System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a question from a user; means for analyzing the question to extract topics and keywords; means for collecting information related to the question from the Internet; means for selecting an advertisement related to the question; means for combining the collected information and the selected advertisement to generate an answer to the user; and means for transmitting the generated answer and advertisement 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] Conventional generative AI systems were unable to incorporate advertising when providing answers to user questions, resulting in missed monetization opportunities. Furthermore, many users were reluctant to pay high usage fees to use generative AI. Therefore, a method for effectively monetizing generative AI while reducing the user's financial burden was needed. [Means for solving the problem]

[0005] The present invention solves the above problems by the following means. First, a question from a user is received, and the question is analyzed to extract topics and keywords. Next, information related to the question is collected from the Internet. Next, advertisements related to the question are selected, and the collected information is combined with the selected advertisements to generate an answer for the user. By sending the generated answer and advertisements to the user, the user can obtain information for free or at a reduced cost, and at the same time, the provider can earn revenue by viewing the advertisements.

[0006] The "means for receiving a question from a user" is a component that has the function of obtaining a question entered by a user and passing it to the next processing step for analysis.

[0007] "Means for analyzing questions and extracting topics and keywords" means algorithms or software modules that recognize the content of received questions and identify and extract important topics and keywords.

[0008] "Means for collecting information related to the question from the Internet" refers to a system that has the function of collecting information related to the question from the Internet using a web crawl engine or search engine API.

[0009] The "means for selecting ads relevant to a question" is a component that uses algorithms and databases to select the most relevant ads based on the user's question.

[0010] The "means for combining the collected information with the selected advertisements to generate a response for the user" is an algorithm or software module that integrates the collected information with the selected advertisements to generate a final response to be provided to the user.

[0011] The "means for transmitting the generated answers and advertisements to the user" refers to a communication module or system for transmitting the generated final answers and advertisements to the user's terminal.

[0012] An "interface" is a point of contact with a user, such as a graphical user interface (GUI) or web page, through which the user can enter a question and view generated answers and advertisements. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The present invention relates to a generative AI system that incorporates advertisements into answers to questions from users and provides the answers to the users. Hereinafter, an embodiment of this system will be described in detail.

[0035] System Overview

[0036] The system consists of the following elements:

[0037] 1. Means of receiving questions from users

[0038] 2. A method for analyzing questions and extracting topics and keywords

[0039] 3. How to gather information related to your question from the Internet

[0040] 4. How to select ads relevant to your question

[0041] 5. A means of combining collected information with selected ads to generate answers for users.

[0042] 6. Means for sending generated answers and advertisements to users

[0043] Program processing

[0044] First, the user inputs a question into the interface of the generative AI system. For example, they input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0045] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0046] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0047] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0048] The server combines the collected information with the selected advertisement to generate an answer to be provided to the user. Care is taken to ensure that the advertisement is inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is paired.

[0049] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the user's interface, allowing the user to get a useful answer to their question and view relevant advertisements.

[0050] Specific examples

[0051] Consider what happens when a user asks, "What's the latest smartphone recommendation?"

[0052] The user enters a question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to collect related information from the Internet, retrieving the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from the advertising management system. By combining the collected information with the selected advertisement, the server generates a response that incorporates an advertisement such as "X brand model Y is highly rated as the latest smartphone. Its features are..." in response to a question such as, "X brand model Y is now 20% off!" Finally, the server sends the response and advertisement to the user's device, where the user can view them on the interface.

[0053] As described above, the generative AI system according to the present invention is capable of providing free or reduced-cost information to users while effectively delivering advertisements to advertisers.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] The user enters a question into the interface of the generative AI system and presses the send button. For example, the user enters the question, "What is your recommendation for the latest smartphone?"

[0057] Step 2:

[0058] The terminal receives the user's question and sends it to the server using a communication protocol such as an HTTP request.

[0059] Step 3:

[0060] The server receives the question sent by the user and passes the received question as text data to the analysis engine.

[0061] Step 4:

[0062] The server uses a text analysis engine to analyze the content of the question, extracting key keywords such as "smartphone," "latest," and "recommended" to identify the topic of the question.

[0063] Step 5:

[0064] The server launches a web crawling engine to gather information related to the question from the Internet, such as the latest smartphone reviews and product information, selecting only reliable sources.

[0065] Step 6:

[0066] The server accesses the ad management system and selects the most appropriate ad based on the query, for example, selecting an ad campaign related to the latest smartphones, using targeting information specified by the advertiser and past user behavior data.

[0067] Step 7:

[0068] The server combines the collected information with the selected advertisement to generate an answer to be provided to the user. At this time, the advertisement is adjusted so that it is inserted naturally into the context of the answer. For example, in response to the question, "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is combined.

[0069] Step 8:

[0070] The server then sends the generated response and advertisement to the user's device, usually using a communication protocol such as an HTTP response.

[0071] Step 9:

[0072] The terminal receives the answers and advertisements sent from the server and displays them on the user's interface, allowing the user to check them and view the contents of the answers and advertisements.

[0073] Through these steps, the system effectively provides useful answers to users' questions and relevant advertisements.

[0074] Example 1

[0075] 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."

[0076] Conventional information provision systems often lack the accuracy and reliability of answers to user questions. Furthermore, it is difficult to naturally incorporate advertisements into answers, which can detract from the user experience. Furthermore, it is difficult to select appropriate advertisements based on the content of the question, which reduces the effectiveness of advertising.

[0077] 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.

[0078] In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting main keywords and topics, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, and means for transmitting the generated answer and advertisements to the user. This makes it possible to provide highly accurate and reliable answers to user questions and to provide effective information that naturally incorporates advertisements.

[0079] A "user" is a person who uses the system to input a question.

[0080] The "means for receiving a question" is a function that allows the server to obtain a question entered by a user.

[0081] "Means for analyzing questions to extract key keywords and topics" refers to a function that analyzes questions to identify important phrases and themes.

[0082] "Means of collecting information related to the question from the Internet" is a function that collects data related to the question from the web.

[0083] "Means for selecting advertisements" is a function that selects appropriate advertisements based on the content of the question.

[0084] The "means for generating an answer by combining information and advertisements" is a function for generating an answer to be provided to a user using collected information and selected advertisements.

[0085] The "means for transmitting the generated answer and advertisement to the user" is a function for transmitting the generated answer and advertisement to the user's terminal.

[0086] "Means for extracting reliable information" is the function of selecting trustworthy data from the collected information.

[0087] "Means of naturally inserting into the context of the answer" refers to the ability to seamlessly incorporate advertisements into the content of the answer.

[0088] MODE FOR CARRYING OUT THE INVENTION

[0089] The present invention relates to a generation AI system that incorporates advertisements into answers to user questions and provides them to the user. To implement this system, a terminal to which the user connects and a server that analyzes the questions and generates answers are required. A specific embodiment of this system is described in detail below.

[0090] Hardware and software used

[0091] Server: This is the main component that receives questions, analyzes them, collects information, selects ads, generates answers, and sends them. The following software is installed on the server:

[0092] Text Analysis Engine: Analyzes the text of the question and extracts key keywords and topics. Uses Natural Language Processing (NLP) techniques.

[0093] Web Crawl Engine: Automatically crawls specific websites to collect reliable information on the Internet.

[0094] Ad Management System: Targets and selects ads.

[0095] Generative AI model: Generates answers to provide to users based on collected information and selected ads.

[0096] User device: A device that inputs questions and receives and displays answers, such as a PC, smartphone, or tablet, allowing users to interact with the system.

[0097] Explaining program processing in natural language

[0098] First, the user inputs a question into the interface of the generative AI system. For example, they input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0099] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0100] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0101] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0102] The server combines the collected information with the selected advertisements to generate answers to be provided to the user. It uses a generative AI model to create natural sentences and ensures that the advertisements are inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", it combines an advertisement saying "X brand model Y is now 20% off!"

[0103] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the user's interface, allowing the user to get a useful answer to their question and view relevant advertisements.

[0104] Examples and prompts

[0105] As a concrete example, consider the case where a user asks, "What's the best new smartphone?" The user enters the question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to gather relevant information from the Internet, including the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from an advertising management system. By combining the collected information with the selected advertisement, the server generates a response that incorporates an advertisement, such as "Brand X's Model Y is highly rated as the latest smartphone. Its features are..." in response to a question such as, "Brand X's Model Y is currently 20% off!" Finally, the server sends the response and advertisement to the user's device, where the user can view them through the interface.

[0106] As described above, the generative AI system according to the present invention is a system that integrates the provision of highly accurate and reliable information with effective advertisement delivery.

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

[0108] Step 1:

[0109] The user inputs a question into the interface of the generative AI system. As a concrete example, let's assume the user inputs "What's your recommendation for the latest smartphone?" The device then sends this question to the server. The input is the user's question text, and the output is an HTTP request sent to the server.

[0110] Step 2:

[0111] The server receives questions submitted by users. It passes the received questions to a text analysis engine. The text analysis engine analyzes the question text and extracts key keywords and topics. This analysis uses natural language processing (NLP) techniques. The input is the user's question text, and the output is the extracted keywords and topics.

[0112] Step 3:

[0113] The server launches a web crawling engine to collect relevant information from the Internet. Specifically, it crawls news sites, blogs, review sites, etc. to retrieve articles and reviews about the latest smartphones and recommended models. The crawling engine scrapes the page content from each site and stores reliable information in a database. The input is the extracted keywords, and the output is the collected related information.

[0114] Step 4:

[0115] The server simultaneously accesses the ad management system and selects the most appropriate ad for the query. Specifically, the server searches for relevant ad campaigns based on keywords such as "smartphone" or "latest model." This is done using targeting information provided by the advertiser and past user behavior data. The input is the extracted keywords and topics, and the output is the selected ad.

[0116] Step 5:

[0117] The server combines the collected information with the selected advertisements to generate an answer to be provided to the user. A generative AI model is used to create the optimal sentence for the user's question. This sentence incorporates the collected reviews and product information, and is designed to insert the selected advertisements naturally (without any sense of incongruity). The input is the collected information and the selected advertisements, and the output is the generated answer.

[0118] Step 6:

[0119] The server sends the generated answers and advertisements to the user's terminal. Specifically, it sends the generated text data back to the user's terminal in the form of an HTTP response. The terminal receives this and displays it on the user's interface. The input is the generated answers and advertisements, and the output is the text displayed on the user's interface.

[0120] Step 7:

[0121] The user checks the answers and advertisements displayed on the device. Specifically, they read the answers on the interface and view the related advertisements. This allows the user to obtain useful information about the question and simultaneously view selected advertisements. The input is the displayed answers and advertisements, and the output is the user's browsing behavior.

[0122] (Application example 1)

[0123] 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."

[0124] Conventional generative AI systems have had difficulty gathering accurate information and inserting advertisements naturally when generating answers to user questions and generating advertisements. Furthermore, there has been no interactive answering system that combines visual and audio information for smart devices with the ability to display information in the user's field of view in real time. As a result, improving the user experience has been a challenge.

[0125] 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.

[0126] In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, and means for transmitting the generated answer and advertisement to the user terminal and displaying them on the smart device.

[0127] This will enable accurate information and relevant advertisements to be provided to users in real time, and enable interactive information provision through visual and audio, improving the user experience.

[0128] The "means for receiving a question from a user" refers to a technical means for obtaining a question entered by a user via voice or text through a digital device.

[0129] The "means for analyzing the question and extracting topics and keywords" refers to a technical means for analyzing the received question using natural language processing technology and identifying the main topics and related keywords.

[0130] "Means for collecting information related to the question from the Internet" means technical means for searching and collecting information related to the question from reliable websites and databases on the Internet.

[0131] The "means for selecting advertisements relevant to the question" refers to a technical means for selecting advertisements that are highly relevant based on the content of the question and displaying them to the user.

[0132] "Means for combining the collected information with the selected advertisements to generate a response for the user" refers to technical means for integrating the collected information with the selected advertisements to generate a response for the user in a natural format.

[0133] "Means for transmitting the generated answers and advertisements to a user terminal and displaying them on a smart device" refers to technical means for transmitting the generated answers and advertisements to a user's digital device and displaying them on a smart device such as a smartphone or smart glasses.

[0134] The present invention relates to a generative AI system that incorporates advertisements into answers to questions posed by users and displays the answers and advertisements on smart devices. The following describes in detail the embodiments of the present invention.

[0135] System Configuration

[0136] The system consists of the following main components:

[0137] 1. Means of receiving questions from users

[0138] 2. Means for analyzing the question and extracting topics and keywords

[0139] 3. How to gather information related to your question from the Internet

[0140] 4. Means for selecting advertisements relevant to the question

[0141] 5. Means for combining the collected information with the selected advertisement to generate a response for the user.

[0142] 6. Means for transmitting the generated answers and advertisements to the user terminal and displaying them on the smart device

[0143] Hardware and Software Use

[0144] Hardware:

[0145] Smart glasses: equipped with cameras and audio capture capabilities

[0146] software:

[0147] Google Cloud Vision API

[0148] Google Speech Recognition API

[0149] OpenAI GPT-3 API

[0150] Data processing and calculation

[0151] 1. Receiving and parsing questions:

[0152] The system captures questions spoken by users into the smart glasses as audio and converts them into text using the Google Speech Recognition API, recognizes objects in the user's line of sight using the Google Cloud Vision API, and analyzes the question along with extracted topics and keywords.

[0153] 2. Information and Advertising Collection:

[0154] The server searches the Internet to gather reliable information related to the question. The web crawling engine crawls news sites, blogs, review sites, etc. to obtain the latest information. Meanwhile, it accesses the ad management system to select the most suitable ad for the question. This ad selection takes into account the question's topic and keywords, past user behavior data, etc.

[0155] 3. Generate and send the answer:

[0156] The collected information is integrated with the selected advertisements to generate answers for the user in a natural format. This process is performed using the OpenAI GPT-3 API. The generated answers and advertisements are sent to the user's device and displayed on the smart glasses.

[0157] Specific examples

[0158] A user is looking at the latest smartphone exhibit and asks, "What are the features of this smartphone?"

[0159] The smartphone is recognized from the captured image, and the user's question is converted into text using voice recognition.

[0160] Based on the question and object recognition results, prompts are sent to GPT-3 to generate answers and relevant ads.

[0161] Example prompt sentence:

[0162] Q: What are the features of the latest smartphones?

[0163] Object: Smartphone

[0164] Please provide your answer and relevant ads:

[0165] This improvement allows users to obtain quick and accurate information through questions and answers, and at the same time, to receive relevant advertisements in a natural way.

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

[0167] Step 1:

[0168] User question input

[0169] How it works: A user speaks a question into the smart glasses, for example, "What are the features of this smartphone?"

[0170] Input: User's voice data

[0171] Output: Captured audio data

[0172] Step 2:

[0173] Speech-to-text conversion

[0174] How it works: Converts user voice data into text using the Google Speech Recognition API.

[0175] Input: Captured audio data

[0176] Output: Texted question (e.g., "What are the features of this smartphone?")

[0177] Step 3:

[0178] Eye tracking and object recognition

[0179] How it works: The smart glasses' camera is used to capture objects in the user's line of sight, and the object is recognized using the Google Cloud Vision API.

[0180] Input: Image data captured by the camera

[0181] Output: Recognized object (e.g. "smartphone")

[0182] Step 4:

[0183] Parsing the query and object recognition results

[0184] How it works: The server analyzes the textual questions and object recognition results to extract key topics and keywords.

[0185] Input: Texted question, recognized object

[0186] Output: Extracted topics and keywords (e.g., "smartphone" and "features")

[0187] Step 5:

[0188] Gathering relevant information

[0189] How it works: The server searches the internet to gather reliable information related to your question, grabbing the data it needs from news sites, blogs, review sites, etc.

[0190] Input: Extracted topics and keywords

[0191] Output: Collected relevant information (e.g., reviews of the latest smartphones)

[0192] Step 6:

[0193] Selection of relevant advertisements

[0194] Operation: The server accesses the ad management system and selects relevant ads based on topics and keywords.

[0195] Input: Extracted topics and keywords

[0196] Output: Selected advertisements (e.g. smartphone discount campaigns)

[0197] Step 7:

[0198] Answer and Ad Generation

[0199] How it works: The server combines the collected information with the selected ads to generate a natural-looking answer for the user. This process is performed using the OpenAI GPT-3 API.

[0200] Input: Collected relevant information, selected advertisements

[0201] Output: Generated answer and advertisement (e.g., "X brand's model Y is highly rated as the latest smartphone. Features include... 20% off now!")

[0202] Step 8:

[0203] Sending and displaying responses and advertisements

[0204] How it works: The server sends the generated answers and advertisements to the user's smart glasses and displays them for the user to see in real time.

[0205] Input: Generated answers and advertisements

[0206] Output: Answers and advertisements displayed on the smart glasses (e.g., users can view them through the glasses)

[0207] 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.

[0208] The present invention relates to a generative AI system that incorporates advertisements into answers to user questions and provides them to the user. Furthermore, the present invention provides a system that combines an emotion engine that recognizes the user's emotions and adjusts the answers and advertisements based on the emotions. Below, an embodiment of this system will be described in detail.

[0209] System Overview

[0210] The system consists of the following elements:

[0211] 1. Means of receiving questions from users

[0212] 2. A means of parsing questions to extract topics and keywords

[0213] 3. How to gather information related to your question from the Internet

[0214] 4. How to select ads relevant to your question

[0215] 5. A means of combining collected information with selected ads to generate answers for users.

