressions and voice analysis software that analyzes emotions from a user's tone of voice, allowing the engine to analyze the user's emotional state (e.g., joy, surprise, interest, etc.) while browsing gift suggestions and prioritize gift suggestions based on the user's emotions.

[0617] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0618] Specific examples

[0619] A specific example is given below.

[0620] scenario:

[0621] A user named "Yamada Hanako" wants to choose a birthday present for her friend Tanaka Taro, who is 35. Furthermore, the gift is optimized taking into account Yamada Hanako's feelings.

[0622] 1. User device: Hanako Yamada accesses the application and enters Taro Tanaka's information (age 35, male, friend).

[0623] 2. User device: Hanako Yamada requests permission to access Taro Tanaka's Instagram account.

[0624] 3. User terminal: After obtaining permission to use, provide account information to the system.

[0625] 4. Server: Collects Tanaka Taro's posting data on "cooking," "sports," and "travel" via the SNS API.

[0626] 5. Server: Analyzes the text and image data and extracts Taro Tanaka's interests (e.g., sports equipment, kitchen gadgets, travel-related goods).

[0627] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[0628] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[0629] 8. Server: Use the emotion engine to analyze Hanako Yamada's emotional state while she browses gift suggestions and optimize gift suggestions based on her emotions.

[0630] 9. Server: Sends the optimized gift candidate list to the user device.

[0631] 10. User device: Display suggested gift items for Hanako (e.g., jogging shoes, the latest blender, and a compact travel bag).

[0632] 11. User device: Hanako Yamada selects jogging shoes and completes the purchase process.

[0633] 12. Server: Notify the user and recipient once the purchase and delivery process is complete.

[0634] In this way, a system is provided that allows users to select the most suitable gift in a short time while taking their emotions into consideration.

[0635] The processing flow will be explained below.

[0636] Step 1:

[0637] User device: The user accesses the Present Match AI and enters basic information about the person they want to give a gift to (name, age, gender, relationship, etc.).

[0638] Step 2:

[0639] User Device: The user selects the option to link the social networking service (SNS) account of the person to whom the gift is to be given.

[0640] Step 3:

[0641] User device: The user requests and receives approval for access to the recipient's social media account.

[0642] Step 4:

[0643] Server: Uses the SNS API to retrieve data such as the recipient's liked posts, shared articles, followed accounts, and post content.

[0644] Step 5:

[0645] Server: Analyzes the acquired SNS data using natural language processing (NLP) algorithms, tokenizes the text data, and uses topic modeling (e.g., LDA) to extract the recipient's areas of interest.

[0646] Step 6:

[0647] Server: Image and video data is analyzed using image recognition algorithms (e.g., CNN) to identify interest in specific brands and products.

[0648] Step 7:

[0649] Server: Based on the extracted areas of interest and other information, collect relevant gift suggestions from online marketplaces and APIs of specific gift shops.

[0650] Step 8:

[0651] Server: Obtains detailed information about each product (price, rating, category, etc.) and filters it according to the user's budget or special requirements.

[0652] Step 9:

[0653] Server: Sends the optimized gift candidate list to the user device.

[0654] Step 10:

[0655] User terminal: Display a list of suggested gifts to the user and allow the user to select the desired gift item.

[0656] Step 11:

[0657] User device: The user selects the gift item and begins the purchase process.

[0658] Step 12:

[0659] User terminal: Provides an interface for entering payment and shipping information.

[0660] Step 13:

[0661] Server: Once the purchase process is complete, we contact the partner gift shop or marketplace API to check stock availability and proceed with the delivery process.

[0662] Step 14:

[0663] Server: Sends purchase completion notification and shipping information to the user and recipient.

[0664] Step 15:

[0665] User device: Display purchase completion notification and shipping information to the user.

[0666] Step 16:

[0667] Emotion Engine: Uses the camera and microphone to collect the user's facial expressions and tone of voice as they browse gift options.

[0668] Step 17:

[0669] Emotion engine: Analyzes collected data and recognizes the user's emotional state (e.g., joy, surprise, interest).

[0670] Step 18:

[0671] Emotion Engine: Based on the recognized emotional state, it reprioritizes the gift suggestion list and lists gifts that best fit the user's emotions.

[0672] Step 19:

[0673] User device: Display the re-prioritized gift idea list to the user.

[0674] Step 20:

[0675] User device: The user selects a gift from the reprioritized list and initiates the final purchase process.

[0676] Example 2

[0677] 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."

[0678] Conventional gift suggestion systems can generate gift candidates based on information provided by users and social media data, but they do not take the user's emotional state into account, resulting in a low level of personalized gift suggestions. Furthermore, the gift selection process cannot reflect the user's emotional changes in real time, making it difficult to suggest optimal gifts. Furthermore, the suggested gifts may not meet the user's expectations, resulting in a poor user experience.

[0679] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0680] In this invention, the server includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, a means for recognizing the user's emotions and optimizing the gift candidates, and a means for suggesting the generated gift candidates to the user, thereby enabling highly personalized gift suggestions that take the user's emotional state into consideration.

[0681] "Information provided by the user" refers to basic information about the recipient (such as name, age, gender, relationship, etc.) that the user enters into the system.

[0682] "Means of obtaining data from the recipient's social networking service" refers to a mechanism for accessing the recipient's social media account via an API or other means and collecting data such as posts, "likes," shared articles, and followed accounts.

[0683] "Means of analyzing the acquired data and extracting the recipient's interests and concerns" refers to methods of using natural language processing (NLP) and image analysis algorithms to identify the recipient's interests and areas of concern from the collected social media data.

[0684] "Means for generating gift suggestions based on analysis results" refers to a system that uses APIs of online marketplaces and gift shops to create a list of related products based on extracted interests.

[0685] "Means to recognize user emotions and optimize gift candidates" refers to a system that uses cameras and microphones to analyze the user's facial expressions and tone of voice in real time and adjusts the ranking of gift candidates based on the analysis results.

[0686] "Means for suggesting generated gift candidates to a user" refers to a system that transmits the optimized gift candidate list to a user terminal and displays it through a user interface.

[0687] "Means for purchasing and shipping gift items selected by the user" refers to a system that provides an interface for users to enter payment and shipping information for the gift selected by the user, and processes the items to be properly delivered after the purchase is completed.

[0688] "Methods of using recipient account information linked by the user" refers to methods of linking social media account information and collecting necessary data with the user's permission.

[0689] This invention relates to a system that suggests the perfect gift based on information about the person a user wants to give a gift to and their activity data on social networking services (SNS). Furthermore, this system is combined with an emotion engine, which can recognize the user's emotions and improve the level of personalization of the gifts it suggests. This system is composed of multiple components, including a user terminal, a server, various APIs, and the emotion engine.

[0690] The user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0691] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[0692] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[0693] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[0694] Furthermore, the present invention incorporates an emotion engine to recognize a user's emotions in real time and optimize gift suggestions based on those emotions. The emotion engine uses a camera and microphone to analyze a user's facial expressions, voice tone, and input content. The emotion engine includes facial expression recognition software that reads emotions from the user's facial expressions and voice analysis software that analyzes emotions from the user's voice tone. This allows the system to analyze the user's emotional state (e.g., joy, surprise, interest, etc.) while browsing gift suggestions and prioritize gift suggestions based on the user's emotions.

[0695] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0696] Specific examples

[0697] A specific example is given below.

[0698] scenario:

[0699] A user wants to choose a birthday gift for a friend, and further optimizes the gift by taking emotions into account.

[0700] 1. User device: The user accesses the application and enters their friend's information (age, gender, relationship, etc.).

[0701] 2. User device: The user requests permission to access a friend's social media account.

[0702] 3. User terminal: After obtaining permission to use, provide account information to the system.

[0703] 4. Server: Collects friends' posting data about "cooking," "sports," and "travel" via SNS API.

[0704] 5. Server: Analyzes text and image data to extract friends' interests (e.g., sports equipment, kitchen gadgets, travel-related items).

[0705] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[0706] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[0707] 8. Server: Uses an emotion engine to analyze the emotional state of the user while browsing gift suggestions and optimize gift suggestions based on that emotion.

[0708] 9. Server: Sends the optimized gift candidate list to the user device.

[0709] 10. User device: Display suggested gift items to the user (e.g., jogging shoes, the latest blender, a compact travel bag).

[0710] 11. User device: The user selects the jogging shoes and completes the purchase.

[0711] 12. Server: Notify the user and recipient once the purchase and delivery process is complete.

[0712] Example prompts for generative AI models

[0713] Below are some examples of specific prompt sentences.

[0714] Prompt Sentence Examples

[0715] A user accesses a system that suggests the best gift for a friend's birthday based on social media data and the user's emotions. Explain all the steps the system takes, including the information the user provides to the system, data analysis, and emotion recognition.

[0716] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0717] Step 1: Enter your user information

[0718] Users simply enter basic information about the recipient (such as name, age, gender, and relationship) into the device.

[0719] Input is basic information provided by the user.

[0720] The output is basic information stored on the device.

[0721] Specific behavior: The user enters basic information into the form and clicks the "Next" button.

[0722] Step 2: Obtain and send recipient's social media account information

[0723] Users simply select the option to request permission to link to the other person's social media account.

[0724] The input is the user's social media account information and link permission of the other person.

[0725] The output is the social media account information and permissions sent to the server.

[0726] Specific operation: The user allows access to the social networking account and sends the link information.

[0727] Step 3: Collect social media data

[0728] The server uses an API to access the recipient's social media account and collect the necessary data.

[0729] The input is the SNS account information sent to the server.

[0730] The output is collected social media data (likes, shared posts, followed accounts, post content, etc.).

[0731] Specific operation: The server calls the SNS API and obtains the recipient's activity data.

[0732] Step 4: Analyze the data

[0733] The server analyzes the collected social media data using natural language processing (NLP) and image analysis algorithms.

[0734] The input is collected social media data.

[0735] The output is an analysis that indicates the recipient's interests.

[0736] What it does: The server tokenizes the text data, identifies regions of interest using topic modeling (e.g., LDA), and analyzes the images using image recognition algorithms (e.g., CNN).

[0737] Step 5: Generate gift suggestions

[0738] Based on the analysis results, the server retrieves relevant gift suggestions from APIs of online marketplaces and gift shops.

[0739] Inputs are the analysis results and the user's budget and special requirements.

[0740] The output is a generated list of gift suggestions.

[0741] Specific operation: The server calls the product's API to obtain detailed information such as price, rating, category, etc.

[0742] Step 6: Emotion Engine in Action

[0743] The device uses a camera and microphone to collect the user's facial expressions and voice tone.

[0744] The input is the user's facial expression data and voice data.

[0745] The output is the analyzed emotion data.

[0746] How it works: The device uses facial recognition and voice analysis software to analyze emotions.

[0747] Step 7: Optimize and display gift ideas

[0748] The server prioritizes gift suggestions based on the user's emotional data.

[0749] The inputs are emotion data and a gift candidate list.

[0750] The output is an optimized gift suggestion list.

[0751] Specific operation: The server adjusts the priority of gift candidates based on the emotional data and sends the list to the user's device.

[0752] Step 8: Gift Selection and Checkout

[0753] Users simply select the most suitable item from the displayed gift options.

[0754] The input is an optimized gift suggestion list.

[0755] The output is the selected gift item.

[0756] What happens: The user adds the selected gift item to their cart and begins the checkout process.

[0757] Step 9: Purchase completion and notification

[0758] The server queries partner gift shops and marketplace APIs to check inventory and process shipping.

[0759] The input is the selected gift item and shipping information.

[0760] The output is a confirmation of purchase completion and shipping information.

[0761] What happens: The server sends a notification to the user and recipient once the purchase is complete.

[0762] (Application example 2)

[0763] 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."

[0764] Conventional gift suggestion systems suggest gifts by taking into account the recipient's information and social media data, but because they are unable to consider the user's emotions, it is difficult to suggest the optimal gift that is in line with the user's feelings. Furthermore, there are cases where the suggested gift does not perfectly match the recipient's interests. Therefore, there was a need for a system that could help users select a gift that satisfies them.

[0765] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, a means for suggesting the generated gift candidates to the user, and a means for recognizing the user's emotions in real time and optimizing the suggested gift candidates. This makes it possible to suggest optimal gifts based on the recipient's interests while taking the user's emotions into consideration.

