System

Abstract

A system is provided.SOLUTION: [A system including a means in which a user inputs a feature of a product or service and an attribute of a target user, a means in which a terminal formats the input information and transmits the formatted information to a server, a means in which the server receives the information, performs natural language processing, and obtains an analysis result, a means in which the server refers to the attribute of the target user and generates a catch-phrase using a catch-phrase generation algorithm, a means in which the server transmits the generated catch-phrase to the terminal, and a means in which the terminal displays the catch-phrase 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] In modern society, companies and individuals need compelling slogans to effectively communicate their products and services to the market. However, creating a slogan requires specialized knowledge and skills, and often consumes a lot of time and effort. It is also difficult to accurately generate effective slogans tailored to target users. To solve these problems, a system is needed that can automatically and efficiently generate slogans that are optimal for target users. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means: A system including a means for a user to input the characteristics of a product or service and the attributes of a target user, a means for a terminal to format the input information and send it to a server, a means for the server to receive the information, perform natural language processing, and obtain an analysis result, a means for the server to reference the attributes of the target user and generate a catchy slogan using a catchy slogan generation algorithm, a means for the server to send the generated catchy slogan to the terminal, and a means for the terminal to display the catchy slogan to the user, allows a user to easily generate a catchy slogan suitable for a target user. This system is expected to significantly reduce the time and effort required to create a catchy slogan and increase marketing effectiveness.

[0006] A "user" is an entity that inputs product / service characteristics and target user attributes into the system.

[0007] A "terminal" is a device used by a user that formats and transmits input information to a server.

[0008] The "server" is a central system that receives information sent from the terminals, analyzes it, and generates catchphrases.

[0009] "Features of a product or service" is information that indicates the characteristics and appealing points of a service or product.

[0010] "Target user attributes" refers to information such as the age, gender, and interests of the target users.

[0011] "Formatting" refers to arranging input information into a specific form.

[0012] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[0013] "Analysis results" are structured data of information obtained through natural language processing.

[0014] A "catchphrase generation algorithm" is a calculation method or procedure for generating a catchphrase based on input information.

[0015] A "machine learning model" is a type of algorithm that learns patterns from data and makes predictions and classifications.

[0016] An "HTTP POST request" is a request format that uses the web communication protocol to send data to a server.

[0017] An "HTTP response" is response data sent from a server to a terminal. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention relates to a system for automatically generating catchy slogans based on the characteristics of a product or service selected by a user and the attributes of a target user. As an embodiment of the invention, the specific operation of the system will be described below.

[0040] System configuration

[0041] This system is broadly divided into the following three components:

[0042] 1. Users

[0043] 2. Terminal

[0044] 3. Server

[0045] System Operation Overview

[0046] 1. The user enters information

[0047] The user specifies the features and selling points of the product or service. They also input the attributes of the target users (e.g., age, gender, interests, etc.). For example, the user can input features of a new diet supplement such as "short-term results" and "100% natural ingredients," and specify "health-conscious women in their 30s" as the target users.

[0048] 2. The device sends the information to the server

[0049] The terminal formats the information the user enters and sends it to the server, for example in the following format:

[0050] json

[0051] {

[0052] "features": ["short-term results", "100% natural ingredients"],

[0053] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0054] }

[0055] 3. The server starts processing

[0056] The server receives the information sent from the device, then analyzes the product / service features using natural language processing tools to extract important keywords, and then references the target user's attribute data to set conditions for generating an appropriate catchphrase.

[0057] 4. Generate a catchphrase

[0058] The server combines the data obtained through natural language processing with the target profile to run a catchphrase generation algorithm. For example, a machine learning model is used to generate a catchphrase such as "Become beautiful in a short time, in a healthy way, with the power of nature."

[0059] 5. Send the generated tagline to the device

[0060] The server sends the generated catchphrase to the terminal as an HTTP response.

[0061] 6. The device displays the tagline to the user.

[0062] The terminal visually displays the received tagline to the user, for example, the text "Get healthy and beautiful in a short time, with the power of nature" on the page of the web browser.

[0063] Specific examples

[0064] 1. Input example

[0065] Product and service features: "Short-term results" "100% natural ingredients"

[0066] Target users: "Health-conscious women in their 30s"

[0067] 2. Example of generated results

[0068] Catchphrase: "Be healthy and beautiful in a short time, with the power of nature."