[0216] 6. Means for sending generated answers and advertisements to users

[0217] 7. Emotion engine that analyzes and recognizes user emotions

[0218] 8. A way to tailor responses and ads based on an emotion engine

[0219] Program processing

[0220] First, the user inputs a question into the interface of the generative AI system. For example, they might input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0221] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0222] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0223] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0224] The server then combines the collected information with the selected advertisement to generate an answer to be provided to the user. Care is taken to ensure that the advertisement is inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is paired.

[0225] Furthermore, the server uses an emotion engine to analyze the user's emotions. For example, it recognizes the user's emotions from the context when the user enters a question and from past interaction data. Based on the emotion engine, it adjusts the tone and content of answers and advertisements. For example, if the user is emotionally exhausted, it provides answers and advertisements that are more relaxing.

[0226] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the interface, allowing the user to view the answer and advertisement content.

[0227] Specific examples

[0228] Consider what happens when a user asks, "What's the latest smartphone recommendation?"

[0229] The user enters a question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to collect related information from the Internet, retrieving the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from the advertising management system. By combining the collected information with the selected advertisements, for example, in response to a question such as "X brand model Y is highly rated as the latest smartphone. Its features are...", the server generates a response incorporating an advertisement such as "X brand model Y is now 20% off!"

[0230] Furthermore, if the user's emotion is "excited," the content will be adjusted to emphasize that reaction. Or, if the user is recognized as "tired," words or advertisements with a relaxing effect will be selected.

[0231] Finally, the server sends this response and the advertisement to the user's terminal, where the user confirms it in the interface.

[0232] As described above, the generative AI system of the present invention provides users with free or reduced-cost information while effectively delivering ads to advertisers. It also provides a more personalized experience by adjusting responses and ads based on the user's emotions.

[0233] The processing flow will be explained below.

[0234] Step 1:

[0235] The user enters a question into the interface of the generative AI system and presses the send button. For example, the user enters the question, "What is your recommendation for the latest smartphone?"

[0236] Step 2:

[0237] The terminal receives the user's question and sends it to the server using a communication protocol such as an HTTP request.

[0238] Step 3:

[0239] The server receives the question sent by the user and passes the received question as text data to the analysis engine.

[0240] Step 4:

[0241] The server uses a text analysis engine to analyze the content of the question, extracting key keywords such as "smartphone," "latest," and "recommended" to identify the topic of the question.

[0242] Step 5:

[0243] The server uses an emotion engine to analyze emotions from the user's input text and past behavioral data. Based on the emotion analysis algorithm, the server identifies the user's emotional state (e.g., joy, excitement, sadness, fatigue).

[0244] Step 6:

[0245] The server launches a web crawling engine to gather information related to the question from the Internet, such as the latest smartphone reviews and product information, selecting only reliable sources.

[0246] Step 7:

[0247] The server accesses the ad management system and selects the most appropriate ad based on the query, for example, selecting an ad campaign related to the latest smartphones, using targeting information specified by the advertiser and past user behavior data.

[0248] Step 8:

[0249] The server combines the collected information with the selected advertisements to generate a response to be presented to the user. The tone of the response and the content of the advertisement are adjusted based on the user's emotions. For example, if the user is "excited," the server uses expressions that enhance excitement and makes the advertisement relevant to that emotion.

[0250] Step 9:

[0251] The server then sends the generated response and advertisement to the user's device, usually using a communication protocol such as an HTTP response.

[0252] Step 10:

[0253] The device receives the answers and advertisements sent from the server and displays them on the user's interface in a format that takes into consideration the user's feelings. The user can confirm the display and view the content of the answers and advertisements.

[0254] Through these steps, the system effectively provides useful answers to users' questions and relevant advertisements, while also providing a personalized experience that responds to the user's emotional state.

[0255] Example 2

[0256] 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."

[0257] Conventional question-answering systems are limited to providing answers to user questions and lack a way to effectively combine them with advertisements. Furthermore, they lack the ability to analyze user sentiment and tailor answers and advertisements accordingly, preventing an improved user experience. Therefore, a system that provides personalized advertisements and answers tailored to user needs was needed.

[0258] 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.

[0259] In this invention, the server includes means for receiving a question from a user, means for analyzing the question to extract topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for generating an answer for the user by combining the collected information and the selected advertisements, means for transmitting the generated answer and advertisement to the user, means for analyzing and recognizing user emotions, and means for adjusting the answer and advertisement based on the emotion analysis, thereby making it possible to provide personalized answers and advertisements according to the user's needs and emotions.

[0260] The "means for receiving questions from users" is an interface that allows the server to receive questions input by users via their terminals.

[0261] The "means for analyzing the question and extracting topics and keywords" refers to a system that analyzes the question received by the server using technology such as a text analysis engine and extracts the subject matter and important words of the question content.

[0262] "Means for collecting information related to the question from the Internet" refers to a system in which a server uses a web crawling engine or the like to search for and collect information related to the question from news sites, blogs, review sites, etc. on the Internet.

[0263] The "means for selecting an advertisement relevant to the question" refers to a process in which the server uses an advertisement management system to select an advertisement that is most suitable for the content of the question.

[0264] "Means for combining the collected information with the selected advertisements to generate a response for the user" refers to a technology for integrating the information collected by the server with the selected advertisements to generate a response for the user.

[0265] The "means for transmitting the generated answer and advertisement to the user" is a system for transmitting the answer and advertisement generated by the server to the user's terminal and displaying them on the user interface.

[0266] "Means for analyzing and recognizing user emotions" refers to technology that allows the server to analyze user input and past interaction data to recognize the user's current emotional state.

[0267] "Means for adjusting the answers and advertisements based on the sentiment analysis" refers to a process for personalizing the content and wording of answers and advertisements according to the emotional state of the user as recognized by the server.

[0268] The generative AI system of the present invention generates answers incorporating advertisements to user questions and provides personalized answers by analyzing the user's emotions. This system is composed of the following main components:

[0269] 1. User terminal: An interface is provided for users to input questions. For example, a device such as a smartphone or computer can be used.

[0270] 2. Server: Plays a central role in performing various processes and uses the following software and hardware:

[0271] Text analysis engine: Analyzes questions and extracts topics and keywords.

[0272] Web crawling engine: Collects information related to your question from the internet.

[0273] Advertisement management system: Selects the best advertisement for the question.

[0274] Emotion engine: Analyzes and recognizes user emotions.

[0275] Answer generation module: Generates answers by combining collected information with selected advertisements.

[0276] 3. Communication: Network communication is required to send and receive data between the user device and the server. This is achieved via an Internet connection.

[0277] Hardware and software used

[0278] User device: A personal computer, smartphone, tablet, etc. connected to the Internet.

[0279] Server: A physical or virtual server with high-performance computing resources, with the following software installed:

[0280] Text analysis engines: Libraries for natural language processing (e.g. NLTK, spaCy, etc.).

[0281] Web crawling engines: Tools for web scraping (e.g. Beautiful Soup, Scrapy, etc.).

[0282] Ad Management Systems: Ad databases and targeting algorithms (e.g., Google Ad Manager).

[0283] Emotion engine: An emotion analysis tool that uses facial recognition and text mining technology (e.g., IBM Watson, Microsoft Azure Emotion API, etc.).

[0284] Answer generation module: Utilizes generative AI models (e.g., GPT-3).

[0285] Specific examples

[0286] For example, consider a scenario in which a user inputs the question "What's the latest smartphone recommendation?" into a generative AI system.

[0287] 1. The user inputs a question into the interface, and the user terminal sends this input to the server.

[0288] 2. The server receives the question and uses a text analysis engine to extract the main keywords "smartphone" and "recommended."

[0289] 3. The server then launches a web crawling engine to gather reliable information about the latest smartphones from news sites and blogs across the Internet.

[0290] 4. At the same time, the server accesses the ad management system and selects relevant ads based on the collected keywords and user attributes. For example, it selects an ad for a 20% discount on model Y of brand X during a campaign.

[0291] 5. The server combines the collected information with the selected advertisement, and incorporates an advertisement that reads, "X brand model Y is highly rated as the latest smartphone. Its features are..." into the response, "X brand model Y is now 20% off!"

[0292] 6. The server uses the emotion engine to hypothesize the user's current emotional state. For example, it recognizes that the user is "excited" based on the speed at which the question is typed and past interactions.

[0293] 7. The server further adjusts the tone and content of the responses and ads based on sentiment analysis: if the user is "excited," it uses language that emphasizes that sentiment.

[0294] 8. Finally, the server sends the generated answer and advertisement to the user's terminal, where the user can view the content through the interface.

[0295] For example, the prompt is:

[0296] What's your recommendation for the latest smartphone?

[0297] In this way, the generative AI system of the present invention can provide personalized answers and advertisements that match the user's needs and emotions, thereby improving the user experience and maximizing the effectiveness of advertisements.

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

[0299] Step 1:

[0300] The user inputs a question into the interface. For example, the user inputs a question such as "What is the latest smartphone recommended?" The input question is stored on the device as string data.

[0301] Step 2:

[0302] The terminal sends the entered question to the server. The terminal uses a transmission protocol to send the question as a string of data to the server. The input is the user's question, and the output is the transfer of the question data to the server.

[0303] Step 3:

[0304] The server receives the question and passes it to the text analysis engine. The analysis engine receives the question that arrives at the server and extracts the main keywords and topics of the question. For example, keywords such as "smartphone" and "recommended" are extracted. The input is the user's question data, and the output is the extracted keywords and topics.

[0305] Step 4:

[0306] The server starts a web crawling engine to gather information related to the question from the Internet. It uses a search engine API to retrieve related news articles, review sites, blog posts, etc. For example, "latest smartphone review articles" or "product information." The input is the extracted keywords, and the output is the data of related web pages.

[0307] Step 5:

[0308] The server accesses the advertising management system and selects the advertisement that best suits the query. The server uses a targeting algorithm to select advertisements related to "smartphones" and "latest models" from the advertising database. For example, it selects a campaign advertisement such as "X brand Y model is now 20% off!" The input is the extracted keywords and user attribute data, and the output is the selected advertising information.

[0309] Step 6:

[0310] The server combines the collected information with the selected advertisement to generate an answer. The answer generation module uses text generation technology to create an answer based on the collected information and inserts the advertisement naturally. For example, to the question, "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is added. The input is the collected information and the selected advertisement, and the output is the generated answer.

[0311] Step 7:

[0312] The server uses an emotion engine to analyze the user's emotions. It determines the user's emotional state, such as whether they are "excited" or "tired," based on past interaction data and contextual analysis of input. The input is the user's past data and current question data, and the output is the user's emotional state information.

[0313] Step 8:

[0314] The server adjusts the tone and content of responses and advertisements based on emotion analysis. For example, if the user is recognized as "tired," the responses will be adjusted to be more relaxing, and advertisements will also be changed to have a similarly relaxing effect. The input is the user's emotional state information, and the output is the adjusted responses and advertisements.

[0315] Step 9:

[0316] The server sends the generated answers and advertisements to the user's terminal. The server sends this data to the terminal via the Internet, and the terminal receives it. The input is the generated answers and advertisements, and the output is the data transfer to the terminal.

[0317] Step 10:

[0318] The terminal displays the received information on the interface, and the user can confirm it. The user can see the provided answers and advertisement content on the interface. The input is the data sent from the server, and the output is the displayed answers and advertisements.

[0319] (Application example 2)

[0320] 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."

[0321] Conventional information provision systems have the problem that answers to user questions are uniform and not personalized to reflect the user's emotions or circumstances. Furthermore, when incorporating advertisements, it is difficult to insert them naturally into the context, which can detract from the user experience. Furthermore, the collected information may not always be reliable, raising concerns about a decline in user trust. To address these issues, technology is needed to tailor answers and advertisements based on the user's emotions and to provide reliable information.

[0322] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, means for sending the generated answer and advertisement to the user, means for analyzing and recognizing the user's emotions, and means for adjusting the answer and advertisement based on the emotion analysis. This makes it possible to provide personalized answers and advertisements according to the user's emotions.

[0323] The "means for receiving a question from a user" is an interface that allows the system to receive a question in text format entered by a user.

[0324] The "means for analyzing questions and extracting topics and keywords" is a function for analyzing user questions using natural language processing technology and identifying major topics and important words and phrases.

[0325] The "means for collecting information related to a question from the Internet" is a program for searching and acquiring information related to a user's question from data sources on the Internet.

[0326] The "means for selecting advertisements relevant to a question" is a function for selecting highly relevant advertisements from a database or advertising platform based on the content of a user's question.

[0327] The "means for combining collected information with selected advertisements to generate a response for the user" is a program that integrates the acquired information with advertisements and creates a response to be provided to the user.

[0328] The "means for transmitting the generated answers and advertisements to the user" is a communication function for delivering the answers and advertisements generated by the system to the user's terminal.

[0329] "Means for analyzing and recognizing user emotions" refers to technology that performs emotion analysis based on questions entered by the user and past data, and identifies the user's current emotional state.

[0330] The "means for adjusting answers and advertisements based on sentiment analysis" refers to an algorithm for changing the content and tone of answers and advertisements provided depending on the emotional state of the user.

[0331] The system that realizes this application combines answers to user questions with advertisements and tailors them based on emotions. The system consists of the following main hardware and software components:

[0332] 1. User Device:

[0333] The device, such as a smartphone or tablet, provides an interface for users to input questions, which are then sent to a server.

[0334] 2. Server:

[0335] It is a central system that runs a text analysis engine, web crawling engine, ad management system, generative AI system, sentiment engine, etc. The server integrates these functions and manages the process.

[0336] Specific software used includes natural language processing libraries (e.g., TextBlob), web crawling libraries (e.g., BeautifulSoup), and machine learning libraries (e.g., TensorFlow).

[0337] 3. Program processing flow:

[0338] When a user types a question, it is sent to the server, which first passes it through a text analysis engine to extract key keywords and topics.

[0339] Next, the web crawling engine gathers relevant information from the internet, gathering information from reliable data sources such as news sites, blogs, and review sites.

[0340] The server accesses the advertisement management system to select advertisements relevant to the query, using criteria including keywords in the query and past user behavior data.

[0341] The AI ​​system combines the collected information with the selected ads to generate answers, which are then adjusted to insert the ads naturally into the context.

[0342] The emotion engine analyzes the user's emotions and adjusts the responses and ads based on the emotions, for example, if the user is in a positive emotional state, it will choose positive ads, and if the user is in a negative emotional state, it will choose ads with a relaxing effect.

[0343] Finally, the generated answers and advertisements are sent to the user's terminal, where the user can view them.

[0344] Examples:

[0345] A user enters a question such as "What's the best new smartphone?" This question is sent to a server, where a text analysis engine extracts keywords such as "smartphone" and "recommended." A web crawling engine collects related review articles and product information, and an advertising management system selects an advertisement that reads, "20% off a new smartphone!" A generative AI system combines the collected information with the advertisement to generate an answer.

[0346] The emotion engine analyzes the user's emotions, and if the user's emotions are positive, the content of the advertisement is adjusted to "We'll also bring you some fun information!" The adjusted answer and advertisement are sent to the user's device, where the user can view them.

[0347] Example prompt sentence:

[0348] "A user asks, 'What's the best new smartphone?' Generate an answer to this question that includes information about the latest smartphones and relevant ads. Be especially positive in your answers and ads, and make the user feel good."

[0349] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0350] Step 1:

[0351] A user types a question into a device. When a user types a question into the device's interface, such as "What's the best new smartphone?", the question is sent to a server. The input is the user's question text, and the output is that this text is sent to the server.

[0352] Step 2:

[0353] The server receives the question and passes it to a text analysis engine. The text analysis engine analyzes the input question and extracts topics and keywords. For example, the keywords "latest smartphone" and "recommendations" are extracted. The input is the user's question text, and the output is the extracted keywords and topics.

[0354] Step 3:

[0355] Based on the extracted keywords, the server uses a web crawling engine to collect related information from the Internet, obtaining data from reliable sources such as news sites, blogs, and review sites. The input is the extracted keywords and topics, and the output is related information data.

[0356] Step 4:

[0357] The server uses an ad management system to select ads relevant to the query. The ad management system searches a database for appropriate ads based on the extracted keywords. For example, an ad for "20% off the latest smartphone" is selected. The input is the extracted keywords, topics, and past user behavior data, and the output is the selected ad.

[0358] Step 5:

[0359] The server combines the collected information with the selected advertisements and generates an answer using a generative AI system. The generative AI system generates text that naturally inserts advertisements into the context of the answer. For example, the generated answer might be, "The latest smartphone is model X, which has received high reviews. Plus, you can get it now for 20% off!" The input is the collected information and the selected advertisements, and the output is the answer text with the advertisements incorporated.

[0360] Step 6:

[0361] The server analyzes the user's input questions and past interaction data to analyze the user's emotions using an emotion engine. The emotion engine identifies the user's current emotional state. The input is the user's question text and past interaction data, and the output is the analyzed emotional state.

[0362] Step 7:

[0363] The server adjusts the content and tone of the answers and advertisements based on the emotional analysis. For example, if the user is in a positive emotional state, it provides positive words and emphasizes the advertisement. Conversely, if the user is in a negative emotional state, it changes the expressions and content to make the user feel more relaxed. The input is the analyzed emotional state and the generated answer text, and the output is the adjusted answer and advertisement text.

[0364] Step 8:

[0365] The server sends the final answer and advertisement to the user's device, which receives it and displays it on the interface. The user can then review the provided answer and advertisement. The input is the adjusted answer and advertisement text, and the output is the display on the user's device.

[0366] 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.

[0367] 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.

[0368] 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.

[0369] [Second embodiment]

[0370] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0371] 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.

[0372] 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).

[0373] 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.

[0374] 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.

[0375] 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).

[0376] 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.

[0377] 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.

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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."