[0766] The "means for inputting information provided by the user" refers to an input device and software that allows the user to input basic information about the recipient, budget, etc.

[0767] "Means for obtaining data from the recipient's social networking service" refers to the means of communication and software for accessing the recipient's social networking account information and obtaining data such as posts, likes, and shared articles via API.

[0768] "Means for analyzing acquired data and extracting the recipient's interests" refers to hardware and software that uses natural language processing and image analysis algorithms to analyze acquired SNS data and identify the recipient's areas of interest.

[0769] The "means for generating gift candidates based on the analysis results" refers to software that obtains related product information from the APIs of online marketplaces and gift shops based on the analyzed interests and generates gift candidates.

[0770] The "means for suggesting generated gift candidates to the user" refers to a display device and software for presenting the generated multiple gift candidates to the user and assisting in the selection.

[0771] "Means for recognizing a user's emotions in real time and optimizing suggested gift candidates" refers to hardware and software that uses a camera and microphone to analyze emotions from a user's facial expressions and tone of voice, and optimizes the prioritization of gift candidates based on the user's emotions.

[0772] This invention is realized by constructing a gift suggestion system using a user terminal and a server. This system includes means for inputting information provided by a user, means for acquiring data from the recipient's social networking service, means for analyzing the acquired data and extracting the recipient's interests, means for generating gift candidates based on the analysis results, means for suggesting the generated gift candidates to the user, and means for recognizing the user's emotions in real time and optimizing the suggested gift candidates.

[0773] First, the user device provides an input device and software that allows the user to input basic information about the recipient, their budget, etc. This input information is sent to the server. Meanwhile, the recipient's social media account information is also linked to the user, and the server obtains the recipient's posts, likes, shared articles, etc. through the social media API. The obtained data is then analyzed on the server using natural language processing tools (e.g., TextBlob) and image analysis algorithms (e.g., CNN) to extract the recipient's interests and concerns.

[0774] Based on the analysis results, the server retrieves relevant gift suggestions from online marketplace APIs and gift shop APIs, and obtains detailed information (price, rating, category, etc.). This generates gift suggestions that take into account the user's budget and special requirements. Furthermore, it uses an emotion engine (e.g., FER) to recognize the user's real-time emotions through the camera and microphone on the user's device. Based on this, the priority of gift suggestions is optimized and suggested to the user.

[0775] Specifically, the server begins with a step in which a user accesses the application and enters the recipient's basic information and social media account. For example, suppose a user named "Yamada Hanako" wants to choose a gift for a "friend (35 years old, male)." The user links her "Instagram account," and the server obtains the social media data. Analysis reveals that she is interested in "cooking," "sports," and "travel," and generates gift suggestions based on that. After that, the camera determines that Yamada Hanako's emotion is "joy," and sports and travel-related goods are prioritized as suggestions.

[0776] Example prompts to input to the generative AI model:

[0777] "Please enter the name and social media account of the person you would like to give the gift to:

[0778] Name: Yamada Hanako

[0779] Social Media Account: example_user

[0780] Next, enter your budget (e.g., 5000 yen):

[0781] Budget: 5,000 yen

[0782] Turn on the camera and start emotion recognition.

[0783] ...

[0784] We're optimizing gift suggestions...

[0785] Perfect gift idea list:

[0786] 1. Jogging shoes

[0787] 2. Modern Blender

[0788] 3. Compact travel bag

[0789] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0790] Step 1:

[0791] The user enters the basic information and social media account information of the person they want to give the gift to.

[0792] Input: Name, age, gender, relationship, SNS account information

[0793] Output: The acquired information is sent from the device to the server.

[0794] Specific operation: When a user enters the required information into the input form on the terminal and clicks the send button, the terminal sends this information to the server.

[0795] Step 2:

[0796] The server accesses the recipient's SNS account and obtains the recipient's posted data, etc., via the SNS API.

[0797] Input: Recipient's SNS account information

[0798] Output: Post data of recipients, such as likes and shared posts, obtained from the SNS API

[0799] What it does: The server sends an API request to the linked social media account and receives data from the social media platform in response.

[0800] Step 3:

[0801] The server analyzes the acquired SNS data using natural language processing and image analysis algorithms to extract the recipient's interests and concerns.

[0802] Input: SNS data (text and images)

[0803] Output: A list of keywords related to the recipient's interests

[0804] How it works: The server uses TextBlob to analyze text and topic modeling to identify areas of interest, and uses CNN to analyze image data and extract interest in specific brands and products.

[0805] Step 4:

[0806] The server retrieves gift suggestions from the online marketplace API or gift shop API based on the analysis results.

[0807] Input: List of keywords of interest

[0808] Output: A list of related gift ideas and detailed information about each item

[0809] Specific operation: The server sends a request including keywords to the marketplace API and receives related product information in response.

[0810] Step 5:

[0811] The server filters gift suggestions, taking into account the user's budget and special requirements.

[0812] Input: Gift idea list, user budget information, special requirements

[0813] Output: A filtered list of gift ideas

[0814] What happens: The server checks the details of each product and selects the appropriate product based on the user's budget and requirements.

[0815] Step 6:

[0816] The terminal uses the user's camera and microphone to recognize the user's emotions in real time.

[0817] Input: User's facial and voice data

[0818] Output: User's emotional state (e.g., happy, surprised, etc.)

[0819] Specific operation: The device collects data in real time from the camera and microphone and analyzes the data using FER and voice analysis software.

[0820] Step 7:

[0821] The server optimizes the prioritization of gift candidates based on the user's emotional state.

[0822] Input: A filtered list of gift ideas, the user's emotional state

[0823] Output: Optimized list of gift ideas

[0824] Specific operation: The server takes into account the user's emotions and prioritizes placing the most suitable gifts at the top of the list.

[0825] Step 8:

[0826] The terminal displays the optimized gift candidate list to the user, and the user selects a gift.

[0827] Input: A list of optimized gift ideas

[0828] Output: Gift items selected by the user

[0829] Specific operation: The device displays a list of gift options on the screen, and the user selects the desired item.

[0830] Step 9:

[0831] The server processes the purchase and delivery of the selected gift item.

[0832] Input: Gift items selected by user, payment information, shipping information

[0833] Output: Purchase confirmation message, delivery confirmation message

[0834] Specific operation: The server accesses the marketplace API to complete the purchase, confirms the shipping information, and notifies the user and recipient.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] [Third embodiment]

[0839] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0840] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0841] 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).

[0842] 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.

[0843] 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.

[0844] 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).

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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."

[0851] This invention relates to a system that suggests optimal gifts based on information about the recipient and their activity data on social networking services (SNS). This system is composed of multiple components, including a user terminal, a server, and various APIs.

[0852] Program processing description

[0853] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0854] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[0855] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[0856] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[0857] Finally, the server sends the optimized gift candidate list to the user terminal and suggests it to the user, who then displays the list to the user, allowing the user to select a desired item from the suggested gifts.

[0858] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0859] Specific examples

[0860] A specific example is given below.

[0861] scenario:

[0862] User "Yamada Hanako" wants to choose a birthday present for her 35-year-old friend Tanaka Taro.

[0863] 1. User device: Hanako Yamada accesses the application and enters Taro Tanaka's information (age 35, male, friend).

[0864] 2. User device: Hanako Yamada requests permission to access Taro Tanaka's Instagram account.

[0865] 3. User terminal: After obtaining permission to use, provide account information to the system.

[0866] 4. Server: Collects Tanaka Taro's posting data on "cooking," "sports," and "travel" via the SNS API.

[0867] 5. Server: Analyzes the text and image data and extracts Taro Tanaka's interests (e.g., sports equipment, kitchen gadgets, travel-related goods).

[0868] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[0869] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[0870] 8. Server: Sends the optimized gift candidate list to the user device.

[0871] 9. User device: Display suggested gift items for Hanako (e.g., jogging shoes, the latest blender, and a compact travel bag).

[0872] 10. User device: Hanako Yamada selects jogging shoes and completes the purchase process.

[0873] 11. Server: Notify the user and recipient once the purchase and delivery process is complete.

[0874] In this way, a system is provided that allows users to select the most suitable gift in a short amount of time without stress.

[0875] The processing flow will be explained below.

[0876] Step 1:

[0877] User device: The user accesses the Present Match AI and enters basic information about the person they want to give a gift to (name, age, gender, relationship, etc.).

[0878] Step 2:

[0879] User Device: The user selects the option to link the social networking service (SNS) account of the person to whom the gift is to be given.

[0880] Step 3:

[0881] User device: The user requests and receives approval for access to the recipient's social media account.

[0882] Step 4:

[0883] Server: Uses the SNS API to retrieve data such as the recipient's liked posts, shared articles, followed accounts, and post content.

[0884] Step 5:

[0885] Server: Analyzes the acquired SNS data using natural language processing (NLP) algorithms, tokenizes the text data, and uses topic modeling (e.g., LDA) to extract the recipient's areas of interest.

[0886] Step 6:

[0887] Server: Image and video data is analyzed using image recognition algorithms (e.g., CNN) to identify interest in specific brands and products.

[0888] Step 7:

[0889] Server: Based on the extracted areas of interest and other information, collect relevant gift suggestions from online marketplaces and APIs of specific gift shops.

[0890] Step 8:

[0891] Server: Obtains detailed information about each product (price, rating, category, etc.) and filters it according to the user's budget or special requirements.

[0892] Step 9:

[0893] Server: Sends the optimized gift candidate list to the user device.

[0894] Step 10:

[0895] User terminal: Display a list of suggested gifts to the user and allow the user to select the desired gift item.

[0896] Step 11:

[0897] User device: The user selects the gift item and begins the purchase process.

[0898] Step 12:

[0899] User terminal: Provides an interface for entering payment and shipping information.

[0900] Step 13:

[0901] Server: Once the purchase process is complete, we contact the partner gift shop or marketplace API to check stock availability and proceed with the delivery process.

[0902] Step 14:

[0903] Server: Sends purchase completion notification and shipping information to the user and recipient.

[0904] Step 15:

[0905] User device: Display purchase completion notification and shipping information to the user.

[0906] Example 1

[0907] 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."

[0908] Today's consumers often spend a lot of time and effort selecting gifts, which can be especially challenging when considering the recipient's preferences. Therefore, there is a need for a system that can suggest the best gift based on the recipient's interests. However, existing systems lack the ability to collect and analyze social media data, making it difficult to meet individual needs.

[0909] 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.

[0910] In this invention, the server includes means for inputting information provided by a user, means for acquiring data from the recipient's social networking service, means for analyzing the acquired data and extracting the recipient's interests, means for analyzing the data using natural language processing and image analysis algorithms, means for acquiring relevant gift candidates from online marketplaces and databases of specific gift shops based on the analysis results, means for filtering the gift candidates taking into account the user's budget and special requirements, and means for suggesting the generated gift candidates to the user, thereby enabling the user to select the most suitable gift in a short period of time.

[0911] "User" means an individual or organization that uses the system, inputs information through a terminal, and makes gift suggestions and makes purchases.

[0912] "Terminal" refers to a computer device or mobile device that a user accesses and that allows the input and display of information.

[0913] "Server" refers to the central device that manages the entire system, collects, analyzes, filters, and recommends optimal gifts.

[0914] A "social networking service" is an online platform that enables people to communicate over the internet and is subject to data collection.

[0915] "Data Acquisition Methods" refers to APIs and other technical methods for collecting the required information from social networking services.

[0916] "Natural language processing" refers to technology that analyzes acquired text data and understands the recipient's interests and concerns.

[0917] "Image analysis algorithm" refers to technology that analyzes acquired image data and recognizes characteristics such as specific brands and products.

[0918] "Analysis Results" refers to information about the recipient's interests and concerns obtained by analyzing information collected using data acquisition means using natural language processing and image analysis algorithms.

[0919] "Online marketplace" refers to an online commercial platform where various products can be purchased.

[0920] "Gift suggestion means" refers to a technical method for presenting gift candidates generated based on the analysis results to the user.

[0921] MODE FOR CARRYING OUT THE INVENTION

[0922] This invention is a system that suggests optimal gifts based on information about the recipient of a gift and the recipient's activity data on a social networking service. This system is composed of multiple components, including a user terminal, a server, and various APIs. Detailed embodiments are described below.