[0069] In this way, this system allows users to efficiently and effectively generate catchy slogans that are appropriate for target users, significantly reducing the time and effort required to create catchy slogans and improving marketing effectiveness.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] The user inputs the characteristics of the product / service and the attributes of the target user. The user inputs the specific characteristics and selling points of the product / service into a dedicated input form. At the same time, the user also inputs attribute information of the target user, such as age, gender, and interests.

[0073] Step 2:

[0074] The device formats the input information and sends it to the server. The device (such as a computer or smartphone used by the user) converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[0075] Step 3:

[0076] The server receives the information and begins the analysis process. The server analyzes the received HTTP POST request and extracts the product / service features and target user attributes.

[0077] Step 4:

[0078] The server performs natural language processing (NLP). The server analyzes the product features using natural language processing tools (e.g., tokenization, part-of-speech tagging) to identify important keywords and phrases.

[0079] Step 5:

[0080] The server references the target user's attribute information. The server then references a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[0081] Step 6:

[0082] The server applies a catchphrase generation algorithm. Based on the keywords obtained through natural language processing and the attributes of the target user, the server uses a catchphrase generation algorithm (e.g., machine learning model, rule-based model) to generate an appropriate catchphrase.

[0083] Step 7:

[0084] The server sends the generated catchphrase to the terminal. The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0085] Step 8:

[0086] The device displays the catchphrase to the user. The device parses the HTTP response sent from the server and displays the catchphrase content in a format that is easy for the user to read. For example, the generated catchphrase "Be healthy, beautiful in a short time, with the power of nature" is displayed as part of a web page.

[0087] Example 1

[0088] 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."

[0089] Currently, in the marketing field, it takes a great deal of time and effort to understand the features of a product and generate a catchy slogan that is effective for target users. Furthermore, the quality of the catchy slogans is not stable, making it difficult to achieve consistent marketing results. To solve these problems, a system is needed that can automatically generate high-quality catchy slogans based on the product's features and the attributes of the target users.

[0090] 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.

[0091] In this invention, the server includes means for receiving information and obtaining analysis results using natural language processing technology, means for referencing attributes of the target user and generating a catchphrase using a catchphrase generation algorithm, and means for transmitting the generated catchphrase to the terminal, thereby enabling the user to quickly and effectively generate a catchphrase that appeals to the target user based on the input information.

[0092] A "user" is an individual or a corporation who inputs product features and target user attributes.

[0093] A "terminal" is a device that transmits information entered by a user to a server, and includes computers, smartphones, tablets, etc.

[0094] A "server" is a computer system that receives information, analyzes it, generates catchphrases, and returns it to the terminal.

[0095] "Product or service features" refer to the specific characteristics and appealing points of the product or service being offered.

[0096] "Target user attributes" refers to characteristic information such as age, gender, and interests of customers who are the target of marketing.

[0097] "Data formatting" is the process of converting information entered by a user into a standardized format (e.g., JSON).

[0098] "Natural language processing technology" is a technology for understanding and analyzing human language, and includes text analysis and keyword extraction.

[0099] A "catchphrase generation algorithm" is an algorithm for generating catchphrases for advertising and marketing purposes from input information.

[0100] A "generative AI model" is a type of artificial intelligence model that uses machine learning or deep learning to make predictions and generate results. An example of this is GPT-3 (registered trademark).

[0101] A "prompt" is an instruction that serves as input to the generative AI model, and specifically describes the requirements and conditions for generating a catchy slogan.

[0102] The present invention relates to a system that automatically generates catchy slogans based on the characteristics of a product or service entered by a user and the attributes of a target user. The following describes how to specifically implement the invention.

[0103] First, the user accesses the system using their own device (e.g., computer, smartphone, tablet). The user enters the product or service features and target user attributes on a form page provided through a web browser. For example, the user might enter "short-term results" and "100% natural ingredients" as features of a new diet supplement, and specify "health-conscious women in their 30s" as the target user attributes.

[0104] The terminal then formats the information you enter into JSON format, which looks like this:

[0105] json

[0106] {

[0107] "features": ["short-term results", "100% natural ingredients"],

[0108] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0109] }

[0110] This data is sent to the server as an HTTP request.