[0382] The present invention relates to a generative AI system that incorporates advertisements into answers to questions from users and provides the answers to the users. Hereinafter, an embodiment of this system will be described in detail.

[0383] System Overview

[0384] The system consists of the following elements:

[0385] 1. Means of receiving questions from users

[0386] 2. A method for analyzing questions and extracting topics and keywords

[0387] 3. How to gather information related to your question from the Internet

[0388] 4. How to select ads relevant to your question

[0389] 5. A means of combining collected information with selected ads to generate answers for users.

[0390] 6. Means for sending generated answers and advertisements to users

[0391] Program processing

[0392] First, the user inputs a question into the interface of the generative AI system. For example, they input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0393] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0394] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0395] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0396] The server combines the collected information with the selected advertisement to generate an answer to be provided to the user. Care is taken to ensure that the advertisement is inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is paired.

[0397] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the user's interface, allowing the user to get a useful answer to their question and view relevant advertisements.

[0398] Specific examples

[0399] Consider what happens when a user asks, "What's the latest smartphone recommendation?"

[0400] The user enters a question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to collect related information from the Internet, retrieving the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from the advertising management system. By combining the collected information with the selected advertisement, the server generates a response that incorporates an advertisement such as "X brand model Y is highly rated as the latest smartphone. Its features are..." in response to a question such as, "X brand model Y is now 20% off!" Finally, the server sends the response and advertisement to the user's device, where the user can view them on the interface.

[0401] As described above, the generative AI system according to the present invention is capable of providing free or reduced-cost information to users while effectively delivering advertisements to advertisers.

[0402] The processing flow will be explained below.

[0403] Step 1:

[0404] The user enters a question into the interface of the generative AI system and presses the send button. For example, the user enters the question, "What is your recommendation for the latest smartphone?"

[0405] Step 2:

[0406] The terminal receives the user's question and sends it to the server using a communication protocol such as an HTTP request.

[0407] Step 3:

[0408] The server receives the question sent by the user and passes the received question as text data to the analysis engine.

[0409] Step 4:

[0410] The server uses a text analysis engine to analyze the content of the question, extracting key keywords such as "smartphone," "latest," and "recommended" to identify the topic of the question.

[0411] Step 5:

[0412] The server launches a web crawling engine to gather information related to the question from the Internet, such as the latest smartphone reviews and product information, selecting only reliable sources.

[0413] Step 6:

[0414] The server accesses the ad management system and selects the most appropriate ad based on the query, for example, selecting an ad campaign related to the latest smartphones, using targeting information specified by the advertiser and past user behavior data.

[0415] Step 7:

[0416] The server combines the collected information with the selected advertisement to generate an answer to be provided to the user. At this time, the advertisement is adjusted so that it is inserted naturally into the context of the answer. For example, in response to the question, "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is combined.

[0417] Step 8:

[0418] The server then sends the generated response and advertisement to the user's device, usually using a communication protocol such as an HTTP response.

[0419] Step 9:

[0420] The terminal receives the answers and advertisements sent from the server and displays them on the user's interface, allowing the user to check them and view the contents of the answers and advertisements.

[0421] Through these steps, the system effectively provides useful answers to users' questions and relevant advertisements.

[0422] Example 1

[0423] 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."

[0424] Conventional information provision systems often lack the accuracy and reliability of answers to user questions. Furthermore, it is difficult to naturally incorporate advertisements into answers, which can detract from the user experience. Furthermore, it is difficult to select appropriate advertisements based on the content of the question, which reduces the effectiveness of advertising.

[0425] 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.

[0426] In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting main keywords and topics, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, and means for transmitting the generated answer and advertisements to the user. This makes it possible to provide highly accurate and reliable answers to user questions and to provide effective information that naturally incorporates advertisements.

[0427] A "user" is a person who uses the system to input a question.

[0428] The "means for receiving a question" is a function that allows the server to obtain a question entered by a user.

[0429] "Means for analyzing questions to extract key keywords and topics" refers to a function that analyzes questions to identify important phrases and themes.

[0430] "Means of collecting information related to the question from the Internet" is a function that collects data related to the question from the web.

[0431] "Means for selecting advertisements" is a function that selects appropriate advertisements based on the content of the question.

[0432] The "means for generating an answer by combining information and advertisements" is a function for generating an answer to be provided to a user using collected information and selected advertisements.

[0433] The "means for transmitting the generated answer and advertisement to the user" is a function for transmitting the generated answer and advertisement to the user's terminal.

[0434] "Means for extracting reliable information" is the function of selecting trustworthy data from the collected information.

[0435] "Means of naturally inserting into the context of the answer" refers to the ability to seamlessly incorporate advertisements into the content of the answer.

[0436] MODE FOR CARRYING OUT THE INVENTION

[0437] The present invention relates to a generation AI system that incorporates advertisements into answers to user questions and provides them to the user. To implement this system, a terminal to which the user connects and a server that analyzes the questions and generates answers are required. A specific embodiment of this system is described in detail below.

[0438] Hardware and software used

[0439] Server: This is the main component that receives questions, analyzes them, collects information, selects ads, generates answers, and sends them. The following software is installed on the server:

[0440] Text Analysis Engine: Analyzes the text of the question and extracts key keywords and topics. Uses Natural Language Processing (NLP) techniques.

[0441] Web Crawl Engine: Automatically crawls specific websites to collect reliable information on the Internet.

[0442] Ad Management System: Targets and selects ads.

[0443] Generative AI model: Generates answers to provide to users based on collected information and selected ads.

[0444] User device: A device that inputs questions and receives and displays answers, such as a PC, smartphone, or tablet, allowing users to interact with the system.

[0445] Explaining program processing in natural language

[0446] First, the user inputs a question into the interface of the generative AI system. For example, they input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0447] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0448] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0449] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0450] The server combines the collected information with the selected advertisements to generate answers to be provided to the user. It uses a generative AI model to create natural sentences and ensures that the advertisements are inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", it combines an advertisement saying "X brand model Y is now 20% off!"

[0451] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the user's interface, allowing the user to get a useful answer to their question and view relevant advertisements.

[0452] Examples and prompts

[0453] As a concrete example, consider the case where a user asks, "What's the best new smartphone?" The user enters the question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to gather relevant information from the Internet, including the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from an advertising management system. By combining the collected information with the selected advertisement, the server generates a response that incorporates an advertisement, such as "Brand X's Model Y is highly rated as the latest smartphone. Its features are..." in response to a question such as, "Brand X's Model Y is currently 20% off!" Finally, the server sends the response and advertisement to the user's device, where the user can view them through the interface.

[0454] As described above, the generative AI system according to the present invention is a system that integrates the provision of highly accurate and reliable information with effective advertisement delivery.

[0455] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0456] Step 1:

[0457] The user inputs a question into the interface of the generative AI system. As a concrete example, let's assume the user inputs "What's your recommendation for the latest smartphone?" The device then sends this question to the server. The input is the user's question text, and the output is an HTTP request sent to the server.

[0458] Step 2:

[0459] The server receives questions submitted by users. It passes the received questions to a text analysis engine. The text analysis engine analyzes the question text and extracts key keywords and topics. This analysis uses natural language processing (NLP) techniques. The input is the user's question text, and the output is the extracted keywords and topics.

[0460] Step 3:

[0461] The server launches a web crawling engine to collect relevant information from the Internet. Specifically, it crawls news sites, blogs, review sites, etc. to retrieve articles and reviews about the latest smartphones and recommended models. The crawling engine scrapes the page content from each site and stores reliable information in a database. The input is the extracted keywords, and the output is the collected related information.

[0462] Step 4:

[0463] The server simultaneously accesses the ad management system and selects the most appropriate ad for the query. Specifically, the server searches for relevant ad campaigns based on keywords such as "smartphone" or "latest model." This is done using targeting information provided by the advertiser and past user behavior data. The input is the extracted keywords and topics, and the output is the selected ad.

[0464] Step 5:

[0465] The server combines the collected information with the selected advertisements to generate an answer to be provided to the user. A generative AI model is used to create the optimal sentence for the user's question. This sentence incorporates the collected reviews and product information, and is designed to insert the selected advertisements naturally (without any sense of incongruity). The input is the collected information and the selected advertisements, and the output is the generated answer.

[0466] Step 6:

[0467] The server sends the generated answers and advertisements to the user's terminal. Specifically, it sends the generated text data back to the user's terminal in the form of an HTTP response. The terminal receives this and displays it on the user's interface. The input is the generated answers and advertisements, and the output is the text displayed on the user's interface.

[0468] Step 7:

[0469] The user checks the answers and advertisements displayed on the device. Specifically, they read the answers on the interface and view the related advertisements. This allows the user to obtain useful information about the question and simultaneously view selected advertisements. The input is the displayed answers and advertisements, and the output is the user's browsing behavior.

[0470] (Application example 1)

[0471] 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."

[0472] Conventional generative AI systems have had difficulty gathering accurate information and inserting advertisements naturally when generating answers to user questions and generating advertisements. Furthermore, there has been no interactive answering system that combines visual and audio information for smart devices with the ability to display information in the user's field of view in real time. As a result, improving the user experience has been a challenge.

[0473] 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.

[0474] In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, and means for transmitting the generated answer and advertisement to the user terminal and displaying them on the smart device.

[0475] This will enable accurate information and relevant advertisements to be provided to users in real time, and enable interactive information provision through visual and audio, improving the user experience.

[0476] The "means for receiving a question from a user" refers to a technical means for obtaining a question entered by a user via voice or text through a digital device.

[0477] The "means for analyzing the question and extracting topics and keywords" refers to a technical means for analyzing the received question using natural language processing technology and identifying the main topics and related keywords.

[0478] "Means for collecting information related to the question from the Internet" means technical means for searching and collecting information related to the question from reliable websites and databases on the Internet.

[0479] The "means for selecting advertisements relevant to the question" refers to a technical means for selecting advertisements that are highly relevant based on the content of the question and displaying them to the user.

[0480] "Means for combining the collected information with the selected advertisements to generate a response for the user" refers to technical means for integrating the collected information with the selected advertisements to generate a response for the user in a natural format.

[0481] "Means for transmitting the generated answers and advertisements to a user terminal and displaying them on a smart device" refers to technical means for transmitting the generated answers and advertisements to a user's digital device and displaying them on a smart device such as a smartphone or smart glasses.

[0482] The present invention relates to a generative AI system that incorporates advertisements into answers to questions posed by users and displays the answers and advertisements on smart devices. The following describes in detail the embodiments of the present invention.

[0483] System Configuration

[0484] The system consists of the following main components:

[0485] 1. Means of receiving questions from users

[0486] 2. Means for analyzing the question and extracting topics and keywords

[0487] 3. How to gather information related to your question from the Internet

[0488] 4. Means for selecting advertisements relevant to the question

[0489] 5. Means for combining the collected information with the selected advertisement to generate a response for the user.

[0490] 6. Means for transmitting the generated answers and advertisements to the user terminal and displaying them on the smart device

[0491] Hardware and Software Use

[0492] Hardware:

[0493] Smart glasses: equipped with cameras and audio capture capabilities

[0494] software:

[0495] Google Cloud Vision API

[0496] Google Speech Recognition API

[0497] OpenAI GPT-3 API

[0498] Data processing and calculation

[0499] 1. Receiving and parsing questions:

[0500] The system captures questions spoken by users into the smart glasses as audio and converts them into text using the Google Speech Recognition API, recognizes objects in the user's line of sight using the Google Cloud Vision API, and analyzes the question along with extracted topics and keywords.

[0501] 2. Information and Advertising Collection:

[0502] The server searches the Internet to gather reliable information related to the question. The web crawling engine crawls news sites, blogs, review sites, etc. to obtain the latest information. Meanwhile, it accesses the ad management system to select the most suitable ad for the question. This ad selection takes into account the question's topic and keywords, past user behavior data, etc.

[0503] 3. Generate and send the answer:

[0504] The collected information is integrated with the selected advertisements to generate answers for the user in a natural format. This process is performed using the OpenAI GPT-3 API. The generated answers and advertisements are sent to the user's device and displayed on the smart glasses.

[0505] Specific examples

[0506] A user is looking at the latest smartphone exhibit and asks, "What are the features of this smartphone?"

[0507] The smartphone is recognized from the captured image, and the user's question is converted into text using voice recognition.

[0508] Based on the question and object recognition results, prompts are sent to GPT-3 to generate answers and relevant ads.

[0509] Example prompt sentence:

[0510] Q: What are the features of the latest smartphones?

[0511] Object: Smartphone

[0512] Please provide your answer and relevant ads:

[0513] This improvement allows users to obtain quick and accurate information through questions and answers, and at the same time, to receive relevant advertisements in a natural way.

[0514] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0515] Step 1:

[0516] User question input

[0517] How it works: A user speaks a question into the smart glasses, for example, "What are the features of this smartphone?"

[0518] Input: User's voice data

[0519] Output: Captured audio data

[0520] Step 2:

[0521] Speech-to-text conversion

[0522] How it works: Converts user voice data into text using the Google Speech Recognition API.

[0523] Input: Captured audio data

[0524] Output: Texted question (e.g., "What are the features of this smartphone?")

[0525] Step 3:

[0526] Eye tracking and object recognition

[0527] How it works: The smart glasses' camera is used to capture objects in the user's line of sight, and the object is recognized using the Google Cloud Vision API.

[0528] Input: Image data captured by the camera

[0529] Output: Recognized object (e.g. "smartphone")

[0530] Step 4:

[0531] Parsing the query and object recognition results

[0532] How it works: The server analyzes the textual questions and object recognition results to extract key topics and keywords.

[0533] Input: Texted question, recognized object

[0534] Output: Extracted topics and keywords (e.g., "smartphone" and "features")

[0535] Step 5:

[0536] Gathering relevant information

[0537] How it works: The server searches the internet to gather reliable information related to your question, grabbing the data it needs from news sites, blogs, review sites, etc.

[0538] Input: Extracted topics and keywords

[0539] Output: Collected relevant information (e.g., reviews of the latest smartphones)

[0540] Step 6:

[0541] Selection of relevant advertisements

[0542] Operation: The server accesses the ad management system and selects relevant ads based on topics and keywords.

[0543] Input: Extracted topics and keywords

[0544] Output: Selected advertisements (e.g. smartphone discount campaigns)

[0545] Step 7:

[0546] Answer and Ad Generation

[0547] How it works: The server combines the collected information with the selected ads to generate a natural-looking answer for the user. This process is performed using the OpenAI GPT-3 API.

[0548] Input: Collected relevant information, selected advertisements

[0549] Output: Generated answer and advertisement (e.g., "X brand's model Y is highly rated as the latest smartphone. Features include... 20% off now!")

[0550] Step 8:

[0551] Sending and displaying responses and advertisements

[0552] How it works: The server sends the generated answers and advertisements to the user's smart glasses and displays them for the user to see in real time.

[0553] Input: Generated answers and advertisements

[0554] Output: Answers and advertisements displayed on the smart glasses (e.g., users can view them through the glasses)

[0555] 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.

[0556] The present invention relates to a generative AI system that incorporates advertisements into answers to user questions and provides them to the user. Furthermore, the present invention provides a system that combines an emotion engine that recognizes the user's emotions and adjusts the answers and advertisements based on the emotions. Below, an embodiment of this system will be described in detail.

[0557] System Overview

[0558] The system consists of the following elements:

[0559] 1. Means of receiving questions from users

[0560] 2. A means of parsing questions to extract topics and keywords

[0561] 3. How to gather information related to your question from the Internet

[0562] 4. How to select ads relevant to your question

[0563] 5. A means of combining collected information with selected ads to generate answers for users.

[0564] 6. Means for sending generated answers and advertisements to users

[0565] 7. Emotion engine that analyzes and recognizes user emotions

[0566] 8. A way to tailor responses and ads based on an emotion engine

[0567] Program processing

[0568] First, the user inputs a question into the interface of the generative AI system. For example, they might input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0569] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0570] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0571] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0572] The server then combines the collected information with the selected advertisement to generate an answer to be provided to the user. Care is taken to ensure that the advertisement is inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is paired.

[0573] Furthermore, the server uses an emotion engine to analyze the user's emotions. For example, it recognizes the user's emotions from the context when the user enters a question and from past interaction data. Based on the emotion engine, it adjusts the tone and content of answers and advertisements. For example, if the user is emotionally exhausted, it provides answers and advertisements that are more relaxing.

[0574] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the interface, allowing the user to view the answer and advertisement content.

[0575] Specific examples

[0576] Consider what happens when a user asks, "What's the latest smartphone recommendation?"

[0577] The user enters a question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to collect related information from the Internet, retrieving the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from the advertising management system. By combining the collected information with the selected advertisements, for example, in response to a question such as "X brand model Y is highly rated as the latest smartphone. Its features are...", the server generates a response incorporating an advertisement such as "X brand model Y is now 20% off!"

[0578] Furthermore, if the user's emotion is "excited," the content will be adjusted to emphasize that reaction. Or, if the user is recognized as "tired," words or advertisements with a relaxing effect will be selected.

[0579] Finally, the server sends this response and the advertisement to the user's terminal, where the user confirms it in the interface.

[0580] As described above, the generative AI system of the present invention provides users with free or reduced-cost information while effectively delivering ads to advertisers. It also provides a more personalized experience by adjusting responses and ads based on the user's emotions.

[0581] The processing flow will be explained below.

[0582] Step 1:

[0583] The user enters a question into the interface of the generative AI system and presses the send button. For example, the user enters the question, "What is your recommendation for the latest smartphone?"

[0584] Step 2:

[0585] The terminal receives the user's question and sends it to the server using a communication protocol such as an HTTP request.

[0586] Step 3:

[0587] The server receives the question sent by the user and passes the received question as text data to the analysis engine.