[0923] First, the user accesses the gift suggestion system using a device. The application home screen displays a "Gift Suggestion" option, and the user selects this option.

[0924] The user is presented with a form where they can enter basic information about the recipient, such as their name, age, gender, and relationship. Following this, the user selects the option to link their social media account. Here, the user obtains permission to access their social media account (e.g., Instagram, Facebook, etc.) and provides their account information to the system.

[0925] The device sends the basic information entered by the user and social media account information to a server, which then uses social media APIs (such as Instagram API and Facebook Graph API) to collect data such as the other person's "liked" posts, shared articles, accounts they follow, and post content.

[0926] The server analyzes the collected data using natural language processing (NLP) and image analysis algorithms. Specifically, it tokenizes text data and extracts multiple themes using LDA (Latent Dirichlet Allocation). Image data is analyzed using CNN (Convolutional Neural Networks) to extract interest in specific brands and products. This allows for highly accurate detection of a person's interests.

[0927] Based on the analysis results, the server searches for relevant gift suggestions from online marketplaces (e.g., Amazon API or Rakuten API) or specific gift shop APIs, filtering them based on the user's budget and special requirements (e.g., eco-friendly products or specific brands).

[0928] The server then generates a list of optimal gift options and sends it to the user's device, where the user can select the items they want from the list, including details such as images, prices, and ratings for each item.

[0929] When a user selects a gift item, the user's device displays a checkout screen where the user can enter payment and delivery information. The server receives the information, checks inventory, and completes the purchase via the marketplace API. Finally, the server sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0930] Specific examples

[0931] A specific example is given below.

[0932] scenario:

[0933] User A wants to give a birthday gift to friend B who is 35 years old:

[0934] 1. User A accesses the application and enters B's information (35 years old, male, friend).

[0935] 2. User A requests permission to access User B's Instagram account.

[0936] 3. After User A has been granted access, he / she provides his / her account information to the system.

[0937] 4. The server uses the SNS API to collect B's posts about "cooking," "sports," and "travel."

[0938] 5. The server analyzes the collected data and extracts B's interests (e.g., sports equipment, kitchen gadgets, travel-related products).

[0939] 6. The server uses the Amazon API or Rakuten API to search for related products and generate gift suggestions.

[0940] 7. The server filters the gift suggestions taking into account User A's budget and special requirements.

[0941] 8. The server sends the list of best gift candidates to User A's device.

[0942] 9. User A selects jogging shoes from the suggested gift items (e.g., jogging shoes, a new blender, and a compact travel bag) and completes the purchase.

[0943] 10. The server notifies User A and Recipient B once the purchase and delivery process is complete.

[0944] This system allows users to choose the perfect gift in a short amount of time.

[0945] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0946] Step 1:

[0947] The user accesses the gift suggestion system through a terminal and inputs basic information about the recipient (name, age, gender, relationship). The input data includes the user's basic information. The terminal then sends this information to the server.

[0948] Step 2:

[0949] The server receives the basic information sent by the user and displays a screen on the user's device that includes the option to allow SNS account linking. The SNS account linking screen is generated as the output.

[0950] Step 3:

[0951] The user grants permission to access the other person's social media account (e.g., Instagram, Facebook, etc.). The user enters their social media account information and completes authorization authentication. The social media account information is included as input data.

[0952] Step 4:

[0953] The device sends the basic information and SNS account information entered by the user to the server. The input data includes the basic information and SNS account information. The output is the completion of information transfer to the server.

[0954] Step 5:

[0955] The server uses SNS APIs (e.g., Instagram API, Facebook Graph API) to collect data such as posts that the other person has "liked," articles that they have shared, accounts they are following, and the content of their posts. SNS account information is used as input, and the other person's SNS data is collected as output. Specific operations include making a request to the SNS API, retrieving the data, and saving the data.

[0956] Step 6:

[0957] The data collected by the server is analyzed using natural language processing (NLP) and image analysis algorithms. Social media data is used as input. Specific operations include tokenizing text data, topic modeling using LDA (Latent Dirichlet Allocation), and image recognition using CNN (Convolutional Neural Network). The output is data indicating the other person's interests and concerns.

[0958] Step 7:

[0959] The server uses the analysis results to search for relevant gift suggestions from online marketplaces (e.g., Amazon API or Rakuten API) or specific gift shop APIs. The analysis results are used as input and a list of gift suggestions is generated as output. Specific operations include making a request to the API, gathering product information, and generating a gift suggestion list.

[0960] Step 8:

[0961] The server filters gift suggestions, taking into account the user's budget and special requirements (e.g., eco-friendly products or specific brands). The input includes user preferences and a list of suggestions. The output is an optimized list of gift suggestions. The specific operation involves running a filtering algorithm.

[0962] Step 9:

[0963] The server sends the best gift candidate list to the user device, which contains the filtered gift list as input, and displays the gift candidate list on the user device as output.

[0964] Step 10:

[0965] The user selects the desired item from the list and clicks the "Proceed to Checkout" button, including the gift wishlist as input.

[0966] Step 11:

[0967] The terminal displays a checkout screen where the user enters payment and shipping information. The input includes the user's payment and shipping information.

[0968] Step 12:

[0969] The server receives the entered payment information, checks inventory and processes the purchase via the marketplace API. The output is a purchase completion notification and shipping information. Specific operations include making a request to the API, checking inventory, processing the payment, and sending a notification email.

[0970] Step 13:

[0971] The server sends a purchase completion notification and shipping information to the user and recipient, respectively. The input contains the result of the purchase process. The output is the completion of the notification and shipping information.

[0972] (Application example 1)

[0973] 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."

[0974] With conventional gift selection systems, it was difficult to suggest gifts that accurately reflected the recipient's interests, and there were insufficient means to provide detailed information to users in an easy-to-understand manner. This made it difficult for users to quickly select the perfect gift for the recipient, and the selection and purchase process was stressful.

[0975] 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.

[0976] In this invention, the server includes a means for inputting information provided by the user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for displaying detailed information (price, rating, category, etc.) of the generated gift candidates, and a means for purchasing and shipping the gift item selected by the user, thereby enabling the user to quickly select the best gift for the recipient and complete the purchase procedure without stress.

[0977] "User" refers to an individual who uses the Gift Suggestion System.

[0978] "Recipient" means the individual to whom you wish to send a Gift.

[0979] "Social Networking Service" refers to an online platform used by the Recipient that allows the Recipient to share their posts and activity data.

[0980] "Means for Obtaining Data" refers to the means for collecting the required data from the recipient's social networking service.

[0981] "Means for analyzing data" refers to means for extracting the recipient's interests and concerns using the acquired data.

[0982] The "means for generating gift candidates" refers to a means for generating gift candidates suitable for a recipient based on the analysis results.

[0983] "Detailed information" refers to specific information such as the price, rating, and category of the gift candidate.

[0984] "Purchase and Delivery Method" means the method by which a User purchases and completes the delivery process for the selected Gift.

[0985] This invention relates to a system that suggests optimal gifts based on information about the recipient and their activity data on social networking services (SNS). The system is composed of multiple components, including a user terminal, a server, and various APIs.

[0986] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[0987] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, followed accounts, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests. Specifically, the server tokenizes the obtained text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. Furthermore, the server uses image recognition algorithms (e.g., CNN) to analyze posted images and extract interest in specific brands and products.

[0988] Next, based on the analysis results, the server retrieves relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, rating, category, etc.) and extracts gift suggestions that best fit the recipient's profile. This includes filtering based on the user's budget and special requirements. Finally, the server sends the optimized gift suggestion list to the user's device and makes suggestions to the user.

[0989] The user's device displays this list to the user, allowing them to select the desired gift item from the suggested gifts. After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[0990] Specific examples

[0991] A specific example is given below.

[0992] scenario

[0993] A user wants to choose a birthday gift for a friend who is turning 35. The user accesses the application and enters the recipient's information (age, gender, friendship status). They also request permission to access the recipient's social media account and provide the account information to the system. The server collects the recipient's posts related to "cooking," "sports," and "travel" via the social media API. It analyzes the text and image data to extract the recipient's interests (e.g., sports equipment, kitchen gadgets, travel-related goods). It uses the marketplace API to obtain detailed information about related products and generate optimal gift suggestions. It filters the gift suggestions taking into account the user's budget and special requirements and sends the optimized gift suggestion list to the user's device. The user reviews the suggested gift items, selects a pair of jogging shoes, and completes the purchase. The server notifies the user and the recipient once the purchase and delivery process is complete.

[0994] Prompt Sentence Examples

[0995] Example input

[0996] "I'd like some suggestions for the perfect gift for my friend's birthday. Here are their social media accounts."

[0997] Example output

[0998] "Suggested gifts include: jogging shoes, a new blender, and a compact travel bag."

[0999] The specific hardware and software used includes social media APIs (e.g., Instagram API, Twitter API), natural language processing libraries (e.g., NLTK, spaCy), and image analysis models (e.g., ResNet50). Additionally, programming languages ​​such as Python and cloud services (e.g., AWS, Google Cloud) can be used for the server.

[1000] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1001] Step 1:

[1002] A user accesses the gift suggestion system using a device. The user enters basic information about the person they want to give a gift to (such as name, age, gender, and relationship). They also select the option to link the recipient's social media account. This information is sent from the device to the server. The input data (basic information, social media link) is stored on the server and used for analysis.

[1003] Step 2:

[1004] The server accesses the recipient's SNS account information and uses the API to obtain SNS data (liked posts, shared articles, followed accounts, post content, etc.). It obtains the recipient's activity data using the SNS API (e.g., Instagram API, Twitter API). The obtained data is divided into text data and image data. The input is data from the SNS API, and the output is text data and image data for analysis.

[1005] Step 3:

[1006] The server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests. Specifically, it tokenizes the text data and identifies areas of interest using topic modeling (e.g., LDA). It also analyzes posted images using image recognition algorithms (e.g., ResNet50) to extract interest in specific brands and products. The input is the text data and image data for analysis, and the output is the extracted recipient's interests.

[1007] Step 4:

[1008] Based on the analysis results, the server retrieves related gift suggestions from the APIs of online marketplaces or specific gift shops. It uses the APIs of online marketplaces (e.g., Amazon API, Rakuten Market API) to collect detailed information (price, rating, category, etc.) about related products. The input is the analysis results and data from the marketplace API, and the output is a list of gift suggestions.

[1009] Step 5:

[1010] The server filters gift suggestions based on the user's budget and special requirements, listing items that fit within a budget range or fall into a specific category. The input is a list of gift suggestions and user preferences, and the output is a filtered list of optimal gift suggestions.

[1011] Step 6:

[1012] The server sends the optimized gift candidate list to the user terminal. The user terminal displays this list to the user. The user can select desired items from the suggested gifts. The input is the optimized gift candidate list, and the output is the gift candidates presented to the user.

[1013] Step 7:

[1014] For the gift items selected by the user, the user device provides an interface to support the purchase process (input of payment information and delivery information). The user enters the required information and completes the purchase process. The input is the gift items selected by the user and payment and delivery information, and the output is the completion of the purchase process.

[1015] Step 8:

[1016] The server queries partner gift shops and marketplace APIs to check stock availability and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient. The input is purchase completion information, and the output is the stock availability result, the start of delivery procedures, and a completion notification.

[1017] 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.

[1018] This invention is a system that suggests the perfect gift based on information about the person a user wants to give a gift to and their activity data on social networking services (SNS), and further combines it with an emotion engine to recognize the user's emotions and improve the level of personalization of the suggested gifts. This system is composed of multiple components, including a user terminal, a server, various APIs, and an emotion engine.

[1019] Program processing description

[1020] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[1021] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[1022] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[1023] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[1024] Furthermore, the present invention incorporates an emotion engine to recognize users' emotions in real time and optimize gift suggestions based on their emotions. The emotion engine uses a camera and microphone to analyze users' facial expressions, voice tone, and input content.

[1025] The emotion engine includes facial recognition software that reads emotions from a user's facial expressions and voice analysis software that analyzes emotions from a user's tone of voice, allowing the engine to analyze the user's emotional state (e.g., joy, surprise, interest, etc.) while browsing gift suggestions and prioritize gift suggestions based on the user's emotions.

[1026] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[1027] Specific examples

[1028] A specific example is given below.