[0111] The server processes the received JSON data. It uses natural language processing technology (e.g., NLTK, SpaCy) to extract important keywords from the characteristics of the product or service. It then references the target user's attribute data and sets the conditions for generating a catchy slogan.

[0112] Next, the server generates a catchphrase using a generative AI model (e.g., GPT-3).

[0113] Please create a catchy slogan for a new diet supplement that is "effective in a short time" and "made from 100% natural ingredients" for health-conscious women in their 30s.

[0114] Sentences such as these are input into a generative AI model.

[0115] Based on this, the generative AI model generates a tagline like this:

[0116] "Healthy, beautiful, and quick, with the power of nature"

[0117] The server sends the generated catchphrase to the terminal as an HTTP response.

[0118] Finally, the terminal visually displays the catchphrase received from the server to the user, thereby enabling the user to efficiently obtain an effective catchphrase for the target users.

[0119] Through the above process, users can quickly generate a catchy slogan that best suits the product's features and target users, thereby strengthening their marketing activities.

[0120] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0121] Step 1: User Enters Information

[0122] The user uses a terminal to access a form page on a web browser and enters the characteristics of the product or service and the attributes of the target user. The information entered is in the following format: a new diet supplement that is "effective in a short period of time" and "made from 100% natural ingredients," and "health-conscious women in their 30s."

[0123] Step 2: The device formats the input and sends it to the server

[0124] The terminal formats the information entered by the user into JSON, which is converted into the following data format:

[0125] json

[0126] {

[0127] "features": ["short-term results", "100% natural ingredients"],

[0128] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0129] }

[0130] This formatted data is sent to the server as an HTTP request.

[0131] Step 3: The server receives the input and begins parsing it

[0132] The server receives the JSON data sent from the device. Based on the received data, it uses natural language processing technology (e.g., NLTK, SpaCy) to extract important keywords from the characteristics of the product or service. This process yields keywords such as "short-term results" and "100% natural ingredients."

[0133] Step 4: The server references the target profile and sets the conditions for generating the catchphrase.

[0134] The server combines the extracted keywords with the target user's attribute data. It references the target profile and generates a prompt for generating a catchphrase. An example of this prompt is, "Please generate a catchphrase for a new diet supplement that is effective in a short period of time and is made from 100% natural ingredients, aimed at health-conscious women in their 30s."

[0135] Step 5: The server generates a tagline using the generative AI model

[0136] The server uses a generative AI model (e.g., GPT-3) to generate a tagline based on the set prompt. The generative AI model receives the prompt as input and outputs the tagline, "Be healthy, beautiful, and fast, with the power of nature."

[0137] Step 6: The server sends the generated tagline to the device

[0138] The server sends the generated catchphrase "Get healthy and beautiful in a short time with the power of nature" to the terminal as an HTTP response. The terminal receives the catchphrase through this response.

[0139] Step 7: The device displays the tagline to the user

[0140] The terminal displays the catchphrase received from the server on the user interface. Specifically, the text "Get healthy, beautiful in a short time, with the power of nature" is displayed on the web browser page. This text display allows the user to obtain an effective catchphrase.

[0141] Through the above processing steps, the user can easily and quickly generate a catchy slogan suitable for the target user and use it in marketing activities.

[0142] (Application example 1)

[0143] 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."

[0144] In modern marketing, it is important to quickly generate catchy slogans that effectively appeal to target users. However, creating catchy slogans requires time and expertise, so an efficient generation method is needed. Current systems do not adequately meet this need, and there are particularly limited systems that are compatible with smart devices. Therefore, there is a need to provide new methods to improve the efficiency and effectiveness of marketing activities.

[0145] 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.

[0146] In this invention, the server includes a means for the user to input the features of the product / service and the attributes of the target user, a means for the terminal to format the input information and send it to the server, and a means for the server to receive the information, perform natural language processing, and obtain an analysis result. This makes it possible to automatically generate a catchy slogan using a catchy slogan generation algorithm by referring to the attributes of the target user, send it to the terminal, and display it on the smart device.

[0147] "User" refers to a person or group who inputs the characteristics of a product or service and the attributes of the target user.

[0148] "Terminal" refers to the equipment or device that formats and transmits information entered by a user to a server.