[0588] Step 4:

[0589] The server uses a text analysis engine to analyze the content of the question, extracting key keywords such as "smartphone," "latest," and "recommended" to identify the topic of the question.

[0590] Step 5:

[0591] The server uses an emotion engine to analyze emotions from the user's input text and past behavioral data. Based on the emotion analysis algorithm, the server identifies the user's emotional state (e.g., joy, excitement, sadness, fatigue).

[0592] Step 6:

[0593] The server launches a web crawling engine to gather information related to the question from the Internet, such as the latest smartphone reviews and product information, selecting only reliable sources.

[0594] Step 7:

[0595] The server accesses the ad management system and selects the most appropriate ad based on the query, for example, selecting an ad campaign related to the latest smartphones, using targeting information specified by the advertiser and past user behavior data.

[0596] Step 8:

[0597] The server combines the collected information with the selected advertisements to generate a response to be presented to the user. The tone of the response and the content of the advertisement are adjusted based on the user's emotions. For example, if the user is "excited," the server uses expressions that enhance excitement and makes the advertisement relevant to that emotion.

[0598] Step 9:

[0599] The server then sends the generated response and advertisement to the user's device, usually using a communication protocol such as an HTTP response.

[0600] Step 10:

[0601] The device receives the answers and advertisements sent from the server and displays them on the user's interface in a format that takes into consideration the user's feelings. The user can confirm the display and view the content of the answers and advertisements.

[0602] Through these steps, the system effectively provides useful answers to users' questions and relevant advertisements, while also providing a personalized experience that responds to the user's emotional state.

[0603] Example 2

[0604] 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."

[0605] Conventional question-answering systems are limited to providing answers to user questions and lack a way to effectively combine them with advertisements. Furthermore, they lack the ability to analyze user sentiment and tailor answers and advertisements accordingly, preventing an improved user experience. Therefore, a system that provides personalized advertisements and answers tailored to user needs was needed.

[0606] 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.

[0607] In this invention, the server includes means for receiving a question from a user, means for analyzing the question to extract topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for generating an answer for the user by combining the collected information and the selected advertisements, means for transmitting the generated answer and advertisement to the user, means for analyzing and recognizing user emotions, and means for adjusting the answer and advertisement based on the emotion analysis, thereby making it possible to provide personalized answers and advertisements according to the user's needs and emotions.

[0608] The "means for receiving questions from users" is an interface that allows the server to receive questions input by users via their terminals.

[0609] The "means for analyzing the question and extracting topics and keywords" refers to a system that analyzes the question received by the server using technology such as a text analysis engine and extracts the subject matter and important words of the question content.

[0610] "Means for collecting information related to the question from the Internet" refers to a system in which a server uses a web crawling engine or the like to search for and collect information related to the question from news sites, blogs, review sites, etc. on the Internet.

[0611] The "means for selecting an advertisement relevant to the question" refers to a process in which the server uses an advertisement management system to select an advertisement that is most suitable for the content of the question.

[0612] "Means for combining the collected information with the selected advertisements to generate a response for the user" refers to a technology for integrating the information collected by the server with the selected advertisements to generate a response for the user.

[0613] The "means for transmitting the generated answer and advertisement to the user" is a system for transmitting the answer and advertisement generated by the server to the user's terminal and displaying them on the user interface.

[0614] "Means for analyzing and recognizing user emotions" refers to technology that allows the server to analyze user input and past interaction data to recognize the user's current emotional state.

[0615] "Means for adjusting the answers and advertisements based on the sentiment analysis" refers to a process for personalizing the content and wording of answers and advertisements according to the emotional state of the user as recognized by the server.

[0616] The generative AI system of the present invention generates answers incorporating advertisements to user questions and provides personalized answers by analyzing the user's emotions. This system is composed of the following main components:

[0617] 1. User terminal: An interface is provided for users to input questions. For example, a device such as a smartphone or computer can be used.

[0618] 2. Server: Plays a central role in performing various processes and uses the following software and hardware:

[0619] Text analysis engine: Analyzes questions and extracts topics and keywords.

[0620] Web crawling engine: Collects information related to your question from the internet.

[0621] Advertisement management system: Selects the best advertisement for the question.

[0622] Emotion engine: Analyzes and recognizes user emotions.

[0623] Answer generation module: Generates answers by combining collected information with selected advertisements.

[0624] 3. Communication: Network communication is required to send and receive data between the user device and the server. This is achieved via an Internet connection.

[0625] Hardware and software used

[0626] User device: A personal computer, smartphone, tablet, etc. connected to the Internet.

[0627] Server: A physical or virtual server with high-performance computing resources, with the following software installed:

[0628] Text analysis engines: Libraries for natural language processing (e.g. NLTK, spaCy, etc.).

[0629] Web crawling engines: Tools for web scraping (e.g. Beautiful Soup, Scrapy, etc.).

[0630] Ad Management Systems: Ad databases and targeting algorithms (e.g., Google Ad Manager).

[0631] Emotion engine: An emotion analysis tool that uses facial recognition and text mining technology (e.g., IBM Watson, Microsoft Azure Emotion API, etc.).

[0632] Answer generation module: Utilizes generative AI models (e.g., GPT-3).

[0633] Specific examples

[0634] For example, consider a scenario in which a user inputs the question "What's the latest smartphone recommendation?" into a generative AI system.

[0635] 1. The user inputs a question into the interface, and the user terminal sends this input to the server.

[0636] 2. The server receives the question and uses a text analysis engine to extract the main keywords "smartphone" and "recommended."

[0637] 3. The server then launches a web crawling engine to gather reliable information about the latest smartphones from news sites and blogs across the Internet.

[0638] 4. At the same time, the server accesses the ad management system and selects relevant ads based on the collected keywords and user attributes. For example, it selects an ad for a 20% discount on model Y of brand X during a campaign.

[0639] 5. The server combines the collected information with the selected advertisement, and incorporates an advertisement that reads, "X brand model Y is highly rated as the latest smartphone. Its features are..." into the response, "X brand model Y is now 20% off!"

[0640] 6. The server uses the emotion engine to hypothesize the user's current emotional state. For example, it recognizes that the user is "excited" based on the speed at which the question is typed and past interactions.

[0641] 7. The server further adjusts the tone and content of the responses and ads based on sentiment analysis: if the user is "excited," it uses language that emphasizes that sentiment.

[0642] 8. Finally, the server sends the generated answer and advertisement to the user's terminal, where the user can view the content through the interface.

[0643] For example, the prompt is:

[0644] What's your recommendation for the latest smartphone?

[0645] In this way, the generative AI system of the present invention can provide personalized answers and advertisements that match the user's needs and emotions, thereby improving the user experience and maximizing the effectiveness of advertisements.

[0646] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0647] Step 1:

[0648] The user inputs a question into the interface. For example, the user inputs a question such as "What is the latest smartphone recommended?" The input question is stored on the device as string data.

[0649] Step 2:

[0650] The terminal sends the entered question to the server. The terminal uses a transmission protocol to send the question as a string of data to the server. The input is the user's question, and the output is the transfer of the question data to the server.

[0651] Step 3:

[0652] The server receives the question and passes it to the text analysis engine. The analysis engine receives the question that arrives at the server and extracts the main keywords and topics of the question. For example, keywords such as "smartphone" and "recommended" are extracted. The input is the user's question data, and the output is the extracted keywords and topics.

[0653] Step 4:

[0654] The server starts a web crawling engine to gather information related to the question from the Internet. It uses a search engine API to retrieve related news articles, review sites, blog posts, etc. For example, "latest smartphone review articles" or "product information." The input is the extracted keywords, and the output is the data of related web pages.

[0655] Step 5:

[0656] The server accesses the advertising management system and selects the advertisement that best suits the query. The server uses a targeting algorithm to select advertisements related to "smartphones" and "latest models" from the advertising database. For example, it selects a campaign advertisement such as "X brand Y model is now 20% off!" The input is the extracted keywords and user attribute data, and the output is the selected advertising information.

[0657] Step 6:

[0658] The server combines the collected information with the selected advertisement to generate an answer. The answer generation module uses text generation technology to create an answer based on the collected information and inserts the advertisement naturally. For example, to the question, "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is added. The input is the collected information and the selected advertisement, and the output is the generated answer.

[0659] Step 7:

[0660] The server uses an emotion engine to analyze the user's emotions. It determines the user's emotional state, such as whether they are "excited" or "tired," based on past interaction data and contextual analysis of input. The input is the user's past data and current question data, and the output is the user's emotional state information.

[0661] Step 8:

[0662] The server adjusts the tone and content of responses and advertisements based on emotion analysis. For example, if the user is recognized as "tired," the responses will be adjusted to be more relaxing, and advertisements will also be changed to have a similarly relaxing effect. The input is the user's emotional state information, and the output is the adjusted responses and advertisements.

[0663] Step 9:

[0664] The server sends the generated answers and advertisements to the user's terminal. The server sends this data to the terminal via the Internet, and the terminal receives it. The input is the generated answers and advertisements, and the output is the data transfer to the terminal.

[0665] Step 10:

[0666] The terminal displays the received information on the interface, and the user can confirm it. The user can see the provided answers and advertisement content on the interface. The input is the data sent from the server, and the output is the displayed answers and advertisements.

[0667] (Application example 2)

[0668] 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."

[0669] Conventional information provision systems have the problem that answers to user questions are uniform and not personalized to reflect the user's emotions or circumstances. Furthermore, when incorporating advertisements, it is difficult to insert them naturally into the context, which can detract from the user experience. Furthermore, the collected information may not always be reliable, raising concerns about a decline in user trust. To address these issues, technology is needed to tailor answers and advertisements based on the user's emotions and to provide reliable information.

[0670] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, means for sending the generated answer and advertisement to the user, means for analyzing and recognizing the user's emotions, and means for adjusting the answer and advertisement based on the emotion analysis. This makes it possible to provide personalized answers and advertisements according to the user's emotions.

[0671] The "means for receiving a question from a user" is an interface that allows the system to receive a question in text format entered by a user.

[0672] The "means for analyzing questions and extracting topics and keywords" is a function for analyzing user questions using natural language processing technology and identifying major topics and important words and phrases.

[0673] The "means for collecting information related to a question from the Internet" is a program for searching and acquiring information related to a user's question from data sources on the Internet.

[0674] The "means for selecting advertisements relevant to a question" is a function for selecting highly relevant advertisements from a database or advertising platform based on the content of a user's question.

[0675] The "means for combining collected information with selected advertisements to generate a response for the user" is a program that integrates the acquired information with advertisements and creates a response to be provided to the user.

[0676] The "means for transmitting the generated answers and advertisements to the user" is a communication function for delivering the answers and advertisements generated by the system to the user's terminal.

[0677] "Means for analyzing and recognizing user emotions" refers to technology that performs emotion analysis based on questions entered by the user and past data, and identifies the user's current emotional state.

[0678] The "means for adjusting answers and advertisements based on sentiment analysis" refers to an algorithm for changing the content and tone of answers and advertisements provided depending on the emotional state of the user.

[0679] The system that realizes this application combines answers to user questions with advertisements and tailors them based on emotions. The system consists of the following main hardware and software components:

[0680] 1. User Device:

[0681] The device, such as a smartphone or tablet, provides an interface for users to input questions, which are then sent to a server.

[0682] 2. Server:

[0683] It is a central system that runs a text analysis engine, web crawling engine, ad management system, generative AI system, sentiment engine, etc. The server integrates these functions and manages the process.

[0684] Specific software used includes natural language processing libraries (e.g., TextBlob), web crawling libraries (e.g., BeautifulSoup), and machine learning libraries (e.g., TensorFlow).

[0685] 3. Program processing flow:

[0686] When a user types a question, it is sent to the server, which first passes it through a text analysis engine to extract key keywords and topics.

[0687] Next, the web crawling engine gathers relevant information from the internet, gathering information from reliable data sources such as news sites, blogs, and review sites.

[0688] The server accesses the advertisement management system to select advertisements relevant to the query, using criteria including keywords in the query and past user behavior data.

[0689] The AI ​​system combines the collected information with the selected ads to generate answers, which are then adjusted to insert the ads naturally into the context.

[0690] The emotion engine analyzes the user's emotions and adjusts the responses and ads based on the emotions, for example, if the user is in a positive emotional state, it will choose positive ads, and if the user is in a negative emotional state, it will choose ads with a relaxing effect.

[0691] Finally, the generated answers and advertisements are sent to the user's terminal, where the user can view them.

[0692] Examples:

[0693] A user enters a question such as "What's the best new smartphone?" This question is sent to a server, where a text analysis engine extracts keywords such as "smartphone" and "recommended." A web crawling engine collects related review articles and product information, and an advertising management system selects an advertisement that reads, "20% off a new smartphone!" A generative AI system combines the collected information with the advertisement to generate an answer.

[0694] The emotion engine analyzes the user's emotions, and if the user's emotions are positive, the content of the advertisement is adjusted to "We'll also bring you some fun information!" The adjusted answer and advertisement are sent to the user's device, where the user can view them.

[0695] Example prompt sentence:

[0696] "A user asks, 'What's the best new smartphone?' Generate an answer to this question that includes information about the latest smartphones and relevant ads. Be especially positive in your answers and ads, and make the user feel good."

[0697] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0698] Step 1:

[0699] A user types a question into a device. When a user types a question into the device's interface, such as "What's the best new smartphone?", the question is sent to a server. The input is the user's question text, and the output is that this text is sent to the server.

[0700] Step 2:

[0701] The server receives the question and passes it to a text analysis engine. The text analysis engine analyzes the input question and extracts topics and keywords. For example, the keywords "latest smartphone" and "recommendations" are extracted. The input is the user's question text, and the output is the extracted keywords and topics.

[0702] Step 3:

[0703] Based on the extracted keywords, the server uses a web crawling engine to collect related information from the Internet, obtaining data from reliable sources such as news sites, blogs, and review sites. The input is the extracted keywords and topics, and the output is related information data.

[0704] Step 4:

[0705] The server uses an ad management system to select ads relevant to the query. The ad management system searches a database for appropriate ads based on the extracted keywords. For example, an ad for "20% off the latest smartphone" is selected. The input is the extracted keywords, topics, and past user behavior data, and the output is the selected ad.

[0706] Step 5:

[0707] The server combines the collected information with the selected advertisements and generates an answer using a generative AI system. The generative AI system generates text that naturally inserts advertisements into the context of the answer. For example, the generated answer might be, "The latest smartphone is model X, which has received high reviews. Plus, you can get it now for 20% off!" The input is the collected information and the selected advertisements, and the output is the answer text with the advertisements incorporated.

[0708] Step 6:

[0709] The server analyzes the user's input questions and past interaction data to analyze the user's emotions using an emotion engine. The emotion engine identifies the user's current emotional state. The input is the user's question text and past interaction data, and the output is the analyzed emotional state.

[0710] Step 7:

[0711] The server adjusts the content and tone of the answers and advertisements based on the emotional analysis. For example, if the user is in a positive emotional state, it provides positive words and emphasizes the advertisement. Conversely, if the user is in a negative emotional state, it changes the expressions and content to make the user feel more relaxed. The input is the analyzed emotional state and the generated answer text, and the output is the adjusted answer and advertisement text.

[0712] Step 8:

[0713] The server sends the final answer and advertisement to the user's device, which receives it and displays it on the interface. The user can then review the provided answer and advertisement. The input is the adjusted answer and advertisement text, and the output is the display on the user's device.

[0714] 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.

[0715] 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.

[0716] 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.

[0717] [Third embodiment]

[0718] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0719] 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.

[0720] 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).

[0721] 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.

[0722] 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.

[0723] 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).

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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.

[0728] 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.

[0729] 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."

[0730] The present invention relates to a generative AI system that incorporates advertisements into answers to questions from users and provides the answers to the users. Hereinafter, an embodiment of this system will be described in detail.

[0731] System Overview

[0732] The system consists of the following elements:

[0733] 1. Means of receiving questions from users

[0734] 2. A method for analyzing questions and extracting topics and keywords

[0735] 3. How to gather information related to your question from the Internet

[0736] 4. How to select ads relevant to your question

[0737] 5. A means of combining collected information with selected ads to generate answers for users.

[0738] 6. Means for sending generated answers and advertisements to users

[0739] Program processing

[0740] First, the user inputs a question into the interface of the generative AI system. For example, they input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0741] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0742] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0743] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0744] The server combines the collected information with the selected advertisement to generate an answer to be provided to the user. Care is taken to ensure that the advertisement is inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is paired.

[0745] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the user's interface, allowing the user to get a useful answer to their question and view relevant advertisements.

[0746] Specific examples

[0747] Consider what happens when a user asks, "What's the latest smartphone recommendation?"

[0748] The user enters a question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to collect related information from the Internet, retrieving the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from the advertising management system. By combining the collected information with the selected advertisement, the server generates a response that incorporates an advertisement such as "X brand model Y is highly rated as the latest smartphone. Its features are..." in response to a question such as, "X brand model Y is now 20% off!" Finally, the server sends the response and advertisement to the user's device, where the user can view them on the interface.

[0749] As described above, the generative AI system according to the present invention is capable of providing free or reduced-cost information to users while effectively delivering advertisements to advertisers.

[0750] The processing flow will be explained below.

[0751] Step 1:

[0752] The user enters a question into the interface of the generative AI system and presses the send button. For example, the user enters the question, "What is your recommendation for the latest smartphone?"

[0753] Step 2:

[0754] The terminal receives the user's question and sends it to the server using a communication protocol such as an HTTP request.

[0755] Step 3:

[0756] The server receives the question sent by the user and passes the received question as text data to the analysis engine.