[1029] scenario:

[1030] A user named "Yamada Hanako" wants to choose a birthday present for her friend Tanaka Taro, who is 35. Furthermore, the gift is optimized taking into account Yamada Hanako's feelings.

[1031] 1. User device: Hanako Yamada accesses the application and enters Taro Tanaka's information (age 35, male, friend).

[1032] 2. User device: Hanako Yamada requests permission to access Taro Tanaka's Instagram account.

[1033] 3. User terminal: After obtaining permission to use, provide account information to the system.

[1034] 4. Server: Collects Tanaka Taro's posting data on "cooking," "sports," and "travel" via the SNS API.

[1035] 5. Server: Analyzes the text and image data and extracts Taro Tanaka's interests (e.g., sports equipment, kitchen gadgets, travel-related goods).

[1036] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[1037] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[1038] 8. Server: Use the emotion engine to analyze Hanako Yamada's emotional state while she browses gift suggestions and optimize gift suggestions based on her emotions.

[1039] 9. Server: Sends the optimized gift candidate list to the user device.

[1040] 10. User device: Display suggested gift items for Hanako (e.g., jogging shoes, the latest blender, and a compact travel bag).

[1041] 11. User device: Hanako Yamada selects jogging shoes and completes the purchase process.

[1042] 12. Server: Notify the user and recipient once the purchase and delivery process is complete.

[1043] In this way, a system is provided that allows users to select the most suitable gift in a short time while taking their emotions into consideration.

[1044] The processing flow will be explained below.

[1045] Step 1:

[1046] User device: The user accesses the Present Match AI and enters basic information about the person they want to give a gift to (name, age, gender, relationship, etc.).

[1047] Step 2:

[1048] User Device: The user selects the option to link the social networking service (SNS) account of the person to whom the gift is to be given.

[1049] Step 3:

[1050] User device: The user requests and receives approval for access to the recipient's social media account.

[1051] Step 4:

[1052] Server: Uses the SNS API to retrieve data such as the recipient's liked posts, shared articles, followed accounts, and post content.

[1053] Step 5:

[1054] Server: Analyzes the acquired SNS data using natural language processing (NLP) algorithms, tokenizes the text data, and uses topic modeling (e.g., LDA) to extract the recipient's areas of interest.

[1055] Step 6:

[1056] Server: Image and video data is analyzed using image recognition algorithms (e.g., CNN) to identify interest in specific brands and products.

[1057] Step 7:

[1058] Server: Based on the extracted areas of interest and other information, collect relevant gift suggestions from online marketplaces and APIs of specific gift shops.

[1059] Step 8:

[1060] Server: Obtains detailed information about each product (price, rating, category, etc.) and filters it according to the user's budget or special requirements.

[1061] Step 9:

[1062] Server: Sends the optimized gift candidate list to the user device.

[1063] Step 10:

[1064] User terminal: Display a list of suggested gifts to the user and allow the user to select the desired gift item.

[1065] Step 11:

[1066] User device: The user selects the gift item and begins the purchase process.

[1067] Step 12:

[1068] User terminal: Provides an interface for entering payment and shipping information.

[1069] Step 13:

[1070] Server: Once the purchase process is complete, we contact the partner gift shop or marketplace API to check stock availability and proceed with the delivery process.

[1071] Step 14:

[1072] Server: Sends purchase completion notification and shipping information to the user and recipient.

[1073] Step 15:

[1074] User device: Display purchase completion notification and shipping information to the user.

[1075] Step 16:

[1076] Emotion Engine: Uses the camera and microphone to collect the user's facial expressions and tone of voice as they browse gift options.

[1077] Step 17:

[1078] Emotion engine: Analyzes collected data and recognizes the user's emotional state (e.g., joy, surprise, interest).

[1079] Step 18:

[1080] Emotion Engine: Based on the recognized emotional state, it reprioritizes the gift suggestion list and lists gifts that best fit the user's emotions.

[1081] Step 19:

[1082] User device: Display the re-prioritized gift idea list to the user.

[1083] Step 20:

[1084] User device: The user selects a gift from the reprioritized list and initiates the final purchase process.

[1085] Example 2

[1086] 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."

[1087] Conventional gift suggestion systems can generate gift candidates based on information provided by users and social media data, but they do not take the user's emotional state into account, resulting in a low level of personalized gift suggestions. Furthermore, the gift selection process cannot reflect the user's emotional changes in real time, making it difficult to suggest optimal gifts. Furthermore, the suggested gifts may not meet the user's expectations, resulting in a poor user experience.

[1088] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1089] In this invention, the server includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, a means for recognizing the user's emotions and optimizing the gift candidates, and a means for suggesting the generated gift candidates to the user, thereby enabling highly personalized gift suggestions that take the user's emotional state into consideration.

[1090] "Information provided by the user" refers to basic information about the recipient (such as name, age, gender, relationship, etc.) that the user enters into the system.

[1091] "Means of obtaining data from the recipient's social networking service" refers to a mechanism for accessing the recipient's social media account via an API or other means and collecting data such as posts, "likes," shared articles, and followed accounts.

[1092] "Means of analyzing the acquired data and extracting the recipient's interests and concerns" refers to methods of using natural language processing (NLP) and image analysis algorithms to identify the recipient's interests and areas of concern from the collected social media data.

[1093] "Means for generating gift suggestions based on analysis results" refers to a system that uses APIs of online marketplaces and gift shops to create a list of related products based on extracted interests.

[1094] "Means to recognize user emotions and optimize gift candidates" refers to a system that uses cameras and microphones to analyze the user's facial expressions and tone of voice in real time and adjusts the ranking of gift candidates based on the analysis results.

[1095] "Means for suggesting generated gift candidates to a user" refers to a system that transmits the optimized gift candidate list to a user terminal and displays it through a user interface.

[1096] "Means for purchasing and shipping gift items selected by the user" refers to a system that provides an interface for users to enter payment and shipping information for the gift selected by the user, and processes the items to be properly delivered after the purchase is completed.

[1097] "Methods of using recipient account information linked by the user" refers to methods of linking social media account information and collecting necessary data with the user's permission.

[1098] This invention relates to a system that suggests the perfect gift based on information about the person a user wants to give a gift to and their activity data on social networking services (SNS). Furthermore, this system is combined with an emotion engine, which can recognize the user's emotions and improve the level of personalization of the gifts it suggests. This system is composed of multiple components, including a user terminal, a server, various APIs, and the emotion engine.

[1099] The user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[1100] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[1101] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[1102] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[1103] Furthermore, the present invention incorporates an emotion engine to recognize a user's emotions in real time and optimize gift suggestions based on those emotions. The emotion engine uses a camera and microphone to analyze a user's facial expressions, voice tone, and input content. The emotion engine includes facial expression recognition software that reads emotions from the user's facial expressions and voice analysis software that analyzes emotions from the user's voice tone. This allows the system to analyze the user's emotional state (e.g., joy, surprise, interest, etc.) while browsing gift suggestions and prioritize gift suggestions based on the user's emotions.

[1104] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[1105] Specific examples

[1106] A specific example is given below.

[1107] scenario:

[1108] A user wants to choose a birthday gift for a friend, and further optimizes the gift by taking emotions into account.

[1109] 1. User device: The user accesses the application and enters their friend's information (age, gender, relationship, etc.).

[1110] 2. User device: The user requests permission to access a friend's social media account.

[1111] 3. User terminal: After obtaining permission to use, provide account information to the system.

[1112] 4. Server: Collects friends' posting data about "cooking," "sports," and "travel" via SNS API.

[1113] 5. Server: Analyzes text and image data to extract friends' interests (e.g., sports equipment, kitchen gadgets, travel-related items).

[1114] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[1115] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[1116] 8. Server: Uses an emotion engine to analyze the emotional state of the user while browsing gift suggestions and optimize gift suggestions based on that emotion.

[1117] 9. Server: Sends the optimized gift candidate list to the user device.

[1118] 10. User device: Display suggested gift items to the user (e.g., jogging shoes, the latest blender, a compact travel bag).

[1119] 11. User device: The user selects the jogging shoes and completes the purchase.

[1120] 12. Server: Notify the user and recipient once the purchase and delivery process is complete.

[1121] Example prompts for generative AI models

[1122] Below are some examples of specific prompt sentences.

[1123] Prompt Sentence Examples

[1124] A user accesses a system that suggests the best gift for a friend's birthday based on social media data and the user's emotions. Explain all the steps the system takes, including the information the user provides to the system, data analysis, and emotion recognition.

[1125] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1126] Step 1: Enter your user information

[1127] Users simply enter basic information about the recipient (such as name, age, gender, and relationship) into the device.

[1128] Input is basic information provided by the user.

[1129] The output is basic information stored on the device.

[1130] Specific behavior: The user enters basic information into the form and clicks the "Next" button.

[1131] Step 2: Obtain and send recipient's social media account information

[1132] Users simply select the option to request permission to link to the other person's social media account.

[1133] The input is the user's social media account information and link permission of the other person.

[1134] The output is the social media account information and permissions sent to the server.

[1135] Specific operation: The user allows access to the social networking account and sends the link information.

[1136] Step 3: Collect social media data

[1137] The server uses an API to access the recipient's social media account and collect the necessary data.

[1138] The input is the SNS account information sent to the server.

[1139] The output is collected social media data (likes, shared posts, followed accounts, post content, etc.).

[1140] Specific operation: The server calls the SNS API and obtains the recipient's activity data.

[1141] Step 4: Analyze the data

[1142] The server analyzes the collected social media data using natural language processing (NLP) and image analysis algorithms.

[1143] The input is collected social media data.

[1144] The output is an analysis that indicates the recipient's interests.

[1145] What it does: The server tokenizes the text data, identifies regions of interest using topic modeling (e.g., LDA), and analyzes the images using image recognition algorithms (e.g., CNN).

[1146] Step 5: Generate gift suggestions

[1147] Based on the analysis results, the server retrieves relevant gift suggestions from APIs of online marketplaces and gift shops.

[1148] Inputs are the analysis results and the user's budget and special requirements.

[1149] The output is a generated list of gift suggestions.

[1150] Specific operation: The server calls the product's API to obtain detailed information such as price, rating, category, etc.

[1151] Step 6: Emotion Engine in Action

[1152] The device uses a camera and microphone to collect the user's facial expressions and voice tone.

[1153] The input is the user's facial expression data and voice data.

[1154] The output is the analyzed emotion data.

[1155] How it works: The device uses facial recognition and voice analysis software to analyze emotions.

[1156] Step 7: Optimize and display gift ideas

[1157] The server prioritizes gift suggestions based on the user's emotional data.

[1158] The inputs are emotion data and a gift candidate list.

[1159] The output is an optimized gift suggestion list.

[1160] Specific operation: The server adjusts the priority of gift candidates based on the emotional data and sends the list to the user's device.

[1161] Step 8: Gift Selection and Checkout

[1162] Users simply select the most suitable item from the displayed gift options.

[1163] The input is an optimized gift suggestion list.

[1164] The output is the selected gift item.

[1165] What happens: The user adds the selected gift item to their cart and begins the checkout process.

[1166] Step 9: Purchase completion and notification

[1167] The server queries partner gift shops and marketplace APIs to check inventory and process shipping.

[1168] The input is the selected gift item and shipping information.

[1169] The output is a confirmation of purchase completion and shipping information.

[1170] What happens: The server sends a notification to the user and recipient once the purchase is complete.

[1171] (Application example 2)

[1172] 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."

[1173] Conventional gift suggestion systems suggest gifts by taking into account the recipient's information and social media data, but because they are unable to consider the user's emotions, it is difficult to suggest the optimal gift that is in line with the user's feelings. Furthermore, there are cases where the suggested gift does not perfectly match the recipient's interests. Therefore, there was a need for a system that could help users select a gift that satisfies them.

[1174] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, a means for suggesting the generated gift candidates to the user, and a means for recognizing the user's emotions in real time and optimizing the suggested gift candidates. This makes it possible to suggest optimal gifts based on the recipient's interests while taking the user's emotions into consideration.

[1175] The "means for inputting information provided by the user" refers to an input device and software that allows the user to input basic information about the recipient, budget, etc.

[1176] "Means for obtaining data from the recipient's social networking service" refers to the means of communication and software for accessing the recipient's social networking account information and obtaining data such as posts, likes, and shared articles via API.