[0149] "Server" refers to a computer or platform that receives information sent from a terminal, analyzes it, and generates a catchphrase.

[0150] "Natural language processing" refers to techniques and methods that allow computers to understand and analyze human language.

[0151] "Analysis results" refers to the analysis results of data obtained through natural language processing.

[0152] "Target users" refers to groups or individuals who have the attributes of customers or users expected to be targeted at a particular product or service.

[0153] A "catchphrase generation algorithm" refers to a calculation procedure or program for generating effective catchphrases based on the attributes of target users and the characteristics of product services.

[0154] "Smart devices" refer to mobile information terminals and wearable devices that have Internet connectivity and can run applications.

[0155] This invention relates to a system that automatically generates catchy slogans based on the user's input of product / service characteristics and target user attributes. This system consists of three main components: the user, the terminal, and the server.

[0156] System Overview

[0157] 1. User input:

[0158] Users input the product / service features (e.g., short-term results, 100% natural ingredients) and the target user attributes (e.g., health-conscious women in their 30s). This allows for clear targeting of marketing.

[0159] 2. Terminal processing:

[0160] The terminal is responsible for formatting the information entered by the user, converting it into the appropriate format, and sending it to the server. To send data in JSON format, use the Python requests library, for example. For example, format it as follows:

[0161] json

[0162] {

[0163] "features": ["short-term results", "100% natural ingredients"],

[0164] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0165] }

[0166] 3. Server processing:

[0167] The server receives the data sent from the device and analyzes the information using natural language processing tools (e.g., spaCy or Transformers). After analysis, it runs a slogan generation algorithm (e.g., machine learning model) based on the target user's attribute information and the characteristics of the product or service to generate an appropriate slogan.

[0168] 4. Submit and display your tagline:

[0169] The server sends the generated catchphrase to the terminal, which then visually displays it to the user using a web browser or smartphone application.

[0170] Hardware and software used

[0171] Hardware:

[0172] Smartphone (iOS or ANDROID (registered trademark))

[0173] Server (Cloud server or on-premise server)

[0174] software:

[0175] Python

[0176] Flask (server-side framework)

[0177] requests library (for sending HTTP requests)

[0178] spaCy, Transformers (natural language processing tools)

[0179] Machine learning models (e.g., Tensorflow or PyTorch)

[0180] Specific examples

[0181] For example, if you are marketing a new diet supplement, the user might enter information like this:

[0182] Features: "Effective in a short period of time" "100% natural ingredients"

[0183] Target users: "Health-conscious women in their 30s"

[0184] The user enters this information into a smartphone application, which then converts the information into JSON format and sends it to a server. The server analyzes the received information and uses a machine learning model to generate a catchy slogan. The generated catchy slogan is "Become beautiful in a short amount of time, in a healthy way, with the power of nature." The smartphone application displays this to the user.

[0185] An example of a prompt sentence to input to the generative AI model is as follows:

[0186] Prompt: "The features of this product / service are 'short-term results' and '100% natural ingredients'. The target users are 'health-conscious women in their 30s'. Please generate a catchy slogan based on this."

[0187] This system allows users to quickly and effectively generate catchy slogans that appeal to target users, allowing them to efficiently carry out marketing activities.

[0188] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0189] Step 1:

[0190] The user inputs the characteristics of the product service and the attributes of the target user.

[0191] Input: Product / service features (e.g., "short-term results" and "100% natural ingredients") and target user attributes (e.g., "health-conscious women in their 30s")

[0192] Output: The information entered

[0193] Step 2:

[0194] The terminal formats the entered information and sends it to the server.

[0195] Input: Information entered in step 1

[0196] Data processing: Format the input information into JSON format

[0197] Output: Formatted JSON

[0198] Specific operation: The terminal formats the data in JSON format as shown below.

[0199] json

[0200] {

[0201] "features": ["short-term results", "100% natural ingredients"],

[0202] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0203] }

[0204] The device sends the formatted JSON data to the server via an HTTP request.

[0205] Step 3:

[0206] The server receives the information, performs natural language processing, and obtains the analysis results.