[0757] Step 4:

[0758] The server uses a text analysis engine to analyze the content of the question, extracting key keywords such as "smartphone," "latest," and "recommended" to identify the topic of the question.

[0759] Step 5:

[0760] The server launches a web crawling engine to gather information related to the question from the Internet, such as the latest smartphone reviews and product information, selecting only reliable sources.

[0761] Step 6:

[0762] The server accesses the ad management system and selects the most appropriate ad based on the query, for example, selecting an ad campaign related to the latest smartphones, using targeting information specified by the advertiser and past user behavior data.

[0763] Step 7:

[0764] The server combines the collected information with the selected advertisement to generate an answer to be provided to the user. At this time, the advertisement is adjusted so that it is inserted naturally into the context of the answer. For example, in response to the question, "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is combined.

[0765] Step 8:

[0766] The server then sends the generated response and advertisement to the user's device, usually using a communication protocol such as an HTTP response.

[0767] Step 9:

[0768] The terminal receives the answers and advertisements sent from the server and displays them on the user's interface, allowing the user to check them and view the contents of the answers and advertisements.

[0769] Through these steps, the system effectively provides useful answers to users' questions and relevant advertisements.

[0770] Example 1

[0771] 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."

[0772] Conventional information provision systems often lack the accuracy and reliability of answers to user questions. Furthermore, it is difficult to naturally incorporate advertisements into answers, which can detract from the user experience. Furthermore, it is difficult to select appropriate advertisements based on the content of the question, which reduces the effectiveness of advertising.

[0773] 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.

[0774] In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting main keywords and topics, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, and means for transmitting the generated answer and advertisements to the user. This makes it possible to provide highly accurate and reliable answers to user questions and to provide effective information that naturally incorporates advertisements.

[0775] A "user" is a person who uses the system to input a question.

[0776] The "means for receiving a question" is a function that allows the server to obtain a question entered by a user.

[0777] "Means for analyzing questions to extract key keywords and topics" refers to a function that analyzes questions to identify important phrases and themes.

[0778] "Means of collecting information related to the question from the Internet" is a function that collects data related to the question from the web.

[0779] "Means for selecting advertisements" is a function that selects appropriate advertisements based on the content of the question.

[0780] The "means for generating an answer by combining information and advertisements" is a function for generating an answer to be provided to a user using collected information and selected advertisements.

[0781] The "means for transmitting the generated answer and advertisement to the user" is a function for transmitting the generated answer and advertisement to the user's terminal.

[0782] "Means for extracting reliable information" is the function of selecting trustworthy data from the collected information.

[0783] "Means of naturally inserting into the context of the answer" refers to the ability to seamlessly incorporate advertisements into the content of the answer.

[0784] MODE FOR CARRYING OUT THE INVENTION

[0785] The present invention relates to a generation AI system that incorporates advertisements into answers to user questions and provides them to the user. To implement this system, a terminal to which the user connects and a server that analyzes the questions and generates answers are required. A specific embodiment of this system is described in detail below.

[0786] Hardware and software used

[0787] Server: This is the main component that receives questions, analyzes them, collects information, selects ads, generates answers, and sends them. The following software is installed on the server:

[0788] Text Analysis Engine: Analyzes the text of the question and extracts key keywords and topics. Uses Natural Language Processing (NLP) techniques.

[0789] Web Crawl Engine: Automatically crawls specific websites to collect reliable information on the Internet.

[0790] Ad Management System: Targets and selects ads.

[0791] Generative AI model: Generates answers to provide to users based on collected information and selected ads.

[0792] User device: A device that inputs questions and receives and displays answers, such as a PC, smartphone, or tablet, allowing users to interact with the system.

[0793] Explaining program processing in natural language

[0794] First, the user inputs a question into the interface of the generative AI system. For example, they input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0795] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0796] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0797] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0798] The server combines the collected information with the selected advertisements to generate answers to be provided to the user. It uses a generative AI model to create natural sentences and ensures that the advertisements are inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", it combines an advertisement saying "X brand model Y is now 20% off!"

[0799] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the user's interface, allowing the user to get a useful answer to their question and view relevant advertisements.

[0800] Examples and prompts

[0801] As a concrete example, consider the case where a user asks, "What's the best new smartphone?" The user enters the question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to gather relevant information from the Internet, including the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from an advertising management system. By combining the collected information with the selected advertisement, the server generates a response that incorporates an advertisement, such as "Brand X's Model Y is highly rated as the latest smartphone. Its features are..." in response to a question such as, "Brand X's Model Y is currently 20% off!" Finally, the server sends the response and advertisement to the user's device, where the user can view them through the interface.

[0802] As described above, the generative AI system according to the present invention is a system that integrates the provision of highly accurate and reliable information with effective advertisement delivery.

[0803] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0804] Step 1:

[0805] The user inputs a question into the interface of the generative AI system. As a concrete example, let's assume the user inputs "What's your recommendation for the latest smartphone?" The device then sends this question to the server. The input is the user's question text, and the output is an HTTP request sent to the server.

[0806] Step 2:

[0807] The server receives questions submitted by users. It passes the received questions to a text analysis engine. The text analysis engine analyzes the question text and extracts key keywords and topics. This analysis uses natural language processing (NLP) techniques. The input is the user's question text, and the output is the extracted keywords and topics.

[0808] Step 3:

[0809] The server launches a web crawling engine to collect relevant information from the Internet. Specifically, it crawls news sites, blogs, review sites, etc. to retrieve articles and reviews about the latest smartphones and recommended models. The crawling engine scrapes the page content from each site and stores reliable information in a database. The input is the extracted keywords, and the output is the collected related information.

[0810] Step 4:

[0811] The server simultaneously accesses the ad management system and selects the most appropriate ad for the query. Specifically, the server searches for relevant ad campaigns based on keywords such as "smartphone" or "latest model." This is done using targeting information provided by the advertiser and past user behavior data. The input is the extracted keywords and topics, and the output is the selected ad.

[0812] Step 5:

[0813] The server combines the collected information with the selected advertisements to generate an answer to be provided to the user. A generative AI model is used to create the optimal sentence for the user's question. This sentence incorporates the collected reviews and product information, and is designed to insert the selected advertisements naturally (without any sense of incongruity). The input is the collected information and the selected advertisements, and the output is the generated answer.

[0814] Step 6:

[0815] The server sends the generated answers and advertisements to the user's terminal. Specifically, it sends the generated text data back to the user's terminal in the form of an HTTP response. The terminal receives this and displays it on the user's interface. The input is the generated answers and advertisements, and the output is the text displayed on the user's interface.

[0816] Step 7:

[0817] The user checks the answers and advertisements displayed on the device. Specifically, they read the answers on the interface and view the related advertisements. This allows the user to obtain useful information about the question and simultaneously view selected advertisements. The input is the displayed answers and advertisements, and the output is the user's browsing behavior.

[0818] (Application example 1)

[0819] 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."

[0820] Conventional generative AI systems have had difficulty gathering accurate information and inserting advertisements naturally when generating answers to user questions and generating advertisements. Furthermore, there has been no interactive answering system that combines visual and audio information for smart devices with the ability to display information in the user's field of view in real time. As a result, improving the user experience has been a challenge.

[0821] 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.

[0822] In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, and means for transmitting the generated answer and advertisement to the user terminal and displaying them on the smart device.

[0823] This will enable accurate information and relevant advertisements to be provided to users in real time, and enable interactive information provision through visual and audio, improving the user experience.

[0824] The "means for receiving a question from a user" refers to a technical means for obtaining a question entered by a user via voice or text through a digital device.

[0825] The "means for analyzing the question and extracting topics and keywords" refers to a technical means for analyzing the received question using natural language processing technology and identifying the main topics and related keywords.

[0826] "Means for collecting information related to the question from the Internet" means technical means for searching and collecting information related to the question from reliable websites and databases on the Internet.

[0827] The "means for selecting advertisements relevant to the question" refers to a technical means for selecting advertisements that are highly relevant based on the content of the question and displaying them to the user.

[0828] "Means for combining the collected information with the selected advertisements to generate a response for the user" refers to technical means for integrating the collected information with the selected advertisements to generate a response for the user in a natural format.

[0829] "Means for transmitting the generated answers and advertisements to a user terminal and displaying them on a smart device" refers to technical means for transmitting the generated answers and advertisements to a user's digital device and displaying them on a smart device such as a smartphone or smart glasses.

[0830] The present invention relates to a generative AI system that incorporates advertisements into answers to questions posed by users and displays the answers and advertisements on smart devices. The following describes in detail the embodiments of the present invention.

[0831] System Configuration

[0832] The system consists of the following main components:

[0833] 1. Means of receiving questions from users

[0834] 2. Means for analyzing the question and extracting topics and keywords

[0835] 3. How to gather information related to your question from the Internet

[0836] 4. Means for selecting advertisements relevant to the question

[0837] 5. Means for combining the collected information with the selected advertisement to generate a response for the user.

[0838] 6. Means for transmitting the generated answers and advertisements to the user terminal and displaying them on the smart device

[0839] Hardware and Software Use

[0840] Hardware:

[0841] Smart glasses: equipped with cameras and audio capture capabilities

[0842] software:

[0843] Google Cloud Vision API

[0844] Google Speech Recognition API

[0845] OpenAI GPT-3 API

[0846] Data processing and calculation

[0847] 1. Receiving and parsing questions:

[0848] The system captures questions spoken by users into the smart glasses as audio and converts them into text using the Google Speech Recognition API, recognizes objects in the user's line of sight using the Google Cloud Vision API, and analyzes the question along with extracted topics and keywords.

[0849] 2. Information and Advertising Collection:

[0850] The server searches the Internet to gather reliable information related to the question. The web crawling engine crawls news sites, blogs, review sites, etc. to obtain the latest information. Meanwhile, it accesses the ad management system to select the most suitable ad for the question. This ad selection takes into account the question's topic and keywords, past user behavior data, etc.

[0851] 3. Generate and send the answer:

[0852] The collected information is integrated with the selected advertisements to generate answers for the user in a natural format. This process is performed using the OpenAI GPT-3 API. The generated answers and advertisements are sent to the user's device and displayed on the smart glasses.

[0853] Specific examples

[0854] A user is looking at the latest smartphone exhibit and asks, "What are the features of this smartphone?"

[0855] The smartphone is recognized from the captured image, and the user's question is converted into text using voice recognition.

[0856] Based on the question and object recognition results, prompts are sent to GPT-3 to generate answers and relevant ads.

[0857] Example prompt sentence:

[0858] Q: What are the features of the latest smartphones?

[0859] Object: Smartphone

[0860] Please provide your answer and relevant ads:

[0861] This improvement allows users to obtain quick and accurate information through questions and answers, and at the same time, to receive relevant advertisements in a natural way.

[0862] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0863] Step 1:

[0864] User question input

[0865] How it works: A user speaks a question into the smart glasses, for example, "What are the features of this smartphone?"

[0866] Input: User's voice data

[0867] Output: Captured audio data

[0868] Step 2:

[0869] Speech-to-text conversion

[0870] How it works: Converts user voice data into text using the Google Speech Recognition API.

[0871] Input: Captured audio data

[0872] Output: Texted question (e.g., "What are the features of this smartphone?")

[0873] Step 3:

[0874] Eye tracking and object recognition

[0875] How it works: The smart glasses' camera is used to capture objects in the user's line of sight, and the object is recognized using the Google Cloud Vision API.

[0876] Input: Image data captured by the camera

[0877] Output: Recognized object (e.g. "smartphone")

[0878] Step 4:

[0879] Parsing the query and object recognition results

[0880] How it works: The server analyzes the textual questions and object recognition results to extract key topics and keywords.

[0881] Input: Texted question, recognized object

[0882] Output: Extracted topics and keywords (e.g., "smartphone" and "features")

[0883] Step 5:

[0884] Gathering relevant information

[0885] How it works: The server searches the internet to gather reliable information related to your question, grabbing the data it needs from news sites, blogs, review sites, etc.

[0886] Input: Extracted topics and keywords

[0887] Output: Collected relevant information (e.g., reviews of the latest smartphones)

[0888] Step 6:

[0889] Selection of relevant advertisements

[0890] Operation: The server accesses the ad management system and selects relevant ads based on topics and keywords.

[0891] Input: Extracted topics and keywords

[0892] Output: Selected advertisements (e.g. smartphone discount campaigns)

[0893] Step 7:

[0894] Answer and Ad Generation

[0895] How it works: The server combines the collected information with the selected ads to generate a natural-looking answer for the user. This process is performed using the OpenAI GPT-3 API.

[0896] Input: Collected relevant information, selected advertisements

[0897] Output: Generated answer and advertisement (e.g., "X brand's model Y is highly rated as the latest smartphone. Features include... 20% off now!")

[0898] Step 8:

[0899] Sending and displaying responses and advertisements

[0900] How it works: The server sends the generated answers and advertisements to the user's smart glasses and displays them for the user to see in real time.

[0901] Input: Generated answers and advertisements

[0902] Output: Answers and advertisements displayed on the smart glasses (e.g., users can view them through the glasses)

[0903] 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.

[0904] The present invention relates to a generative AI system that incorporates advertisements into answers to user questions and provides them to the user. Furthermore, the present invention provides a system that combines an emotion engine that recognizes the user's emotions and adjusts the answers and advertisements based on the emotions. Below, an embodiment of this system will be described in detail.

[0905] System Overview

[0906] The system consists of the following elements:

[0907] 1. Means of receiving questions from users

[0908] 2. A means of parsing questions to extract topics and keywords

[0909] 3. How to gather information related to your question from the Internet

[0910] 4. How to select ads relevant to your question

[0911] 5. A means of combining collected information with selected ads to generate answers for users.

[0912] 6. Means for sending generated answers and advertisements to users

[0913] 7. Emotion engine that analyzes and recognizes user emotions

[0914] 8. A way to tailor responses and ads based on an emotion engine

[0915] Program processing

[0916] First, the user inputs a question into the interface of the generative AI system. For example, they might input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[0917] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[0918] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[0919] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[0920] The server then combines the collected information with the selected advertisement to generate an answer to be provided to the user. Care is taken to ensure that the advertisement is inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is paired.

[0921] Furthermore, the server uses an emotion engine to analyze the user's emotions. For example, it recognizes the user's emotions from the context when the user enters a question and from past interaction data. Based on the emotion engine, it adjusts the tone and content of answers and advertisements. For example, if the user is emotionally exhausted, it provides answers and advertisements that are more relaxing.

[0922] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the interface, allowing the user to view the answer and advertisement content.

[0923] Specific examples

[0924] Consider what happens when a user asks, "What's the latest smartphone recommendation?"

[0925] The user enters a question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to collect related information from the Internet, retrieving the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from the advertising management system. By combining the collected information with the selected advertisements, for example, in response to a question such as "X brand model Y is highly rated as the latest smartphone. Its features are...", the server generates a response incorporating an advertisement such as "X brand model Y is now 20% off!"

[0926] Furthermore, if the user's emotion is "excited," the content will be adjusted to emphasize that reaction. Or, if the user is recognized as "tired," words or advertisements with a relaxing effect will be selected.

[0927] Finally, the server sends this response and the advertisement to the user's terminal, where the user confirms it in the interface.

[0928] As described above, the generative AI system of the present invention provides users with free or reduced-cost information while effectively delivering ads to advertisers. It also provides a more personalized experience by adjusting responses and ads based on the user's emotions.

[0929] The processing flow will be explained below.

[0930] Step 1:

[0931] The user enters a question into the interface of the generative AI system and presses the send button. For example, the user enters the question, "What is your recommendation for the latest smartphone?"

[0932] Step 2:

[0933] The terminal receives the user's question and sends it to the server using a communication protocol such as an HTTP request.

[0934] Step 3:

[0935] The server receives the question sent by the user and passes the received question as text data to the analysis engine.

[0936] Step 4:

[0937] The server uses a text analysis engine to analyze the content of the question, extracting key keywords such as "smartphone," "latest," and "recommended" to identify the topic of the question.

[0938] Step 5:

[0939] The server uses an emotion engine to analyze emotions from the user's input text and past behavioral data. Based on the emotion analysis algorithm, the server identifies the user's emotional state (e.g., joy, excitement, sadness, fatigue).

[0940] Step 6:

[0941] The server launches a web crawling engine to gather information related to the question from the Internet, such as the latest smartphone reviews and product information, selecting only reliable sources.

[0942] Step 7:

[0943] The server accesses the ad management system and selects the most appropriate ad based on the query, for example, selecting an ad campaign related to the latest smartphones, using targeting information specified by the advertiser and past user behavior data.

[0944] Step 8:

[0945] The server combines the collected information with the selected advertisements to generate a response to be presented to the user. The tone of the response and the content of the advertisement are adjusted based on the user's emotions. For example, if the user is "excited," the server uses expressions that enhance excitement and makes the advertisement relevant to that emotion.

[0946] Step 9:

[0947] The server then sends the generated response and advertisement to the user's device, usually using a communication protocol such as an HTTP response.

[0948] Step 10:

[0949] The device receives the answers and advertisements sent from the server and displays them on the user's interface in a format that takes into consideration the user's feelings. The user can confirm the display and view the content of the answers and advertisements.

[0950] Through these steps, the system effectively provides useful answers to users' questions and relevant advertisements, while also providing a personalized experience that responds to the user's emotional state.

[0951] Example 2

[0952] 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."

[0953] Conventional question-answering systems are limited to providing answers to user questions and lack a way to effectively combine them with advertisements. Furthermore, they lack the ability to analyze user sentiment and tailor answers and advertisements accordingly, preventing an improved user experience. Therefore, a system that provides personalized advertisements and answers tailored to user needs was needed.

[0954] 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.