[1177] "Means for analyzing acquired data and extracting the recipient's interests" refers to hardware and software that uses natural language processing and image analysis algorithms to analyze acquired SNS data and identify the recipient's areas of interest.

[1178] The "means for generating gift candidates based on the analysis results" refers to software that obtains related product information from the APIs of online marketplaces and gift shops based on the analyzed interests and generates gift candidates.

[1179] The "means for suggesting generated gift candidates to the user" refers to a display device and software for presenting the generated multiple gift candidates to the user and assisting in the selection.

[1180] "Means for recognizing a user's emotions in real time and optimizing suggested gift candidates" refers to hardware and software that uses a camera and microphone to analyze emotions from a user's facial expressions and tone of voice, and optimizes the prioritization of gift candidates based on the user's emotions.

[1181] This invention is realized by constructing a gift suggestion system using a user terminal and a server. This system includes means for inputting information provided by a user, means for acquiring data from the recipient's social networking service, means for analyzing the acquired data and extracting the recipient's interests, means for generating gift candidates based on the analysis results, means for suggesting the generated gift candidates to the user, and means for recognizing the user's emotions in real time and optimizing the suggested gift candidates.

[1182] First, the user device provides an input device and software that allows the user to input basic information about the recipient, their budget, etc. This input information is sent to the server. Meanwhile, the recipient's social media account information is also linked to the user, and the server obtains the recipient's posts, likes, shared articles, etc. through the social media API. The obtained data is then analyzed on the server using natural language processing tools (e.g., TextBlob) and image analysis algorithms (e.g., CNN) to extract the recipient's interests and concerns.

[1183] Based on the analysis results, the server retrieves relevant gift suggestions from online marketplace APIs and gift shop APIs, and obtains detailed information (price, rating, category, etc.). This generates gift suggestions that take into account the user's budget and special requirements. Furthermore, it uses an emotion engine (e.g., FER) to recognize the user's real-time emotions through the camera and microphone on the user's device. Based on this, the priority of gift suggestions is optimized and suggested to the user.

[1184] Specifically, the server begins with a step in which a user accesses the application and enters the recipient's basic information and social media account. For example, suppose a user named "Yamada Hanako" wants to choose a gift for a "friend (35 years old, male)." The user links her "Instagram account," and the server obtains the social media data. Analysis reveals that she is interested in "cooking," "sports," and "travel," and generates gift suggestions based on that. After that, the camera determines that Yamada Hanako's emotion is "joy," and sports and travel-related goods are prioritized as suggestions.

[1185] Example prompts to input to the generative AI model:

[1186] "Please enter the name and social media account of the person you would like to give the gift to:

[1187] Name: Yamada Hanako

[1188] Social Media Account: example_user

[1189] Next, enter your budget (e.g., 5000 yen):

[1190] Budget: 5,000 yen

[1191] Turn on the camera and start emotion recognition.

[1192] ...

[1193] We're optimizing gift suggestions...

[1194] Perfect gift idea list:

[1195] 1. Jogging shoes

[1196] 2. Modern Blender

[1197] 3. Compact travel bag

[1198] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1199] Step 1:

[1200] The user enters the basic information and social media account information of the person they want to give the gift to.

[1201] Input: Name, age, gender, relationship, SNS account information

[1202] Output: The acquired information is sent from the device to the server.

[1203] Specific operation: When a user enters the required information into the input form on the terminal and clicks the send button, the terminal sends this information to the server.

[1204] Step 2:

[1205] The server accesses the recipient's SNS account and obtains the recipient's posted data, etc., via the SNS API.

[1206] Input: Recipient's SNS account information

[1207] Output: Post data of recipients, such as likes and shared posts, obtained from the SNS API

[1208] What it does: The server sends an API request to the linked social media account and receives data from the social media platform in response.

[1209] Step 3:

[1210] The server analyzes the acquired SNS data using natural language processing and image analysis algorithms to extract the recipient's interests and concerns.

[1211] Input: SNS data (text and images)

[1212] Output: A list of keywords related to the recipient's interests

[1213] How it works: The server uses TextBlob to analyze text and topic modeling to identify areas of interest, and uses CNN to analyze image data and extract interest in specific brands and products.

[1214] Step 4:

[1215] The server retrieves gift suggestions from the online marketplace API or gift shop API based on the analysis results.

[1216] Input: List of keywords of interest

[1217] Output: A list of related gift ideas and detailed information about each item

[1218] Specific operation: The server sends a request including keywords to the marketplace API and receives related product information in response.

[1219] Step 5:

[1220] The server filters gift suggestions, taking into account the user's budget and special requirements.

[1221] Input: Gift idea list, user budget information, special requirements

[1222] Output: A filtered list of gift ideas

[1223] What happens: The server checks the details of each product and selects the appropriate product based on the user's budget and requirements.

[1224] Step 6:

[1225] The terminal uses the user's camera and microphone to recognize the user's emotions in real time.

[1226] Input: User's facial and voice data

[1227] Output: User's emotional state (e.g., happy, surprised, etc.)

[1228] Specific operation: The device collects data in real time from the camera and microphone and analyzes the data using FER and voice analysis software.

[1229] Step 7:

[1230] The server optimizes the prioritization of gift candidates based on the user's emotional state.

[1231] Input: A filtered list of gift ideas, the user's emotional state

[1232] Output: Optimized list of gift ideas

[1233] Specific operation: The server takes into account the user's emotions and prioritizes placing the most suitable gifts at the top of the list.

[1234] Step 8:

[1235] The terminal displays the optimized gift candidate list to the user, and the user selects a gift.

[1236] Input: A list of optimized gift ideas

[1237] Output: Gift items selected by the user

[1238] Specific operation: The device displays a list of gift options on the screen, and the user selects the desired item.

[1239] Step 9:

[1240] The server processes the purchase and delivery of the selected gift item.

[1241] Input: Gift items selected by user, payment information, shipping information

[1242] Output: Purchase confirmation message, delivery confirmation message

[1243] Specific operation: The server accesses the marketplace API to complete the purchase, confirms the shipping information, and notifies the user and recipient.

[1244] 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.

[1245] 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.

[1246] 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.

[1247] [Fourth embodiment]

[1248] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1249] 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.

[1250] 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).

[1251] 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.

[1252] 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.

[1253] 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).

[1254] 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.

[1255] 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.

[1256] 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.

[1257] 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.

[1258] 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.

[1259] 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.

[1260] 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."

[1261] This invention relates to a system that suggests optimal gifts based on information about the recipient and their activity data on social networking services (SNS). This system is composed of multiple components, including a user terminal, a server, and various APIs.

[1262] Program processing description

[1263] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[1264] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[1265] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[1266] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[1267] Finally, the server sends the optimized gift candidate list to the user terminal and suggests it to the user, who then displays the list to the user, allowing the user to select a desired item from the suggested gifts.

[1268] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[1269] Specific examples

[1270] A specific example is given below.

[1271] scenario:

[1272] User "Yamada Hanako" wants to choose a birthday present for her 35-year-old friend Tanaka Taro.

[1273] 1. User device: Hanako Yamada accesses the application and enters Taro Tanaka's information (age 35, male, friend).

[1274] 2. User device: Hanako Yamada requests permission to access Taro Tanaka's Instagram account.

[1275] 3. User terminal: After obtaining permission to use, provide account information to the system.

[1276] 4. Server: Collects Tanaka Taro's posting data on "cooking," "sports," and "travel" via the SNS API.

[1277] 5. Server: Analyzes the text and image data and extracts Taro Tanaka's interests (e.g., sports equipment, kitchen gadgets, travel-related goods).

[1278] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[1279] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[1280] 8. Server: Sends the optimized gift candidate list to the user device.

[1281] 9. User device: Display suggested gift items for Hanako (e.g., jogging shoes, the latest blender, and a compact travel bag).

[1282] 10. User device: Hanako Yamada selects jogging shoes and completes the purchase process.

[1283] 11. Server: Notify the user and recipient once the purchase and delivery process is complete.

[1284] In this way, a system is provided that allows users to select the most suitable gift in a short amount of time without stress.

[1285] The processing flow will be explained below.

[1286] Step 1:

[1287] User device: The user accesses the Present Match AI and enters basic information about the person they want to give a gift to (name, age, gender, relationship, etc.).

[1288] Step 2:

[1289] User Device: The user selects the option to link the social networking service (SNS) account of the person to whom the gift is to be given.

[1290] Step 3:

[1291] User device: The user requests and receives approval for access to the recipient's social media account.

[1292] Step 4:

[1293] Server: Uses the SNS API to retrieve data such as the recipient's liked posts, shared articles, followed accounts, and post content.

[1294] Step 5:

[1295] Server: Analyzes the acquired SNS data using natural language processing (NLP) algorithms, tokenizes the text data, and uses topic modeling (e.g., LDA) to extract the recipient's areas of interest.

[1296] Step 6:

[1297] Server: Image and video data is analyzed using image recognition algorithms (e.g., CNN) to identify interest in specific brands and products.

[1298] Step 7:

[1299] Server: Based on the extracted areas of interest and other information, collect relevant gift suggestions from online marketplaces and APIs of specific gift shops.

[1300] Step 8:

[1301] Server: Obtains detailed information about each product (price, rating, category, etc.) and filters it according to the user's budget or special requirements.

[1302] Step 9:

[1303] Server: Sends the optimized gift candidate list to the user device.

[1304] Step 10:

[1305] User terminal: Display a list of suggested gifts to the user and allow the user to select the desired gift item.

[1306] Step 11:

[1307] User device: The user selects the gift item and begins the purchase process.

[1308] Step 12:

[1309] User terminal: Provides an interface for entering payment and shipping information.

[1310] Step 13:

[1311] Server: Once the purchase process is complete, we contact the partner gift shop or marketplace API to check stock availability and proceed with the delivery process.

[1312] Step 14:

[1313] Server: Sends purchase completion notification and shipping information to the user and recipient.

[1314] Step 15:

[1315] User device: Display purchase completion notification and shipping information to the user.

[1316] Example 1

[1317] 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."

[1318] Today's consumers often spend a lot of time and effort selecting gifts, which can be especially challenging when considering the recipient's preferences. Therefore, there is a need for a system that can suggest the best gift based on the recipient's interests. However, existing systems lack the ability to collect and analyze social media data, making it difficult to meet individual needs.

[1319] 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.

[1320] In this invention, the server includes means for inputting information provided by a user, means for acquiring data from the recipient's social networking service, means for analyzing the acquired data and extracting the recipient's interests, means for analyzing the data using natural language processing and image analysis algorithms, means for acquiring relevant gift candidates from online marketplaces and databases of specific gift shops based on the analysis results, means for filtering the gift candidates taking into account the user's budget and special requirements, and means for suggesting the generated gift candidates to the user, thereby enabling the user to select the most suitable gift in a short period of time.

[1321] "User" means an individual or organization that uses the system, inputs information through a terminal, and makes gift suggestions and makes purchases.

[1322] "Terminal" refers to a computer device or mobile device that a user accesses and that allows the input and display of information.

[1323] "Server" refers to the central device that manages the entire system, collects, analyzes, filters, and recommends optimal gifts.

[1324] A "social networking service" is an online platform that enables people to communicate over the internet and is subject to data collection.

[1325] "Data Acquisition Methods" refers to APIs and other technical methods for collecting the required information from social networking services.

[1326] "Natural language processing" refers to technology that analyzes acquired text data and understands the recipient's interests and concerns.

[1327] "Image analysis algorithm" refers to technology that analyzes acquired image data and recognizes characteristics such as specific brands and products.

[1328] "Analysis Results" refers to information about the recipient's interests and concerns obtained by analyzing information collected using data acquisition means using natural language processing and image analysis algorithms.

[1329] "Online marketplace" refers to an online commercial platform where various products can be purchased.

[1330] "Gift suggestion means" refers to a technical method for presenting gift candidates generated based on the analysis results to the user.

[1331] MODE FOR CARRYING OUT THE INVENTION

[1332] This invention is a system that suggests optimal gifts based on information about the recipient of a gift and the recipient's activity data on a social networking service. This system is composed of multiple components, including a user terminal, a server, and various APIs. Detailed embodiments are described below.

[1333] First, the user accesses the gift suggestion system using a device. The application home screen displays a "Gift Suggestion" option, and the user selects this option.