[0955] In this invention, the server includes means for receiving a question from a user, means for analyzing the question to extract topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for generating an answer for the user by combining the collected information and the selected advertisements, means for transmitting the generated answer and advertisement to the user, means for analyzing and recognizing user emotions, and means for adjusting the answer and advertisement based on the emotion analysis, thereby making it possible to provide personalized answers and advertisements according to the user's needs and emotions.

[0956] The "means for receiving questions from users" is an interface that allows the server to receive questions input by users via their terminals.

[0957] The "means for analyzing the question and extracting topics and keywords" refers to a system that analyzes the question received by the server using technology such as a text analysis engine and extracts the subject matter and important words of the question content.

[0958] "Means for collecting information related to the question from the Internet" refers to a system in which a server uses a web crawling engine or the like to search for and collect information related to the question from news sites, blogs, review sites, etc. on the Internet.

[0959] The "means for selecting an advertisement relevant to the question" refers to a process in which the server uses an advertisement management system to select an advertisement that is most suitable for the content of the question.

[0960] "Means for combining the collected information with the selected advertisements to generate a response for the user" refers to a technology for integrating the information collected by the server with the selected advertisements to generate a response for the user.

[0961] The "means for transmitting the generated answer and advertisement to the user" is a system for transmitting the answer and advertisement generated by the server to the user's terminal and displaying them on the user interface.

[0962] "Means for analyzing and recognizing user emotions" refers to technology that allows the server to analyze user input and past interaction data to recognize the user's current emotional state.

[0963] "Means for adjusting the answers and advertisements based on the sentiment analysis" refers to a process for personalizing the content and wording of answers and advertisements according to the emotional state of the user as recognized by the server.

[0964] The generative AI system of the present invention generates answers incorporating advertisements to user questions and provides personalized answers by analyzing the user's emotions. This system is composed of the following main components:

[0965] 1. User terminal: An interface is provided for users to input questions. For example, a device such as a smartphone or computer can be used.

[0966] 2. Server: Plays a central role in performing various processes and uses the following software and hardware:

[0967] Text analysis engine: Analyzes questions and extracts topics and keywords.

[0968] Web crawling engine: Collects information related to your question from the internet.

[0969] Advertisement management system: Selects the best advertisement for the question.

[0970] Emotion engine: Analyzes and recognizes user emotions.

[0971] Answer generation module: Generates answers by combining collected information with selected advertisements.

[0972] 3. Communication: Network communication is required to send and receive data between the user device and the server. This is achieved via an Internet connection.

[0973] Hardware and software used

[0974] User device: A personal computer, smartphone, tablet, etc. connected to the Internet.

[0975] Server: A physical or virtual server with high-performance computing resources, with the following software installed:

[0976] Text analysis engines: Libraries for natural language processing (e.g. NLTK, spaCy, etc.).

[0977] Web crawling engines: Tools for web scraping (e.g. Beautiful Soup, Scrapy, etc.).

[0978] Ad Management Systems: Ad databases and targeting algorithms (e.g., Google Ad Manager).

[0979] Emotion engine: An emotion analysis tool that uses facial recognition and text mining technology (e.g., IBM Watson, Microsoft Azure Emotion API, etc.).

[0980] Answer generation module: Utilizes generative AI models (e.g., GPT-3).

[0981] Specific examples

[0982] For example, consider a scenario in which a user inputs the question "What's the latest smartphone recommendation?" into a generative AI system.

[0983] 1. The user inputs a question into the interface, and the user terminal sends this input to the server.

[0984] 2. The server receives the question and uses a text analysis engine to extract the main keywords "smartphone" and "recommended."

[0985] 3. The server then launches a web crawling engine to gather reliable information about the latest smartphones from news sites and blogs across the Internet.

[0986] 4. At the same time, the server accesses the ad management system and selects relevant ads based on the collected keywords and user attributes. For example, it selects an ad for a 20% discount on model Y of brand X during a campaign.

[0987] 5. The server combines the collected information with the selected advertisement, and incorporates an advertisement that reads, "X brand model Y is highly rated as the latest smartphone. Its features are..." into the response, "X brand model Y is now 20% off!"

[0988] 6. The server uses the emotion engine to hypothesize the user's current emotional state. For example, it recognizes that the user is "excited" based on the speed at which the question is typed and past interactions.

[0989] 7. The server further adjusts the tone and content of the responses and ads based on sentiment analysis: if the user is "excited," it uses language that emphasizes that sentiment.

[0990] 8. Finally, the server sends the generated answer and advertisement to the user's terminal, where the user can view the content through the interface.

[0991] For example, the prompt is:

[0992] What's your recommendation for the latest smartphone?

[0993] In this way, the generative AI system of the present invention can provide personalized answers and advertisements that match the user's needs and emotions, thereby improving the user experience and maximizing the effectiveness of advertisements.

[0994] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0995] Step 1:

[0996] The user inputs a question into the interface. For example, the user inputs a question such as "What is the latest smartphone recommended?" The input question is stored on the device as string data.

[0997] Step 2:

[0998] The terminal sends the entered question to the server. The terminal uses a transmission protocol to send the question as a string of data to the server. The input is the user's question, and the output is the transfer of the question data to the server.

[0999] Step 3:

[1000] The server receives the question and passes it to the text analysis engine. The analysis engine receives the question that arrives at the server and extracts the main keywords and topics of the question. For example, keywords such as "smartphone" and "recommended" are extracted. The input is the user's question data, and the output is the extracted keywords and topics.

[1001] Step 4:

[1002] The server starts a web crawling engine to gather information related to the question from the Internet. It uses a search engine API to retrieve related news articles, review sites, blog posts, etc. For example, "latest smartphone review articles" or "product information." The input is the extracted keywords, and the output is the data of related web pages.

[1003] Step 5:

[1004] The server accesses the advertising management system and selects the advertisement that best suits the query. The server uses a targeting algorithm to select advertisements related to "smartphones" and "latest models" from the advertising database. For example, it selects a campaign advertisement such as "X brand Y model is now 20% off!" The input is the extracted keywords and user attribute data, and the output is the selected advertising information.

[1005] Step 6:

[1006] The server combines the collected information with the selected advertisement to generate an answer. The answer generation module uses text generation technology to create an answer based on the collected information and inserts the advertisement naturally. For example, to the question, "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is added. The input is the collected information and the selected advertisement, and the output is the generated answer.

[1007] Step 7:

[1008] The server uses an emotion engine to analyze the user's emotions. It determines the user's emotional state, such as whether they are "excited" or "tired," based on past interaction data and contextual analysis of input. The input is the user's past data and current question data, and the output is the user's emotional state information.

[1009] Step 8:

[1010] The server adjusts the tone and content of responses and advertisements based on emotion analysis. For example, if the user is recognized as "tired," the responses will be adjusted to be more relaxing, and advertisements will also be changed to have a similarly relaxing effect. The input is the user's emotional state information, and the output is the adjusted responses and advertisements.

[1011] Step 9:

[1012] The server sends the generated answers and advertisements to the user's terminal. The server sends this data to the terminal via the Internet, and the terminal receives it. The input is the generated answers and advertisements, and the output is the data transfer to the terminal.

[1013] Step 10:

[1014] The terminal displays the received information on the interface, and the user can confirm it. The user can see the provided answers and advertisement content on the interface. The input is the data sent from the server, and the output is the displayed answers and advertisements.

[1015] (Application example 2)

[1016] 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."

[1017] Conventional information provision systems have the problem that answers to user questions are uniform and not personalized to reflect the user's emotions or circumstances. Furthermore, when incorporating advertisements, it is difficult to insert them naturally into the context, which can detract from the user experience. Furthermore, the collected information may not always be reliable, raising concerns about a decline in user trust. To address these issues, technology is needed to tailor answers and advertisements based on the user's emotions and to provide reliable information.

[1018] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, means for sending the generated answer and advertisement to the user, means for analyzing and recognizing the user's emotions, and means for adjusting the answer and advertisement based on the emotion analysis. This makes it possible to provide personalized answers and advertisements according to the user's emotions.

[1019] The "means for receiving a question from a user" is an interface that allows the system to receive a question in text format entered by a user.

[1020] The "means for analyzing questions and extracting topics and keywords" is a function for analyzing user questions using natural language processing technology and identifying major topics and important words and phrases.

[1021] The "means for collecting information related to a question from the Internet" is a program for searching and acquiring information related to a user's question from data sources on the Internet.

[1022] The "means for selecting advertisements relevant to a question" is a function for selecting highly relevant advertisements from a database or advertising platform based on the content of a user's question.

[1023] The "means for combining collected information with selected advertisements to generate a response for the user" is a program that integrates the acquired information with advertisements and creates a response to be provided to the user.

[1024] The "means for transmitting the generated answers and advertisements to the user" is a communication function for delivering the answers and advertisements generated by the system to the user's terminal.

[1025] "Means for analyzing and recognizing user emotions" refers to technology that performs emotion analysis based on questions entered by the user and past data, and identifies the user's current emotional state.

[1026] The "means for adjusting answers and advertisements based on sentiment analysis" refers to an algorithm for changing the content and tone of answers and advertisements provided depending on the emotional state of the user.

[1027] The system that realizes this application combines answers to user questions with advertisements and tailors them based on emotions. The system consists of the following main hardware and software components:

[1028] 1. User Device:

[1029] The device, such as a smartphone or tablet, provides an interface for users to input questions, which are then sent to a server.

[1030] 2. Server:

[1031] It is a central system that runs a text analysis engine, web crawling engine, ad management system, generative AI system, sentiment engine, etc. The server integrates these functions and manages the process.

[1032] Specific software used includes natural language processing libraries (e.g., TextBlob), web crawling libraries (e.g., BeautifulSoup), and machine learning libraries (e.g., TensorFlow).

[1033] 3. Program processing flow:

[1034] When a user types a question, it is sent to the server, which first passes it through a text analysis engine to extract key keywords and topics.

[1035] Next, the web crawling engine gathers relevant information from the internet, gathering information from reliable data sources such as news sites, blogs, and review sites.

[1036] The server accesses the advertisement management system to select advertisements relevant to the query, using criteria including keywords in the query and past user behavior data.

[1037] The AI ​​system combines the collected information with the selected ads to generate answers, which are then adjusted to insert the ads naturally into the context.

[1038] The emotion engine analyzes the user's emotions and adjusts the responses and ads based on the emotions, for example, if the user is in a positive emotional state, it will choose positive ads, and if the user is in a negative emotional state, it will choose ads with a relaxing effect.

[1039] Finally, the generated answers and advertisements are sent to the user's terminal, where the user can view them.

[1040] Examples:

[1041] A user enters a question such as "What's the best new smartphone?" This question is sent to a server, where a text analysis engine extracts keywords such as "smartphone" and "recommended." A web crawling engine collects related review articles and product information, and an advertising management system selects an advertisement that reads, "20% off a new smartphone!" A generative AI system combines the collected information with the advertisement to generate an answer.

[1042] The emotion engine analyzes the user's emotions, and if the user's emotions are positive, the content of the advertisement is adjusted to "We'll also bring you some fun information!" The adjusted answer and advertisement are sent to the user's device, where the user can view them.

[1043] Example prompt sentence:

[1044] "A user asks, 'What's the best new smartphone?' Generate an answer to this question that includes information about the latest smartphones and relevant ads. Be especially positive in your answers and ads, and make the user feel good."

[1045] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1046] Step 1:

[1047] A user types a question into a device. When a user types a question into the device's interface, such as "What's the best new smartphone?", the question is sent to a server. The input is the user's question text, and the output is that this text is sent to the server.

[1048] Step 2:

[1049] The server receives the question and passes it to a text analysis engine. The text analysis engine analyzes the input question and extracts topics and keywords. For example, the keywords "latest smartphone" and "recommendations" are extracted. The input is the user's question text, and the output is the extracted keywords and topics.

[1050] Step 3:

[1051] Based on the extracted keywords, the server uses a web crawling engine to collect related information from the Internet, obtaining data from reliable sources such as news sites, blogs, and review sites. The input is the extracted keywords and topics, and the output is related information data.

[1052] Step 4:

[1053] The server uses an ad management system to select ads relevant to the query. The ad management system searches a database for appropriate ads based on the extracted keywords. For example, an ad for "20% off the latest smartphone" is selected. The input is the extracted keywords, topics, and past user behavior data, and the output is the selected ad.

[1054] Step 5:

[1055] The server combines the collected information with the selected advertisements and generates an answer using a generative AI system. The generative AI system generates text that naturally inserts advertisements into the context of the answer. For example, the generated answer might be, "The latest smartphone is model X, which has received high reviews. Plus, you can get it now for 20% off!" The input is the collected information and the selected advertisements, and the output is the answer text with the advertisements incorporated.

[1056] Step 6:

[1057] The server analyzes the user's input questions and past interaction data to analyze the user's emotions using an emotion engine. The emotion engine identifies the user's current emotional state. The input is the user's question text and past interaction data, and the output is the analyzed emotional state.

[1058] Step 7:

[1059] The server adjusts the content and tone of the answers and advertisements based on the emotional analysis. For example, if the user is in a positive emotional state, it provides positive words and emphasizes the advertisement. Conversely, if the user is in a negative emotional state, it changes the expressions and content to make the user feel more relaxed. The input is the analyzed emotional state and the generated answer text, and the output is the adjusted answer and advertisement text.

[1060] Step 8:

[1061] The server sends the final answer and advertisement to the user's device, which receives it and displays it on the interface. The user can then review the provided answer and advertisement. The input is the adjusted answer and advertisement text, and the output is the display on the user's device.

[1062] 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.

[1063] 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.

[1064] 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.

[1065] [Fourth embodiment]

[1066] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1067] 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.

[1068] 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).

[1069] 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.

[1070] 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.

[1071] 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).

[1072] 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.

[1073] 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.

[1074] 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.

[1075] 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.

[1076] 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.

[1077] 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.

[1078] 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."

[1079] The present invention relates to a generative AI system that incorporates advertisements into answers to questions from users and provides the answers to the users. Hereinafter, an embodiment of this system will be described in detail.

[1080] System Overview

[1081] The system consists of the following elements:

[1082] 1. Means of receiving questions from users

[1083] 2. A method for analyzing questions and extracting topics and keywords

[1084] 3. How to gather information related to your question from the Internet

[1085] 4. How to select ads relevant to your question

[1086] 5. A means of combining collected information with selected ads to generate answers for users.

[1087] 6. Means for sending generated answers and advertisements to users

[1088] Program processing

[1089] First, the user inputs a question into the interface of the generative AI system. For example, they input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[1090] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[1091] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[1092] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[1093] The server combines the collected information with the selected advertisement to generate an answer to be provided to the user. Care is taken to ensure that the advertisement is inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is paired.

[1094] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the user's interface, allowing the user to get a useful answer to their question and view relevant advertisements.

[1095] Specific examples

[1096] Consider what happens when a user asks, "What's the latest smartphone recommendation?"

[1097] The user enters a question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to collect related information from the Internet, retrieving the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from the advertising management system. By combining the collected information with the selected advertisement, the server generates a response that incorporates an advertisement such as "X brand model Y is highly rated as the latest smartphone. Its features are..." in response to a question such as, "X brand model Y is now 20% off!" Finally, the server sends the response and advertisement to the user's device, where the user can view them on the interface.

[1098] As described above, the generative AI system according to the present invention is capable of providing free or reduced-cost information to users while effectively delivering advertisements to advertisers.

[1099] The processing flow will be explained below.

[1100] Step 1:

[1101] The user enters a question into the interface of the generative AI system and presses the send button. For example, the user enters the question, "What is your recommendation for the latest smartphone?"

[1102] Step 2:

[1103] The terminal receives the user's question and sends it to the server using a communication protocol such as an HTTP request.

[1104] Step 3:

[1105] The server receives the question sent by the user and passes the received question as text data to the analysis engine.

[1106] Step 4:

[1107] The server uses a text analysis engine to analyze the content of the question, extracting key keywords such as "smartphone," "latest," and "recommended" to identify the topic of the question.

[1108] Step 5:

[1109] The server launches a web crawling engine to gather information related to the question from the Internet, such as the latest smartphone reviews and product information, selecting only reliable sources.

[1110] Step 6:

[1111] The server accesses the ad management system and selects the most appropriate ad based on the query, for example, selecting an ad campaign related to the latest smartphones, using targeting information specified by the advertiser and past user behavior data.

[1112] Step 7:

[1113] The server combines the collected information with the selected advertisement to generate an answer to be provided to the user. At this time, the advertisement is adjusted so that it is inserted naturally into the context of the answer. For example, in response to the question, "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is combined.

[1114] Step 8:

[1115] The server then sends the generated response and advertisement to the user's device, usually using a communication protocol such as an HTTP response.

[1116] Step 9:

[1117] The terminal receives the answers and advertisements sent from the server and displays them on the user's interface, allowing the user to check them and view the contents of the answers and advertisements.

[1118] Through these steps, the system effectively provides useful answers to users' questions and relevant advertisements.

[1119] Example 1

[1120] 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."

[1121] Conventional information provision systems often lack the accuracy and reliability of answers to user questions. Furthermore, it is difficult to naturally incorporate advertisements into answers, which can detract from the user experience. Furthermore, it is difficult to select appropriate advertisements based on the content of the question, which reduces the effectiveness of advertising.

[1122] 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.

[1123] In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting main keywords and topics, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, and means for transmitting the generated answer and advertisements to the user. This makes it possible to provide highly accurate and reliable answers to user questions and to provide effective information that naturally incorporates advertisements.

[1124] A "user" is a person who uses the system to input a question.

[1125] The "means for receiving a question" is a function that allows the server to obtain a question entered by a user.