[1334] The user is presented with a form where they can enter basic information about the recipient, such as their name, age, gender, and relationship. Following this, the user selects the option to link their social media account. Here, the user obtains permission to access their social media account (e.g., Instagram, Facebook, etc.) and provides their account information to the system.

[1335] The device sends the basic information entered by the user and social media account information to a server, which then uses social media APIs (such as Instagram API and Facebook Graph API) to collect data such as the other person's "liked" posts, shared articles, accounts they follow, and post content.

[1336] The server analyzes the collected data using natural language processing (NLP) and image analysis algorithms. Specifically, it tokenizes text data and extracts multiple themes using LDA (Latent Dirichlet Allocation). Image data is analyzed using CNN (Convolutional Neural Networks) to extract interest in specific brands and products. This allows for highly accurate detection of a person's interests.

[1337] Based on the analysis results, the server searches for relevant gift suggestions from online marketplaces (e.g., Amazon API or Rakuten API) or specific gift shop APIs, filtering them based on the user's budget and special requirements (e.g., eco-friendly products or specific brands).

[1338] The server then generates a list of optimal gift options and sends it to the user's device, where the user can select the items they want from the list, including details such as images, prices, and ratings for each item.

[1339] When a user selects a gift item, the user's device displays a checkout screen where the user can enter payment and delivery information. The server receives the information, checks inventory, and completes the purchase via the marketplace API. Finally, the server sends a purchase completion notification and delivery information to the user and recipient, respectively.

[1340] Specific examples

[1341] A specific example is given below.

[1342] scenario:

[1343] User A wants to give a birthday gift to friend B who is 35 years old:

[1344] 1. User A accesses the application and enters B's information (35 years old, male, friend).

[1345] 2. User A requests permission to access User B's Instagram account.

[1346] 3. After User A has been granted access, he / she provides his / her account information to the system.

[1347] 4. The server uses the SNS API to collect B's posts about "cooking," "sports," and "travel."

[1348] 5. The server analyzes the collected data and extracts B's interests (e.g., sports equipment, kitchen gadgets, travel-related products).

[1349] 6. The server uses the Amazon API or Rakuten API to search for related products and generate gift suggestions.

[1350] 7. The server filters the gift suggestions taking into account User A's budget and special requirements.

[1351] 8. The server sends the list of best gift candidates to User A's device.

[1352] 9. User A selects jogging shoes from the suggested gift items (e.g., jogging shoes, a new blender, and a compact travel bag) and completes the purchase.

[1353] 10. The server notifies User A and Recipient B once the purchase and delivery process is complete.

[1354] This system allows users to choose the perfect gift in a short amount of time.

[1355] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1356] Step 1:

[1357] The user accesses the gift suggestion system through a terminal and inputs basic information about the recipient (name, age, gender, relationship). The input data includes the user's basic information. The terminal then sends this information to the server.

[1358] Step 2:

[1359] The server receives the basic information sent by the user and displays a screen on the user's device that includes the option to allow SNS account linking. The SNS account linking screen is generated as the output.

[1360] Step 3:

[1361] The user grants permission to access the other person's social media account (e.g., Instagram, Facebook, etc.). The user enters their social media account information and completes authorization authentication. The social media account information is included as input data.

[1362] Step 4:

[1363] The device sends the basic information and SNS account information entered by the user to the server. The input data includes the basic information and SNS account information. The output is the completion of information transfer to the server.

[1364] Step 5:

[1365] The server uses SNS APIs (e.g., Instagram API, Facebook Graph API) to collect data such as posts that the other person has "liked," articles that they have shared, accounts they are following, and the content of their posts. SNS account information is used as input, and the other person's SNS data is collected as output. Specific operations include making a request to the SNS API, retrieving the data, and saving the data.

[1366] Step 6:

[1367] The data collected by the server is analyzed using natural language processing (NLP) and image analysis algorithms. Social media data is used as input. Specific operations include tokenizing text data, topic modeling using LDA (Latent Dirichlet Allocation), and image recognition using CNN (Convolutional Neural Network). The output is data indicating the other person's interests and concerns.

[1368] Step 7:

[1369] The server uses the analysis results to search for relevant gift suggestions from online marketplaces (e.g., Amazon API or Rakuten API) or specific gift shop APIs. The analysis results are used as input and a list of gift suggestions is generated as output. Specific operations include making a request to the API, gathering product information, and generating a gift suggestion list.

[1370] Step 8:

[1371] The server filters gift suggestions, taking into account the user's budget and special requirements (e.g., eco-friendly products or specific brands). The input includes user preferences and a list of suggestions. The output is an optimized list of gift suggestions. The specific operation involves running a filtering algorithm.

[1372] Step 9:

[1373] The server sends the best gift candidate list to the user device, which contains the filtered gift list as input, and displays the gift candidate list on the user device as output.

[1374] Step 10:

[1375] The user selects the desired item from the list and clicks the "Proceed to Checkout" button, including the gift wishlist as input.

[1376] Step 11:

[1377] The terminal displays a checkout screen where the user enters payment and shipping information. The input includes the user's payment and shipping information.

[1378] Step 12:

[1379] The server receives the entered payment information, checks inventory and processes the purchase via the marketplace API. The output is a purchase completion notification and shipping information. Specific operations include making a request to the API, checking inventory, processing the payment, and sending a notification email.

[1380] Step 13:

[1381] The server sends a purchase completion notification and shipping information to the user and recipient, respectively. The input contains the result of the purchase process. The output is the completion of the notification and shipping information.

[1382] (Application example 1)

[1383] 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."

[1384] With conventional gift selection systems, it was difficult to suggest gifts that accurately reflected the recipient's interests, and there were insufficient means to provide detailed information to users in an easy-to-understand manner. This made it difficult for users to quickly select the perfect gift for the recipient, and the selection and purchase process was stressful.

[1385] 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.

[1386] In this invention, the server includes a means for inputting information provided by the user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for displaying detailed information (price, rating, category, etc.) of the generated gift candidates, and a means for purchasing and shipping the gift item selected by the user, thereby enabling the user to quickly select the best gift for the recipient and complete the purchase procedure without stress.

[1387] "User" refers to an individual who uses the Gift Suggestion System.

[1388] "Recipient" means the individual to whom you wish to send a Gift.

[1389] "Social Networking Service" refers to an online platform used by the Recipient that allows the Recipient to share their posts and activity data.

[1390] "Means for Obtaining Data" refers to the means for collecting the required data from the recipient's social networking service.

[1391] "Means for analyzing data" refers to means for extracting the recipient's interests and concerns using the acquired data.

[1392] The "means for generating gift candidates" refers to a means for generating gift candidates suitable for a recipient based on the analysis results.

[1393] "Detailed information" refers to specific information such as the price, rating, and category of the gift candidate.

[1394] "Purchase and Delivery Method" means the method by which a User purchases and completes the delivery process for the selected Gift.

[1395] This invention relates to a system that suggests optimal gifts based on information about the recipient and their activity data on social networking services (SNS). The system is composed of multiple components, including a user terminal, a server, and various APIs.

[1396] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[1397] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, followed accounts, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests. Specifically, the server tokenizes the obtained text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. Furthermore, the server uses image recognition algorithms (e.g., CNN) to analyze posted images and extract interest in specific brands and products.

[1398] Next, based on the analysis results, the server retrieves relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, rating, category, etc.) and extracts gift suggestions that best fit the recipient's profile. This includes filtering based on the user's budget and special requirements. Finally, the server sends the optimized gift suggestion list to the user's device and makes suggestions to the user.

[1399] The user's device displays this list to the user, allowing them to select the desired gift item from the suggested gifts. After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[1400] Specific examples

[1401] A specific example is given below.

[1402] scenario

[1403] A user wants to choose a birthday gift for a friend who is turning 35. The user accesses the application and enters the recipient's information (age, gender, friendship status). They also request permission to access the recipient's social media account and provide the account information to the system. The server collects the recipient's posts related to "cooking," "sports," and "travel" via the social media API. It analyzes the text and image data to extract the recipient's interests (e.g., sports equipment, kitchen gadgets, travel-related goods). It uses the marketplace API to obtain detailed information about related products and generate optimal gift suggestions. It filters the gift suggestions taking into account the user's budget and special requirements and sends the optimized gift suggestion list to the user's device. The user reviews the suggested gift items, selects a pair of jogging shoes, and completes the purchase. The server notifies the user and the recipient once the purchase and delivery process is complete.

[1404] Prompt Sentence Examples

[1405] Example input

[1406] "I'd like some suggestions for the perfect gift for my friend's birthday. Here are their social media accounts."

[1407] Example output

[1408] "Suggested gifts include: jogging shoes, a new blender, and a compact travel bag."

[1409] The specific hardware and software used includes social media APIs (e.g., Instagram API, Twitter API), natural language processing libraries (e.g., NLTK, spaCy), and image analysis models (e.g., ResNet50). Additionally, programming languages ​​such as Python and cloud services (e.g., AWS, Google Cloud) can be used for the server.

[1410] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1411] Step 1:

[1412] A user accesses the gift suggestion system using a device. The user enters basic information about the person they want to give a gift to (such as name, age, gender, and relationship). They also select the option to link the recipient's social media account. This information is sent from the device to the server. The input data (basic information, social media link) is stored on the server and used for analysis.

[1413] Step 2:

[1414] The server accesses the recipient's SNS account information and uses the API to obtain SNS data (liked posts, shared articles, followed accounts, post content, etc.). It obtains the recipient's activity data using the SNS API (e.g., Instagram API, Twitter API). The obtained data is divided into text data and image data. The input is data from the SNS API, and the output is text data and image data for analysis.

[1415] Step 3:

[1416] The server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests. Specifically, it tokenizes the text data and identifies areas of interest using topic modeling (e.g., LDA). It also analyzes posted images using image recognition algorithms (e.g., ResNet50) to extract interest in specific brands and products. The input is the text data and image data for analysis, and the output is the extracted recipient's interests.

[1417] Step 4:

[1418] Based on the analysis results, the server retrieves related gift suggestions from the APIs of online marketplaces or specific gift shops. It uses the APIs of online marketplaces (e.g., Amazon API, Rakuten Market API) to collect detailed information (price, rating, category, etc.) about related products. The input is the analysis results and data from the marketplace API, and the output is a list of gift suggestions.

[1419] Step 5:

[1420] The server filters gift suggestions based on the user's budget and special requirements, listing items that fit within a budget range or fall into a specific category. The input is a list of gift suggestions and user preferences, and the output is a filtered list of optimal gift suggestions.

[1421] Step 6:

[1422] The server sends the optimized gift candidate list to the user terminal. The user terminal displays this list to the user. The user can select desired items from the suggested gifts. The input is the optimized gift candidate list, and the output is the gift candidates presented to the user.

[1423] Step 7:

[1424] For the gift items selected by the user, the user device provides an interface to support the purchase process (input of payment information and delivery information). The user enters the required information and completes the purchase process. The input is the gift items selected by the user and payment and delivery information, and the output is the completion of the purchase process.

[1425] Step 8:

[1426] The server queries partner gift shops and marketplace APIs to check stock availability and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient. The input is purchase completion information, and the output is the stock availability result, the start of delivery procedures, and a completion notification.

[1427] 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.

[1428] This invention is a system that suggests the perfect gift based on information about the person a user wants to give a gift to and their activity data on social networking services (SNS), and further combines it with an emotion engine to recognize the user's emotions and improve the level of personalization of the suggested gifts. This system is composed of multiple components, including a user terminal, a server, various APIs, and an emotion engine.

[1429] Program processing description

[1430] First, a user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and then selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[1431] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[1432] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[1433] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[1434] Furthermore, the present invention incorporates an emotion engine to recognize users' emotions in real time and optimize gift suggestions based on their emotions. The emotion engine uses a camera and microphone to analyze users' facial expressions, voice tone, and input content.

[1435] The emotion engine includes facial recognition software that reads emotions from a user's facial expressions and voice analysis software that analyzes emotions from a user's tone of voice, allowing the engine to analyze the user's emotional state (e.g., joy, surprise, interest, etc.) while browsing gift suggestions and prioritize gift suggestions based on the user's emotions.

[1436] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[1437] Specific examples

[1438] A specific example is given below.

[1439] scenario:

[1440] A user named "Yamada Hanako" wants to choose a birthday present for her friend Tanaka Taro, who is 35. Furthermore, the gift is optimized taking into account Yamada Hanako's feelings.

[1441] 1. User device: Hanako Yamada accesses the application and enters Taro Tanaka's information (age 35, male, friend).

[1442] 2. User device: Hanako Yamada requests permission to access Taro Tanaka's Instagram account.

[1443] 3. User terminal: After obtaining permission to use, provide account information to the system.

[1444] 4. Server: Collects Tanaka Taro's posting data on "cooking," "sports," and "travel" via the SNS API.

[1445] 5. Server: Analyzes the text and image data and extracts Taro Tanaka's interests (e.g., sports equipment, kitchen gadgets, travel-related goods).

[1446] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[1447] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[1448] 8. Server: Use the emotion engine to analyze Hanako Yamada's emotional state while she browses gift suggestions and optimize gift suggestions based on her emotions.

[1449] 9. Server: Sends the optimized gift candidate list to the user device.

[1450] 10. User device: Display suggested gift items for Hanako (e.g., jogging shoes, the latest blender, and a compact travel bag).

[1451] 11. User device: Hanako Yamada selects jogging shoes and completes the purchase process.

[1452] 12. Server: Notify the user and recipient once the purchase and delivery process is complete.

[1453] In this way, a system is provided that allows users to select the most suitable gift in a short time while taking their emotions into consideration.

[1454] The processing flow will be explained below.

[1455] Step 1:

[1456] User device: The user accesses the Present Match AI and enters basic information about the person they want to give a gift to (name, age, gender, relationship, etc.).

[1457] Step 2:

[1458] User Device: The user selects the option to link the social networking service (SNS) account of the person to whom the gift is to be given.

[1459] Step 3:

[1460] User device: The user requests and receives approval for access to the recipient's social media account.

[1461] Step 4:

[1462] Server: Uses the SNS API to retrieve data such as the recipient's liked posts, shared articles, followed accounts, and post content.

[1463] Step 5:

[1464] Server: Analyzes the acquired SNS data using natural language processing (NLP) algorithms, tokenizes the text data, and uses topic modeling (e.g., LDA) to extract the recipient's areas of interest.

[1465] Step 6:

[1466] Server: Image and video data is analyzed using image recognition algorithms (e.g., CNN) to identify interest in specific brands and products.

[1467] Step 7:

[1468] Server: Based on the extracted areas of interest and other information, collect relevant gift suggestions from online marketplaces and APIs of specific gift shops.

[1469] Step 8:

[1470] Server: Obtains detailed information about each product (price, rating, category, etc.) and filters it according to the user's budget or special requirements.

[1471] Step 9:

[1472] Server: Sends the optimized gift candidate list to the user device.

[1473] Step 10:

[1474] User terminal: Display a list of suggested gifts to the user and allow the user to select the desired gift item.

[1475] Step 11:

[1476] User device: The user selects the gift item and begins the purchase process.

[1477] Step 12:

[1478] User terminal: Provides an interface for entering payment and shipping information.

[1479] Step 13:

[1480] Server: Once the purchase process is complete, we contact the partner gift shop or marketplace API to check stock availability and proceed with the delivery process.

[1481] Step 14:

[1482] Server: Sends purchase completion notification and shipping information to the user and recipient.

[1483] Step 15:

[1484] User device: Display purchase completion notification and shipping information to the user.

[1485] Step 16:

[1486] Emotion Engine: Uses the camera and microphone to collect the user's facial expressions and tone of voice as they browse gift options.

[1487] Step 17:

[1488] Emotion engine: Analyzes collected data and recognizes the user's emotional state (e.g., joy, surprise, interest).

[1489] Step 18:

[1490] Emotion Engine: Based on the recognized emotional state, it reprioritizes the gift suggestion list and lists gifts that best fit the user's emotions.

[1491] Step 19:

[1492] User device: Display the re-prioritized gift idea list to the user.

[1493] Step 20:

[1494] User device: The user selects a gift from the reprioritized list and initiates the final purchase process.

[1495] Example 2

[1496] 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."

[1497] Conventional gift suggestion systems can generate gift candidates based on information provided by users and social media data, but they do not take the user's emotional state into account, resulting in a low level of personalized gift suggestions. Furthermore, the gift selection process cannot reflect the user's emotional changes in real time, making it difficult to suggest optimal gifts. Furthermore, the suggested gifts may not meet the user's expectations, resulting in a poor user experience.

[1498] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1499] In this invention, the server includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, a means for recognizing the user's emotions and optimizing the gift candidates, and a means for suggesting the generated gift candidates to the user, thereby enabling highly personalized gift suggestions that take the user's emotional state into consideration.

[1500] "Information provided by the user" refers to basic information about the recipient (such as name, age, gender, relationship, etc.) that the user enters into the system.

[1501] "Means of obtaining data from the recipient's social networking service" refers to a mechanism for accessing the recipient's social media account via an API or other means and collecting data such as posts, "likes," shared articles, and followed accounts.

[1502] "Means of analyzing the acquired data and extracting the recipient's interests and concerns" refers to methods of using natural language processing (NLP) and image analysis algorithms to identify the recipient's interests and areas of concern from the collected social media data.

[1503] "Means for generating gift suggestions based on analysis results" refers to a system that uses APIs of online marketplaces and gift shops to create a list of related products based on extracted interests.

[1504] "Means to recognize user emotions and optimize gift candidates" refers to a system that uses cameras and microphones to analyze the user's facial expressions and tone of voice in real time and adjusts the ranking of gift candidates based on the analysis results.

[1505] "Means for suggesting generated gift candidates to a user" refers to a system that transmits the optimized gift candidate list to a user terminal and displays it through a user interface.

[1506] "Means for purchasing and shipping gift items selected by the user" refers to a system that provides an interface for users to enter payment and shipping information for the gift selected by the user, and processes the items to be properly delivered after the purchase is completed.

[1507] "Methods of using recipient account information linked by the user" refers to methods of linking social media account information and collecting necessary data with the user's permission.

[1508] This invention relates to a system that suggests the perfect gift based on information about the person a user wants to give a gift to and their activity data on social networking services (SNS). Furthermore, this system is combined with an emotion engine, which can recognize the user's emotions and improve the level of personalization of the gifts it suggests. This system is composed of multiple components, including a user terminal, a server, various APIs, and the emotion engine.

[1509] The user accesses the gift suggestion system using their device. The user enters basic information about the recipient (such as name, age, gender, and relationship), and selects the option to link the recipient's social media account. The user's device then sends this information to the server.

[1510] The server accesses the recipient's social media account information and uses APIs to obtain data such as the recipient's "liked" posts, shared articles, accounts they follow, and post content. After securing this data, the server analyzes the data using natural language processing (NLP) and image analysis algorithms to extract the recipient's interests.

[1511] Specifically, the server tokenizes the acquired text data and uses topic modeling (e.g., LDA) to identify the recipient's areas of interest. It also analyzes the posted images using image recognition algorithms (e.g., CNN) to extract interest in specific brands and products.

[1512] The server then uses the analysis results to retrieve relevant gift suggestions from online marketplaces or specific gift shop APIs. The server collects detailed information about each product (price, ratings, category, etc.) and extracts gift suggestions that best fit the recipient's profile, including filtering based on the user's budget and special requirements.

[1513] Furthermore, the present invention incorporates an emotion engine to recognize a user's emotions in real time and optimize gift suggestions based on those emotions. The emotion engine uses a camera and microphone to analyze a user's facial expressions, voice tone, and input content. The emotion engine includes facial expression recognition software that reads emotions from the user's facial expressions and voice analysis software that analyzes emotions from the user's voice tone. This allows the system to analyze the user's emotional state (e.g., joy, surprise, interest, etc.) while browsing gift suggestions and prioritize gift suggestions based on the user's emotions.

[1514] After the user selects a gift, the user's device provides an interface to support the purchase process (entering payment and delivery information). Once the purchase process is complete, the server queries the partner gift shop or marketplace API to check inventory and process delivery. It then sends a purchase completion notification and delivery information to the user and recipient, respectively.

[1515] Specific examples

[1516] A specific example is given below.

[1517] scenario:

[1518] A user wants to choose a birthday gift for a friend, and further optimizes the gift by taking emotions into account.

[1519] 1. User device: The user accesses the application and enters their friend's information (age, gender, relationship, etc.).

[1520] 2. User device: The user requests permission to access a friend's social media account.

[1521] 3. User terminal: After obtaining permission to use, provide account information to the system.

[1522] 4. Server: Collects friends' posting data about "cooking," "sports," and "travel" via SNS API.

[1523] 5. Server: Analyzes text and image data to extract friends' interests (e.g., sports equipment, kitchen gadgets, travel-related items).

[1524] 6. Server: Uses online marketplace APIs to retrieve relevant product details and generate optimal gift suggestions.

[1525] 7. Server: Filters gift suggestions based on the user's budget and special requirements.

[1526] 8. Server: Uses an emotion engine to analyze the emotional state of the user while browsing gift suggestions and optimize gift suggestions based on that emotion.

[1527] 9. Server: Sends the optimized gift candidate list to the user device.

[1528] 10. User device: Display suggested gift items to the user (e.g., jogging shoes, the latest blender, a compact travel bag).

[1529] 11. User device: The user selects the jogging shoes and completes the purchase.

[1530] 12. Server: Notify the user and recipient once the purchase and delivery process is complete.

[1531] Example prompts for generative AI models

[1532] Below are some examples of specific prompt sentences.

[1533] Prompt Sentence Examples

[1534] A user accesses a system that suggests the best gift for a friend's birthday based on social media data and the user's emotions. Explain all the steps the system takes, including the information the user provides to the system, data analysis, and emotion recognition.

[1535] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1536] Step 1: Enter your user information

[1537] Users simply enter basic information about the recipient (such as name, age, gender, and relationship) into the device.

[1538] Input is basic information provided by the user.

[1539] The output is basic information stored on the device.

[1540] Specific behavior: The user enters basic information into the form and clicks the "Next" button.

[1541] Step 2: Obtain and send recipient's social media account information

[1542] Users simply select the option to request permission to link to the other person's social media account.

[1543] The input is the user's social media account information and link permission of the other person.

[1544] The output is the social media account information and permissions sent to the server.

[1545] Specific operation: The user allows access to the social networking account and sends the link information.

[1546] Step 3: Collect social media data

[1547] The server uses an API to access the recipient's social media account and collect the necessary data.

[1548] The input is the SNS account information sent to the server.

[1549] The output is collected social media data (likes, shared posts, followed accounts, post content, etc.).

[1550] Specific operation: The server calls the SNS API and obtains the recipient's activity data.

[1551] Step 4: Analyze the data

[1552] The server analyzes the collected social media data using natural language processing (NLP) and image analysis algorithms.

[1553] The input is collected social media data.

[1554] The output is an analysis that indicates the recipient's interests.

[1555] What it does: The server tokenizes the text data, identifies regions of interest using topic modeling (e.g., LDA), and analyzes the images using image recognition algorithms (e.g., CNN).

[1556] Step 5: Generate gift suggestions

[1557] Based on the analysis results, the server retrieves relevant gift suggestions from APIs of online marketplaces and gift shops.

[1558] Inputs are the analysis results and the user's budget and special requirements.

[1559] The output is a generated list of gift suggestions.

[1560] Specific operation: The server calls the product's API to obtain detailed information such as price, rating, category, etc.

[1561] Step 6: Emotion Engine in Action

[1562] The device uses a camera and microphone to collect the user's facial expressions and voice tone.

[1563] The input is the user's facial expression data and voice data.

[1564] The output is the analyzed emotion data.

[1565] How it works: The device uses facial recognition and voice analysis software to analyze emotions.

[1566] Step 7: Optimize and display gift ideas

[1567] The server prioritizes gift suggestions based on the user's emotional data.

[1568] The inputs are emotion data and a gift candidate list.

[1569] The output is an optimized gift suggestion list.

[1570] Specific operation: The server adjusts the priority of gift candidates based on the emotional data and sends the list to the user's device.

[1571] Step 8: Gift Selection and Checkout

[1572] Users simply select the most suitable item from the displayed gift options.

[1573] The input is an optimized gift suggestion list.

[1574] The output is the selected gift item.