[1126] "Means for analyzing questions to extract key keywords and topics" refers to a function that analyzes questions to identify important phrases and themes.

[1127] "Means of collecting information related to the question from the Internet" is a function that collects data related to the question from the web.

[1128] "Means for selecting advertisements" is a function that selects appropriate advertisements based on the content of the question.

[1129] The "means for generating an answer by combining information and advertisements" is a function for generating an answer to be provided to a user using collected information and selected advertisements.

[1130] The "means for transmitting the generated answer and advertisement to the user" is a function for transmitting the generated answer and advertisement to the user's terminal.

[1131] "Means for extracting reliable information" is the function of selecting trustworthy data from the collected information.

[1132] "Means of naturally inserting into the context of the answer" refers to the ability to seamlessly incorporate advertisements into the content of the answer.

[1133] MODE FOR CARRYING OUT THE INVENTION

[1134] The present invention relates to a generation AI system that incorporates advertisements into answers to user questions and provides them to the user. To implement this system, a terminal to which the user connects and a server that analyzes the questions and generates answers are required. A specific embodiment of this system is described in detail below.

[1135] Hardware and software used

[1136] Server: This is the main component that receives questions, analyzes them, collects information, selects ads, generates answers, and sends them. The following software is installed on the server:

[1137] Text Analysis Engine: Analyzes the text of the question and extracts key keywords and topics. Uses Natural Language Processing (NLP) techniques.

[1138] Web Crawl Engine: Automatically crawls specific websites to collect reliable information on the Internet.

[1139] Ad Management System: Targets and selects ads.

[1140] Generative AI model: Generates answers to provide to users based on collected information and selected ads.

[1141] User device: A device that inputs questions and receives and displays answers, such as a PC, smartphone, or tablet, allowing users to interact with the system.

[1142] Explaining program processing in natural language

[1143] First, the user inputs a question into the interface of the generative AI system. For example, they input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[1144] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[1145] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[1146] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[1147] The server combines the collected information with the selected advertisements to generate answers to be provided to the user. It uses a generative AI model to create natural sentences and ensures that the advertisements are inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", it combines an advertisement saying "X brand model Y is now 20% off!"

[1148] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the user's interface, allowing the user to get a useful answer to their question and view relevant advertisements.

[1149] Examples and prompts

[1150] As a concrete example, consider the case where a user asks, "What's the best new smartphone?" The user enters the question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to gather relevant information from the Internet, including the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from an advertising management system. By combining the collected information with the selected advertisement, the server generates a response that incorporates an advertisement, such as "Brand X's Model Y is highly rated as the latest smartphone. Its features are..." in response to a question such as, "Brand X's Model Y is currently 20% off!" Finally, the server sends the response and advertisement to the user's device, where the user can view them through the interface.

[1151] As described above, the generative AI system according to the present invention is a system that integrates the provision of highly accurate and reliable information with effective advertisement delivery.

[1152] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1153] Step 1:

[1154] The user inputs a question into the interface of the generative AI system. As a concrete example, let's assume the user inputs "What's your recommendation for the latest smartphone?" The device then sends this question to the server. The input is the user's question text, and the output is an HTTP request sent to the server.

[1155] Step 2:

[1156] The server receives questions submitted by users. It passes the received questions to a text analysis engine. The text analysis engine analyzes the question text and extracts key keywords and topics. This analysis uses natural language processing (NLP) techniques. The input is the user's question text, and the output is the extracted keywords and topics.

[1157] Step 3:

[1158] The server launches a web crawling engine to collect relevant information from the Internet. Specifically, it crawls news sites, blogs, review sites, etc. to retrieve articles and reviews about the latest smartphones and recommended models. The crawling engine scrapes the page content from each site and stores reliable information in a database. The input is the extracted keywords, and the output is the collected related information.

[1159] Step 4:

[1160] The server simultaneously accesses the ad management system and selects the most appropriate ad for the query. Specifically, the server searches for relevant ad campaigns based on keywords such as "smartphone" or "latest model." This is done using targeting information provided by the advertiser and past user behavior data. The input is the extracted keywords and topics, and the output is the selected ad.

[1161] Step 5:

[1162] The server combines the collected information with the selected advertisements to generate an answer to be provided to the user. A generative AI model is used to create the optimal sentence for the user's question. This sentence incorporates the collected reviews and product information, and is designed to insert the selected advertisements naturally (without any sense of incongruity). The input is the collected information and the selected advertisements, and the output is the generated answer.

[1163] Step 6:

[1164] The server sends the generated answers and advertisements to the user's terminal. Specifically, it sends the generated text data back to the user's terminal in the form of an HTTP response. The terminal receives this and displays it on the user's interface. The input is the generated answers and advertisements, and the output is the text displayed on the user's interface.

[1165] Step 7:

[1166] The user checks the answers and advertisements displayed on the device. Specifically, they read the answers on the interface and view the related advertisements. This allows the user to obtain useful information about the question and simultaneously view selected advertisements. The input is the displayed answers and advertisements, and the output is the user's browsing behavior.

[1167] (Application example 1)

[1168] 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."

[1169] Conventional generative AI systems have had difficulty gathering accurate information and inserting advertisements naturally when generating answers to user questions and generating advertisements. Furthermore, there has been no interactive answering system that combines visual and audio information for smart devices with the ability to display information in the user's field of view in real time. As a result, improving the user experience has been a challenge.

[1170] 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.

[1171] In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, and means for transmitting the generated answer and advertisement to the user terminal and displaying them on the smart device.

[1172] This will enable accurate information and relevant advertisements to be provided to users in real time, and enable interactive information provision through visual and audio, improving the user experience.

[1173] The "means for receiving a question from a user" refers to a technical means for obtaining a question entered by a user via voice or text through a digital device.

[1174] The "means for analyzing the question and extracting topics and keywords" refers to a technical means for analyzing the received question using natural language processing technology and identifying the main topics and related keywords.

[1175] "Means for collecting information related to the question from the Internet" means technical means for searching and collecting information related to the question from reliable websites and databases on the Internet.

[1176] The "means for selecting advertisements relevant to the question" refers to a technical means for selecting advertisements that are highly relevant based on the content of the question and displaying them to the user.

[1177] "Means for combining the collected information with the selected advertisements to generate a response for the user" refers to technical means for integrating the collected information with the selected advertisements to generate a response for the user in a natural format.

[1178] "Means for transmitting the generated answers and advertisements to a user terminal and displaying them on a smart device" refers to technical means for transmitting the generated answers and advertisements to a user's digital device and displaying them on a smart device such as a smartphone or smart glasses.

[1179] The present invention relates to a generative AI system that incorporates advertisements into answers to questions posed by users and displays the answers and advertisements on smart devices. The following describes in detail the embodiments of the present invention.

[1180] System Configuration

[1181] The system consists of the following main components:

[1182] 1. Means of receiving questions from users

[1183] 2. Means for analyzing the question and extracting topics and keywords

[1184] 3. How to gather information related to your question from the Internet

[1185] 4. Means for selecting advertisements relevant to the question

[1186] 5. Means for combining the collected information with the selected advertisement to generate a response for the user.

[1187] 6. Means for transmitting the generated answers and advertisements to the user terminal and displaying them on the smart device

[1188] Hardware and Software Use

[1189] Hardware:

[1190] Smart glasses: equipped with cameras and audio capture capabilities

[1191] software:

[1192] Google Cloud Vision API

[1193] Google Speech Recognition API

[1194] OpenAI GPT-3 API

[1195] Data processing and calculation

[1196] 1. Receiving and parsing questions:

[1197] The system captures questions spoken by users into the smart glasses as audio and converts them into text using the Google Speech Recognition API, recognizes objects in the user's line of sight using the Google Cloud Vision API, and analyzes the question along with extracted topics and keywords.

[1198] 2. Information and Advertising Collection:

[1199] The server searches the Internet to gather reliable information related to the question. The web crawling engine crawls news sites, blogs, review sites, etc. to obtain the latest information. Meanwhile, it accesses the ad management system to select the most suitable ad for the question. This ad selection takes into account the question's topic and keywords, past user behavior data, etc.

[1200] 3. Generate and send the answer:

[1201] The collected information is integrated with the selected advertisements to generate answers for the user in a natural format. This process is performed using the OpenAI GPT-3 API. The generated answers and advertisements are sent to the user's device and displayed on the smart glasses.

[1202] Specific examples

[1203] A user is looking at the latest smartphone exhibit and asks, "What are the features of this smartphone?"

[1204] The smartphone is recognized from the captured image, and the user's question is converted into text using voice recognition.

[1205] Based on the question and object recognition results, prompts are sent to GPT-3 to generate answers and relevant ads.

[1206] Example prompt sentence:

[1207] Q: What are the features of the latest smartphones?

[1208] Object: Smartphone

[1209] Please provide your answer and relevant ads:

[1210] This improvement allows users to obtain quick and accurate information through questions and answers, and at the same time, to receive relevant advertisements in a natural way.

[1211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1212] Step 1:

[1213] User question input

[1214] How it works: A user speaks a question into the smart glasses, for example, "What are the features of this smartphone?"

[1215] Input: User's voice data

[1216] Output: Captured audio data

[1217] Step 2:

[1218] Speech-to-text conversion

[1219] How it works: Converts user voice data into text using the Google Speech Recognition API.

[1220] Input: Captured audio data

[1221] Output: Texted question (e.g., "What are the features of this smartphone?")

[1222] Step 3:

[1223] Eye tracking and object recognition

[1224] How it works: The smart glasses' camera is used to capture objects in the user's line of sight, and the object is recognized using the Google Cloud Vision API.

[1225] Input: Image data captured by the camera

[1226] Output: Recognized object (e.g. "smartphone")

[1227] Step 4:

[1228] Parsing the query and object recognition results

[1229] How it works: The server analyzes the textual questions and object recognition results to extract key topics and keywords.

[1230] Input: Texted question, recognized object

[1231] Output: Extracted topics and keywords (e.g., "smartphone" and "features")

[1232] Step 5:

[1233] Gathering relevant information

[1234] How it works: The server searches the internet to gather reliable information related to your question, grabbing the data it needs from news sites, blogs, review sites, etc.

[1235] Input: Extracted topics and keywords

[1236] Output: Collected relevant information (e.g., reviews of the latest smartphones)

[1237] Step 6:

[1238] Selection of relevant advertisements

[1239] Operation: The server accesses the ad management system and selects relevant ads based on topics and keywords.

[1240] Input: Extracted topics and keywords

[1241] Output: Selected advertisements (e.g. smartphone discount campaigns)

[1242] Step 7:

[1243] Answer and Ad Generation

[1244] How it works: The server combines the collected information with the selected ads to generate a natural-looking answer for the user. This process is performed using the OpenAI GPT-3 API.

[1245] Input: Collected relevant information, selected advertisements

[1246] Output: Generated answer and advertisement (e.g., "X brand's model Y is highly rated as the latest smartphone. Features include... 20% off now!")

[1247] Step 8:

[1248] Sending and displaying responses and advertisements

[1249] How it works: The server sends the generated answers and advertisements to the user's smart glasses and displays them for the user to see in real time.

[1250] Input: Generated answers and advertisements

[1251] Output: Answers and advertisements displayed on the smart glasses (e.g., users can view them through the glasses)

[1252] 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.

[1253] The present invention relates to a generative AI system that incorporates advertisements into answers to user questions and provides them to the user. Furthermore, the present invention provides a system that combines an emotion engine that recognizes the user's emotions and adjusts the answers and advertisements based on the emotions. Below, an embodiment of this system will be described in detail.

[1254] System Overview

[1255] The system consists of the following elements:

[1256] 1. Means of receiving questions from users

[1257] 2. A means of parsing questions to extract topics and keywords

[1258] 3. How to gather information related to your question from the Internet

[1259] 4. How to select ads relevant to your question

[1260] 5. A means of combining collected information with selected ads to generate answers for users.

[1261] 6. Means for sending generated answers and advertisements to users

[1262] 7. Emotion engine that analyzes and recognizes user emotions

[1263] 8. A way to tailor responses and ads based on an emotion engine

[1264] Program processing

[1265] First, the user inputs a question into the interface of the generative AI system. For example, they might input a question like, "What's your recommendation for the latest smartphone?" The user's device then sends this question to the server.

[1266] The server receives the question submitted by the user and passes it to a text analysis engine, which extracts key keywords such as "smartphone" and "recommended" and identifies topics to understand the intent of the question.

[1267] The server then launches a web crawling engine to gather relevant information from the Internet, searching news sites, blogs, review sites, and other sources to retrieve reliable information, including reviews and product information for the latest smartphones.

[1268] At the same time, the server accesses the advertising management system and selects the most appropriate advertisement for the query. For example, it selects relevant advertising campaigns based on keywords such as "smartphone" or "latest model." Ad selection also utilizes targeting information specified by the advertiser and past user behavior data.

[1269] The server then combines the collected information with the selected advertisement to generate an answer to be provided to the user. Care is taken to ensure that the advertisement is inserted naturally into the context of the answer. For example, in response to the answer "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is paired.

[1270] Furthermore, the server uses an emotion engine to analyze the user's emotions. For example, it recognizes the user's emotions from the context when the user enters a question and from past interaction data. Based on the emotion engine, it adjusts the tone and content of answers and advertisements. For example, if the user is emotionally exhausted, it provides answers and advertisements that are more relaxing.

[1271] Finally, the server sends the generated answer and advertisement to the user's device, which receives it and displays it on the interface, allowing the user to view the answer and advertisement content.

[1272] Specific examples

[1273] Consider what happens when a user asks, "What's the latest smartphone recommendation?"

[1274] The user enters a question and the device sends it to the server. The server receives the question and uses a text analysis engine to extract keywords such as "smartphone" and "latest model." The server then uses a web crawling engine to collect related information from the Internet, retrieving the latest smartphone review articles and product information. At the same time, the server selects advertisements for new product campaigns from the advertising management system. By combining the collected information with the selected advertisements, for example, in response to a question such as "X brand model Y is highly rated as the latest smartphone. Its features are...", the server generates a response incorporating an advertisement such as "X brand model Y is now 20% off!"

[1275] Furthermore, if the user's emotion is "excited," the content will be adjusted to emphasize that reaction. Or, if the user is recognized as "tired," words or advertisements with a relaxing effect will be selected.

[1276] Finally, the server sends this response and the advertisement to the user's terminal, where the user confirms it in the interface.

[1277] As described above, the generative AI system of the present invention provides users with free or reduced-cost information while effectively delivering ads to advertisers. It also provides a more personalized experience by adjusting responses and ads based on the user's emotions.

[1278] The processing flow will be explained below.

[1279] Step 1:

[1280] The user enters a question into the interface of the generative AI system and presses the send button. For example, the user enters the question, "What is your recommendation for the latest smartphone?"

[1281] Step 2:

[1282] The terminal receives the user's question and sends it to the server using a communication protocol such as an HTTP request.

[1283] Step 3:

[1284] The server receives the question sent by the user and passes the received question as text data to the analysis engine.

[1285] Step 4:

[1286] The server uses a text analysis engine to analyze the content of the question, extracting key keywords such as "smartphone," "latest," and "recommended" to identify the topic of the question.

[1287] Step 5:

[1288] The server uses an emotion engine to analyze emotions from the user's input text and past behavioral data. Based on the emotion analysis algorithm, the server identifies the user's emotional state (e.g., joy, excitement, sadness, fatigue).

[1289] Step 6:

[1290] The server launches a web crawling engine to gather information related to the question from the Internet, such as the latest smartphone reviews and product information, selecting only reliable sources.

[1291] Step 7:

[1292] The server accesses the ad management system and selects the most appropriate ad based on the query, for example, selecting an ad campaign related to the latest smartphones, using targeting information specified by the advertiser and past user behavior data.

[1293] Step 8:

[1294] The server combines the collected information with the selected advertisements to generate a response to be presented to the user. The tone of the response and the content of the advertisement are adjusted based on the user's emotions. For example, if the user is "excited," the server uses expressions that enhance excitement and makes the advertisement relevant to that emotion.

[1295] Step 9:

[1296] The server then sends the generated response and advertisement to the user's device, usually using a communication protocol such as an HTTP response.

[1297] Step 10:

[1298] The device receives the answers and advertisements sent from the server and displays them on the user's interface in a format that takes into consideration the user's feelings. The user can confirm the display and view the content of the answers and advertisements.

[1299] Through these steps, the system effectively provides useful answers to users' questions and relevant advertisements, while also providing a personalized experience that responds to the user's emotional state.

[1300] Example 2

[1301] 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."

[1302] Conventional question-answering systems are limited to providing answers to user questions and lack a way to effectively combine them with advertisements. Furthermore, they lack the ability to analyze user sentiment and tailor answers and advertisements accordingly, preventing an improved user experience. Therefore, a system that provides personalized advertisements and answers tailored to user needs was needed.

[1303] 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.

[1304] In this invention, the server includes means for receiving a question from a user, means for analyzing the question to extract topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for generating an answer for the user by combining the collected information and the selected advertisements, means for transmitting the generated answer and advertisement to the user, means for analyzing and recognizing user emotions, and means for adjusting the answer and advertisement based on the emotion analysis, thereby making it possible to provide personalized answers and advertisements according to the user's needs and emotions.

[1305] The "means for receiving questions from users" is an interface that allows the server to receive questions input by users via their terminals.

[1306] The "means for analyzing the question and extracting topics and keywords" refers to a system that analyzes the question received by the server using technology such as a text analysis engine and extracts the subject matter and important words of the question content.

[1307] "Means for collecting information related to the question from the Internet" refers to a system in which a server uses a web crawling engine or the like to search for and collect information related to the question from news sites, blogs, review sites, etc. on the Internet.

[1308] The "means for selecting an advertisement relevant to the question" refers to a process in which the server uses an advertisement management system to select an advertisement that is most suitable for the content of the question.

[1309] "Means for combining the collected information with the selected advertisements to generate a response for the user" refers to a technology for integrating the information collected by the server with the selected advertisements to generate a response for the user.

[1310] The "means for transmitting the generated answer and advertisement to the user" is a system for transmitting the answer and advertisement generated by the server to the user's terminal and displaying them on the user interface.

[1311] "Means for analyzing and recognizing user emotions" refers to technology that allows the server to analyze user input and past interaction data to recognize the user's current emotional state.

[1312] "Means for adjusting the answers and advertisements based on the sentiment analysis" refers to a process for personalizing the content and wording of answers and advertisements according to the emotional state of the user as recognized by the server.

[1313] The generative AI system of the present invention generates answers incorporating advertisements to user questions and provides personalized answers by analyzing the user's emotions. This system is composed of the following main components:

[1314] 1. User terminal: An interface is provided for users to input questions. For example, a device such as a smartphone or computer can be used.

[1315] 2. Server: Plays a central role in performing various processes and uses the following software and hardware:

[1316] Text analysis engine: Analyzes questions and extracts topics and keywords.

[1317] Web crawling engine: Collects information related to your question from the internet.

[1318] Advertisement management system: Selects the best advertisement for the question.

[1319] Emotion engine: Analyzes and recognizes user emotions.

[1320] Answer generation module: Generates answers by combining collected information with selected advertisements.

[1321] 3. Communication: Network communication is required to send and receive data between the user device and the server. This is achieved via an Internet connection.

[1322] Hardware and software used

[1323] User device: A personal computer, smartphone, tablet, etc. connected to the Internet.

[1324] Server: A physical or virtual server with high-performance computing resources, with the following software installed:

[1325] Text analysis engines: Libraries for natural language processing (e.g. NLTK, spaCy, etc.).

[1326] Web crawling engines: Tools for web scraping (e.g. Beautiful Soup, Scrapy, etc.).

[1327] Ad Management Systems: Ad databases and targeting algorithms (e.g., Google Ad Manager).

[1328] Emotion engine: An emotion analysis tool that uses facial recognition and text mining technology (e.g., IBM Watson, Microsoft Azure Emotion API, etc.).

[1329] Answer generation module: Utilizes generative AI models (e.g., GPT-3).

[1330] Specific examples

[1331] For example, consider a scenario in which a user inputs the question "What's the latest smartphone recommendation?" into a generative AI system.

[1332] 1. The user inputs a question into the interface, and the user terminal sends this input to the server.

[1333] 2. The server receives the question and uses a text analysis engine to extract the main keywords "smartphone" and "recommended."

[1334] 3. The server then launches a web crawling engine to gather reliable information about the latest smartphones from news sites and blogs across the Internet.

[1335] 4. At the same time, the server accesses the ad management system and selects relevant ads based on the collected keywords and user attributes. For example, it selects an ad for a 20% discount on model Y of brand X during a campaign.

[1336] 5. The server combines the collected information with the selected advertisement, and incorporates an advertisement that reads, "X brand model Y is highly rated as the latest smartphone. Its features are..." into the response, "X brand model Y is now 20% off!"

[1337] 6. The server uses the emotion engine to hypothesize the user's current emotional state. For example, it recognizes that the user is "excited" based on the speed at which the question is typed and past interactions.

[1338] 7. The server further adjusts the tone and content of the responses and ads based on sentiment analysis: if the user is "excited," it uses language that emphasizes that sentiment.

[1339] 8. Finally, the server sends the generated answer and advertisement to the user's terminal, where the user can view the content through the interface.

[1340] For example, the prompt is:

[1341] What's your recommendation for the latest smartphone?

[1342] In this way, the generative AI system of the present invention can provide personalized answers and advertisements that match the user's needs and emotions, thereby improving the user experience and maximizing the effectiveness of advertisements.

[1343] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1344] Step 1:

[1345] The user inputs a question into the interface. For example, the user inputs a question such as "What is the latest smartphone recommended?" The input question is stored on the device as string data.

[1346] Step 2:

[1347] The terminal sends the entered question to the server. The terminal uses a transmission protocol to send the question as a string of data to the server. The input is the user's question, and the output is the transfer of the question data to the server.

[1348] Step 3:

[1349] The server receives the question and passes it to the text analysis engine. The analysis engine receives the question that arrives at the server and extracts the main keywords and topics of the question. For example, keywords such as "smartphone" and "recommended" are extracted. The input is the user's question data, and the output is the extracted keywords and topics.

[1350] Step 4:

[1351] The server starts a web crawling engine to gather information related to the question from the Internet. It uses a search engine API to retrieve related news articles, review sites, blog posts, etc. For example, "latest smartphone review articles" or "product information." The input is the extracted keywords, and the output is the data of related web pages.

[1352] Step 5:

[1353] The server accesses the advertising management system and selects the advertisement that best suits the query. The server uses a targeting algorithm to select advertisements related to "smartphones" and "latest models" from the advertising database. For example, it selects a campaign advertisement such as "X brand Y model is now 20% off!" The input is the extracted keywords and user attribute data, and the output is the selected advertising information.

[1354] Step 6:

[1355] The server combines the collected information with the selected advertisement to generate an answer. The answer generation module uses text generation technology to create an answer based on the collected information and inserts the advertisement naturally. For example, to the question, "X brand model Y is highly rated as the latest smartphone. Its features are...", an advertisement such as "X brand model Y is now 20% off!" is added. The input is the collected information and the selected advertisement, and the output is the generated answer.

[1356] Step 7:

[1357] The server uses an emotion engine to analyze the user's emotions. It determines the user's emotional state, such as whether they are "excited" or "tired," based on past interaction data and contextual analysis of input. The input is the user's past data and current question data, and the output is the user's emotional state information.

[1358] Step 8:

[1359] The server adjusts the tone and content of responses and advertisements based on emotion analysis. For example, if the user is recognized as "tired," the responses will be adjusted to be more relaxing, and advertisements will also be changed to have a similarly relaxing effect. The input is the user's emotional state information, and the output is the adjusted responses and advertisements.

[1360] Step 9:

[1361] The server sends the generated answers and advertisements to the user's terminal. The server sends this data to the terminal via the Internet, and the terminal receives it. The input is the generated answers and advertisements, and the output is the data transfer to the terminal.

[1362] Step 10:

[1363] The terminal displays the received information on the interface, and the user can confirm it. The user can see the provided answers and advertisement content on the interface. The input is the data sent from the server, and the output is the displayed answers and advertisements.

[1364] (Application example 2)

[1365] 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."

[1366] Conventional information provision systems have the problem that answers to user questions are uniform and not personalized to reflect the user's emotions or circumstances. Furthermore, when incorporating advertisements, it is difficult to insert them naturally into the context, which can detract from the user experience. Furthermore, the collected information may not always be reliable, raising concerns about a decline in user trust. To address these issues, technology is needed to tailor answers and advertisements based on the user's emotions and to provide reliable information.

[1367] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving a question from a user, means for analyzing the question and extracting topics and keywords, means for collecting information related to the question from the Internet, means for selecting advertisements related to the question, means for combining the collected information with the selected advertisements to generate an answer for the user, means for sending the generated answer and advertisement to the user, means for analyzing and recognizing the user's emotions, and means for adjusting the answer and advertisement based on the emotion analysis. This makes it possible to provide personalized answers and advertisements according to the user's emotions.

[1368] The "means for receiving a question from a user" is an interface that allows the system to receive a question in text format entered by a user.

[1369] The "means for analyzing questions and extracting topics and keywords" is a function for analyzing user questions using natural language processing technology and identifying major topics and important words and phrases.

[1370] The "means for collecting information related to a question from the Internet" is a program for searching and acquiring information related to a user's question from data sources on the Internet.

[1371] The "means for selecting advertisements relevant to a question" is a function for selecting highly relevant advertisements from a database or advertising platform based on the content of a user's question.

[1372] The "means for combining collected information with selected advertisements to generate a response for the user" is a program that integrates the acquired information with advertisements and creates a response to be provided to the user.

[1373] The "means for transmitting the generated answers and advertisements to the user" is a communication function for delivering the answers and advertisements generated by the system to the user's terminal.

[1374] "Means for analyzing and recognizing user emotions" refers to technology that performs emotion analysis based on questions entered by the user and past data, and identifies the user's current emotional state.

[1375] The "means for adjusting answers and advertisements based on sentiment analysis" refers to an algorithm for changing the content and tone of answers and advertisements provided depending on the emotional state of the user.

[1376] The system that realizes this application combines answers to user questions with advertisements and tailors them based on emotions. The system consists of the following main hardware and software components:

[1377] 1. User Device:

[1378] The device, such as a smartphone or tablet, provides an interface for users to input questions, which are then sent to a server.

[1379] 2. Server:

[1380] It is a central system that runs a text analysis engine, web crawling engine, ad management system, generative AI system, sentiment engine, etc. The server integrates these functions and manages the process.

[1381] Specific software used includes natural language processing libraries (e.g., TextBlob), web crawling libraries (e.g., BeautifulSoup), and machine learning libraries (e.g., TensorFlow).

[1382] 3. Program processing flow:

[1383] When a user types a question, it is sent to the server, which first passes it through a text analysis engine to extract key keywords and topics.

[1384] Next, the web crawling engine gathers relevant information from the internet, gathering information from reliable data sources such as news sites, blogs, and review sites.

[1385] The server accesses the advertisement management system to select advertisements relevant to the query, using criteria including keywords in the query and past user behavior data.

[1386] The AI ​​system combines the collected information with the selected ads to generate answers, which are then adjusted to insert the ads naturally into the context.

[1387] The emotion engine analyzes the user's emotions and adjusts the responses and ads based on the emotions, for example, if the user is in a positive emotional state, it will choose positive ads, and if the user is in a negative emotional state, it will choose ads with a relaxing effect.

[1388] Finally, the generated answers and advertisements are sent to the user's terminal, where the user can view them.

[1389] Examples:

[1390] A user enters a question such as "What's the best new smartphone?" This question is sent to a server, where a text analysis engine extracts keywords such as "smartphone" and "recommended." A web crawling engine collects related review articles and product information, and an advertising management system selects an advertisement that reads, "20% off a new smartphone!" A generative AI system combines the collected information with the advertisement to generate an answer.

[1391] The emotion engine analyzes the user's emotions, and if the user's emotions are positive, the content of the advertisement is adjusted to "We'll also bring you some fun information!" The adjusted answer and advertisement are sent to the user's device, where the user can view them.

[1392] Example prompt sentence:

[1393] "A user asks, 'What's the best new smartphone?' Generate an answer to this question that includes information about the latest smartphones and relevant ads. Be especially positive in your answers and ads, and make the user feel good."

[1394] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1395] Step 1:

[1396] A user types a question into a device. When a user types a question into the device's interface, such as "What's the best new smartphone?", the question is sent to a server. The input is the user's question text, and the output is that this text is sent to the server.

[1397] Step 2:

[1398] The server receives the question and passes it to a text analysis engine. The text analysis engine analyzes the input question and extracts topics and keywords. For example, the keywords "latest smartphone" and "recommendations" are extracted. The input is the user's question text, and the output is the extracted keywords and topics.

[1399] Step 3:

[1400] Based on the extracted keywords, the server uses a web crawling engine to collect related information from the Internet, obtaining data from reliable sources such as news sites, blogs, and review sites. The input is the extracted keywords and topics, and the output is related information data.

[1401] Step 4:

[1402] The server uses an ad management system to select ads relevant to the query. The ad management system searches a database for appropriate ads based on the extracted keywords. For example, an ad for "20% off the latest smartphone" is selected. The input is the extracted keywords, topics, and past user behavior data, and the output is the selected ad.

[1403] Step 5:

[1404] The server combines the collected information with the selected advertisements and generates an answer using a generative AI system. The generative AI system generates text that naturally inserts advertisements into the context of the answer. For example, the generated answer might be, "The latest smartphone is model X, which has received high reviews. Plus, you can get it now for 20% off!" The input is the collected information and the selected advertisements, and the output is the answer text with the advertisements incorporated.

[1405] Step 6:

[1406] The server analyzes the user's input questions and past interaction data to analyze the user's emotions using an emotion engine. The emotion engine identifies the user's current emotional state. The input is the user's question text and past interaction data, and the output is the analyzed emotional state.

[1407] Step 7:

[1408] The server adjusts the content and tone of the answers and advertisements based on the emotional analysis. For example, if the user is in a positive emotional state, it provides positive words and emphasizes the advertisement. Conversely, if the user is in a negative emotional state, it changes the expressions and content to make the user feel more relaxed. The input is the analyzed emotional state and the generated answer text, and the output is the adjusted answer and advertisement text.

[1409] Step 8:

[1410] The server sends the final answer and advertisement to the user's device, which receives it and displays it on the interface. The user can then review the provided answer and advertisement. The input is the adjusted answer and advertisement text, and the output is the display on the user's device.

[1411] 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.

[1412] 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.

[1413] 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.

[1414] 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.

[1415] 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.

[1416] 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.

[1417] 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).

[1418] 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.

[1419] 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."

[1420] 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.

[1421] 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).

[1422] 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.

[1423] 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.

[1424] 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.

[1425] 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.

[1426] 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.

[1427] 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.

[1428] 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.

[1429] 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.

[1430] 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.

[1431] 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.

[1432] The following is further disclosed regarding the above embodiment.

[1433] (Claim 1)

[1434] means for receiving a query from a user;

[1435] means for analyzing the question to extract topics and keywords;

[1436] a means for collecting information related to the question from the Internet;

[1437] means for selecting advertisements relevant to said query;

[1438] means for combining the collected information with the selected advertisements to generate a response for the user;

[1439] The system includes means for transmitting the generated answers and advertisements to a user.

[1440] (Claim 2)

[1441] 10. The system of claim 1, further comprising means for analyzing the collected information to extract reliable information.

[1442] (Claim 3)

[1443] 10. The system of claim 1, further comprising means for inserting the advertisement naturally into the context of the answer when combined.

[1444] "Example 1"

[1445] (Claim 1)

[1446] means for receiving a query from a user;

[1447] means for analyzing the question to extract key keywords and topics;

[1448] a means for collecting information related to the question from the Internet;

[1449] means for selecting advertisements relevant to said query;

[1450] means for combining the collected information with the selected advertisements to generate a response for the user;

[1451] The system includes means for transmitting the generated answers and advertisements to a user.

[1452] (Claim 2)

[1453] 10. The system of claim 1, further comprising means for analyzing the collected information to extract reliable information.

[1454] (Claim 3)

[1455] 10. The system of claim 1, further comprising means for inserting the advertisement naturally into the context of the answer when combined.

[1456] "Application Example 1"

[1457] (Claim 1)

[1458] means for receiving a query from a user;

[1459] means for analyzing the question to extract topics and keywords;

[1460] a means for collecting information related to the question from the Internet;

[1461] means for selecting advertisements relevant to said query;

[1462] means for combining the collected information with the selected advertisements to generate a response for the user;

[1463] The system includes a means for transmitting the generated answers and advertisements to a user terminal and displaying them on a smart device.

[1464] (Claim 2)

[1465] 10. The system of claim 1, further comprising means for analyzing the collected information to extract reliable information.

[1466] (Claim 3)

[1467] 10. The system of claim 1, further comprising means for inserting the advertisement naturally into the context of the answer when combined.

[1468] "Example 2: Combining Emotion Engines"

[1469] (Claim 1)

[1470] means for receiving a query from a user;

[1471] means for analyzing the question to extract topics and keywords;

[1472] a means for collecting information related to the question from the Internet;

[1473] means for selecting advertisements relevant to said query;

[1474] means for combining the collected information with the selected advertisements to generate a response for the user;

[1475] means for transmitting the generated answers and advertisements to a user;

[1476] means for analyzing and recognizing user emotions;

[1477] The system includes means for adjusting the responses and advertisements based on the sentiment analysis.

[1478] (Claim 2)

[1479] 10. The system of claim 1, further comprising means for analyzing the collected information to extract reliable information.

[1480] (Claim 3)

[1481] 10. The system of claim 1, further comprising means for inserting the advertisement naturally into the context of the answer when combined.

[1482] "Application example 2 when combining emotion engines"

[1483] The following is a new claim that adds the distinctive features of the application example to the original claim:

[1484] (Claim 1)

[1485] means for receiving a query from a user;

[1486] means for analyzing the question to extract topics and keywords;

[1487] a means for collecting information related to the question from the Internet;

[1488] means for selecting advertisements relevant to said query;

[1489] means for combining the collected information with the selected advertisements to generate a response for the user;

[1490] means for transmitting the generated answers and advertisements to a user;

[1491] means for analyzing and recognizing user emotions;

[1492] The system includes means for tailoring responses and advertisements based on said sentiment analysis.

[1493] (Claim 2)

[1494] 10. The system of claim 1, further comprising means for analyzing the collected information to extract reliable information.

[1495] (Claim 3)

[1496] 10. The system of claim 1, further comprising means for inserting the advertisement naturally into the context of the answer when combined. [Explanation of symbols]

[1497] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a query from a user; means for analyzing the question to extract topics and keywords; a means for collecting information related to the question from the Internet; means for selecting advertisements relevant to said query; means for combining the collected information with the selected advertisements to generate a response for the user; The system includes means for transmitting the generated answers and advertisements to a user.

2. The system of claim 1 further comprising means for analyzing the collected information to extract reliable information.

3. The system of claim 1 , further comprising means for inserting the advertisement naturally into the context of the answer when combined.

Images