[1575] What happens: The user adds the selected gift item to their cart and begins the checkout process.

[1576] Step 9: Purchase completion and notification

[1577] The server queries partner gift shops and marketplace APIs to check inventory and process shipping.

[1578] The input is the selected gift item and shipping information.

[1579] The output is a confirmation of purchase completion and shipping information.

[1580] What happens: The server sends a notification to the user and recipient once the purchase is complete.

[1581] (Application example 2)

[1582] 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."

[1583] Conventional gift suggestion systems suggest gifts by taking into account the recipient's information and social media data, but because they are unable to consider the user's emotions, it is difficult to suggest the optimal gift that is in line with the user's feelings. Furthermore, there are cases where the suggested gift does not perfectly match the recipient's interests. Therefore, there was a need for a system that could help users select a gift that satisfies them.

[1584] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting information provided by a user, a means for acquiring data from the recipient's social networking service, a means for analyzing the acquired data and extracting the recipient's interests, a means for generating gift candidates based on the analysis results, a means for suggesting the generated gift candidates to the user, and a means for recognizing the user's emotions in real time and optimizing the suggested gift candidates. This makes it possible to suggest optimal gifts based on the recipient's interests while taking the user's emotions into consideration.

[1585] The "means for inputting information provided by the user" refers to an input device and software that allows the user to input basic information about the recipient, budget, etc.

[1586] "Means for obtaining data from the recipient's social networking service" refers to the means of communication and software for accessing the recipient's social networking account information and obtaining data such as posts, likes, and shared articles via API.

[1587] "Means for analyzing acquired data and extracting the recipient's interests" refers to hardware and software that uses natural language processing and image analysis algorithms to analyze acquired SNS data and identify the recipient's areas of interest.

[1588] The "means for generating gift candidates based on the analysis results" refers to software that obtains related product information from the APIs of online marketplaces and gift shops based on the analyzed interests and generates gift candidates.

[1589] The "means for suggesting generated gift candidates to the user" refers to a display device and software for presenting the generated multiple gift candidates to the user and assisting in the selection.

[1590] "Means for recognizing a user's emotions in real time and optimizing suggested gift candidates" refers to hardware and software that uses a camera and microphone to analyze emotions from a user's facial expressions and tone of voice, and optimizes the prioritization of gift candidates based on the user's emotions.

[1591] This invention is realized by constructing a gift suggestion system using a user terminal and a server. This system includes means for inputting information provided by a user, means for acquiring data from the recipient's social networking service, means for analyzing the acquired data and extracting the recipient's interests, means for generating gift candidates based on the analysis results, means for suggesting the generated gift candidates to the user, and means for recognizing the user's emotions in real time and optimizing the suggested gift candidates.

[1592] First, the user device provides an input device and software that allows the user to input basic information about the recipient, their budget, etc. This input information is sent to the server. Meanwhile, the recipient's social media account information is also linked to the user, and the server obtains the recipient's posts, likes, shared articles, etc. through the social media API. The obtained data is then analyzed on the server using natural language processing tools (e.g., TextBlob) and image analysis algorithms (e.g., CNN) to extract the recipient's interests and concerns.

[1593] Based on the analysis results, the server retrieves relevant gift suggestions from online marketplace APIs and gift shop APIs, and obtains detailed information (price, rating, category, etc.). This generates gift suggestions that take into account the user's budget and special requirements. Furthermore, it uses an emotion engine (e.g., FER) to recognize the user's real-time emotions through the camera and microphone on the user's device. Based on this, the priority of gift suggestions is optimized and suggested to the user.

[1594] Specifically, the server begins with a step in which a user accesses the application and enters the recipient's basic information and social media account. For example, suppose a user named "Yamada Hanako" wants to choose a gift for a "friend (35 years old, male)." The user links her "Instagram account," and the server obtains the social media data. Analysis reveals that she is interested in "cooking," "sports," and "travel," and generates gift suggestions based on that. After that, the camera determines that Yamada Hanako's emotion is "joy," and sports and travel-related goods are prioritized as suggestions.

[1595] Example prompts to input to the generative AI model:

[1596] "Please enter the name and social media account of the person you would like to give the gift to:

[1597] Name: Yamada Hanako

[1598] Social Media Account: example_user

[1599] Next, enter your budget (e.g., 5000 yen):

[1600] Budget: 5,000 yen

[1601] Turn on the camera and start emotion recognition.

[1602] ...

[1603] We're optimizing gift suggestions...

[1604] Perfect gift idea list:

[1605] 1. Jogging shoes

[1606] 2. Modern Blender

[1607] 3. Compact travel bag

[1608] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1609] Step 1:

[1610] The user enters the basic information and social media account information of the person they want to give the gift to.

[1611] Input: Name, age, gender, relationship, SNS account information

[1612] Output: The acquired information is sent from the device to the server.

[1613] Specific operation: When a user enters the required information into the input form on the terminal and clicks the send button, the terminal sends this information to the server.

[1614] Step 2:

[1615] The server accesses the recipient's SNS account and obtains the recipient's posted data, etc., via the SNS API.

[1616] Input: Recipient's SNS account information

[1617] Output: Post data of recipients, such as likes and shared posts, obtained from the SNS API

[1618] What it does: The server sends an API request to the linked social media account and receives data from the social media platform in response.

[1619] Step 3:

[1620] The server analyzes the acquired SNS data using natural language processing and image analysis algorithms to extract the recipient's interests and concerns.

[1621] Input: SNS data (text and images)

[1622] Output: A list of keywords related to the recipient's interests

[1623] How it works: The server uses TextBlob to analyze text and topic modeling to identify areas of interest, and uses CNN to analyze image data and extract interest in specific brands and products.

[1624] Step 4:

[1625] The server retrieves gift suggestions from the online marketplace API or gift shop API based on the analysis results.

[1626] Input: List of keywords of interest

[1627] Output: A list of related gift ideas and detailed information about each item

[1628] Specific operation: The server sends a request including keywords to the marketplace API and receives related product information in response.

[1629] Step 5:

[1630] The server filters gift suggestions, taking into account the user's budget and special requirements.

[1631] Input: Gift idea list, user budget information, special requirements

[1632] Output: A filtered list of gift ideas

[1633] What happens: The server checks the details of each product and selects the appropriate product based on the user's budget and requirements.

[1634] Step 6:

[1635] The terminal uses the user's camera and microphone to recognize the user's emotions in real time.

[1636] Input: User's facial and voice data

[1637] Output: User's emotional state (e.g., happy, surprised, etc.)

[1638] Specific operation: The device collects data in real time from the camera and microphone and analyzes the data using FER and voice analysis software.

[1639] Step 7:

[1640] The server optimizes the prioritization of gift candidates based on the user's emotional state.

[1641] Input: A filtered list of gift ideas, the user's emotional state

[1642] Output: Optimized list of gift ideas

[1643] Specific operation: The server takes into account the user's emotions and prioritizes placing the most suitable gifts at the top of the list.

[1644] Step 8:

[1645] The terminal displays the optimized gift candidate list to the user, and the user selects a gift.

[1646] Input: A list of optimized gift ideas

[1647] Output: Gift items selected by the user

[1648] Specific operation: The device displays a list of gift options on the screen, and the user selects the desired item.

[1649] Step 9:

[1650] The server processes the purchase and delivery of the selected gift item.

[1651] Input: Gift items selected by user, payment information, shipping information

[1652] Output: Purchase confirmation message, delivery confirmation message

[1653] Specific operation: The server accesses the marketplace API to complete the purchase, confirms the shipping information, and notifies the user and recipient.

[1654] 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.

[1655] 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.

[1656] 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.

[1657] 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.

[1658] 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.

[1659] 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.

[1660] 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).

[1661] 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.

[1662] 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."

[1663] 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.

[1664] 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).

[1665] 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.

[1666] 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.

[1667] 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.

[1668] 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.

[1669] 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.

[1670] 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.

[1671] 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.

[1672] 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.

[1673] 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.

[1674] 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.

[1675] The following is further disclosed regarding the above embodiment.

[1676] (Claim 1)

[1677] a means for inputting user-supplied information;

[1678] means for obtaining data from the recipient's social networking service;

[1679] A means for analyzing the acquired data and extracting the recipient's interests and concerns;

[1680] means for generating gift suggestions based on the analysis results;

[1681] means for suggesting the generated gift candidates to a user;

[1682] A system including:

[1683] (Claim 2)

[1684] 10. The system of claim 1, further comprising means for arranging for the purchase and delivery of the gift item selected by the user.

[1685] (Claim 3)

[1686] 10. The system of claim 1, wherein the means for obtaining data from a social networking service comprises means for utilizing account information of the recipient linked by the user.

[1687] "Example 1"

[1688] (Claim 1)

[1689] a means for inputting user-supplied information;

[1690] means for obtaining data from the recipient's social networking service;

[1691] A means for analyzing the acquired data and extracting recipient interests;

[1692] a means for analyzing the data using natural language processing and image analysis algorithms;

[1693] A means for retrieving relevant gift suggestions from an online marketplace or a database of a particular gift shop based on the analysis results;

[1694] A way for users to filter gift ideas based on their budget or special requirements;

[1695] A means for suggesting the generated gift candidates to a user;

[1696] A system including:

[1697] (Claim 2)

[1698] 10. The system of claim 1, further comprising means for arranging for the purchase and delivery of the gift item selected by the user.

[1699] (Claim 3)

[1700] 10. The system of claim 1, wherein the means for obtaining data from a social networking service comprises means for utilizing account information of recipients linked by the user.

[1701] "Application Example 1"

[1702] (Claim 1)

[1703] a means for inputting user-supplied information;

[1704] means for obtaining data from the recipient's social networking service;

[1705] A means for analyzing the acquired data and extracting the recipient's interests and concerns;

[1706] means for generating gift suggestions based on the analysis results;

[1707] means for suggesting the generated gift candidates to a user;

[1708] A means to display detailed information (price, rating, category, etc.) of the generated gift suggestions;

[1709] A system including:

[1710] (Claim 2)

[1711] 10. The system of claim 1, further comprising means for arranging for the purchase and delivery of the gift item selected by the user.

[1712] (Claim 3)

[1713] 10. The system of claim 1, wherein the means for obtaining data from a social networking service comprises means for utilizing account information of the recipient linked by the user.

[1714] "Example 2: Combining Emotion Engines"

[1715] (Claim 1)

[1716] a means for inputting user-supplied information;

[1717] means for obtaining data from the recipient's social networking service;

[1718] A means for analyzing the acquired data and extracting the recipient's interests and concerns;

[1719] means for generating gift suggestions based on the analysis results;

[1720] A means to recognize user emotions and optimize gift suggestions;

[1721] means for suggesting the generated gift candidates to a user;

[1722] A system including:

[1723] (Claim 2)

[1724] 10. The system of claim 1, further comprising means for arranging for the purchase and delivery of the gift item selected by the user.

[1725] (Claim 3)

[1726] 10. The system of claim 1, wherein the means for obtaining data from a social networking service comprises means for utilizing account information of the recipient linked by the user.

[1727] "Application example 2 when combining emotion engines"

[1728] (Claim 1)

[1729] a means for inputting user-supplied information;

[1730] means for obtaining data from the recipient's social networking service;

[1731] A means for analyzing the acquired data and extracting the recipient's interests and concerns;

[1732] means for generating gift suggestions based on the analysis results;

[1733] means for suggesting the generated gift candidates to a user;

[1734] A means to recognize user emotions in real time and optimize gift suggestions;

[1735] A system including:

[1736] (Claim 2)

[1737] 10. The system of claim 1, further comprising means for arranging for the purchase and delivery of the gift item selected by the user.

[1738] (Claim 3)

[1739] 10. The system of claim 1, wherein the means for obtaining data from a social networking service comprises means for utilizing account information of the recipient linked by the user. [Explanation of symbols]

[1740] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting user-supplied information; means for obtaining data from the recipient's social networking service; A means for analyzing the acquired data and extracting the recipient's interests and concerns; means for generating gift suggestions based on the analysis results; means for suggesting the generated gift candidates to a user; A system including:

2. 10. The system of claim 1, further comprising means for arranging for the purchase and delivery of a user-selected gift item.

3. The system of claim 1 , wherein the means for obtaining data from a social networking service comprises means for utilizing account information of recipients linked by the user.

Images