[0207] Input: JSON data sent in step 2

[0208] Data Computation: Using natural language processing tools (e.g., spaCy or Transformers) to analyze features and target information within the JSON data

[0209] Output: Analysis results (extraction of important keywords and characteristics)

[0210] Specific operation: The server performs natural language processing to extract keywords such as "short-term," "effective," "natural ingredients," and "health-conscious" based on the product service's characteristics and target attributes.

[0211] Step 4:

[0212] The server refers to the attributes of the target user and generates a catchphrase using a catchphrase generation algorithm.

[0213] Input: Analysis results obtained in Step 3, product features, and target user information

[0214] Data calculation: Using a machine learning model (e.g., TensorFlow or PyTorch), a prompt is generated based on the analysis results, and the copy generation algorithm is driven based on that prompt.

[0215] Output: Generated tagline

[0216] Specific operation: The server generates a catchy slogan such as "Get healthy and beautiful in a short time with the power of nature."

[0217] Step 5:

[0218] The server transmits the generated catchphrase to the terminal.

[0219] Input: Tagline generated in step 4

[0220] Output: JSON data to be sent

[0221] Specific operation: The server sends JSON data containing the generated tagline to the terminal as an HTTP response.

[0222] Step 6:

[0223] The terminal displays the catchphrase to the user.

[0224] Input: JSON data containing the tagline submitted in Step 5

[0225] Output: The tagline that is visually displayed to the user

[0226] Specific operation: The device displays the tagline "Get healthy and beautiful in a short time, with the power of nature" to the user through a web browser or smartphone application.

[0227] 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.

[0228] The present invention relates to a system for automatically generating catchy slogans based on the characteristics of a product or service selected by a user and the attributes of target users. In particular, the present invention relates to a system for generating catchy slogans that are more optimized for target users by combining an emotion engine that recognizes user emotions.

[0229] System configuration

[0230] This system is broadly divided into the following four components:

[0231] 1. Users

[0232] 2. Terminal

[0233] 3. Server

[0234] 4. Emotion Engine

[0235] System Operation Overview

[0236] 1. The user enters information

[0237] The user inputs the features and selling points of the product or service. They also input the attributes of the target users (e.g., age, gender, interests, etc.). For example, the user inputs features of a new diet supplement such as "short-term results" and "100% natural ingredients," and specifies "health-conscious women in their 30s" as the target users.

[0238] 2. The device sends the information to the server

[0239] The terminal formats the information the user enters and sends it to the server, for example in the following format:

[0240] json

[0241] {

[0242] "features": ["short-term results", "100% natural ingredients"],

[0243] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0244] }

[0245] 3. The device acquires the user's emotions and sends them to the server.

[0246] The device analyzes the user's current emotions using its emotion recognition function and transmits the information to the server, which also transmits the emotion information.

[0247] 4. The server receives the information and emotion data and starts the analysis process.

[0248] The server receives the information and emotion data sent from the device, then analyzes the product / service features using natural language processing tools and extracts important keywords.

[0249] 5. The server performs natural language processing (NLP)

[0250] The server analyzes the product service features using natural language processing tools (e.g., tokenization, part-of-speech tagging), thereby identifying important keywords and phrases.

[0251] 6. The server references the target user's attribute information

[0252] The server refers to a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[0253] 7. The server obtains the emotion analysis results using the emotion engine.

[0254] The server uses an emotion engine to analyze the emotion data and extract features based on the user's emotions.

[0255] 8. The server applies the tagline generation algorithm

[0256] The server generates an appropriate catchphrase using a catchphrase generation algorithm (e.g., machine learning model, rule-based model) based on the keywords obtained through natural language processing, the results of sentiment analysis, and the attributes of the target user.

[0257] 9. The server sends the generated tagline to the device.

[0258] The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0259] 10. The device displays the tagline to the user.

[0260] The device parses the HTTP response sent from the server and displays the content of the tagline in a user-friendly format. For example, the tagline "Be healthy, beautiful, and fast with the power of nature" is displayed as part of a web page.

[0261] Specific examples

[0262] 1. Input example

[0263] Product and service features: "Short-term results" "100% natural ingredients"

[0264] Target users: "Health-conscious women in their 30s"

[0265] User sentiment: optimistic, positive state

[0266] 2. Example of generated results

[0267] Catchphrase: "Enjoy beauty in a short time with the power of healthy, natural ingredients."

[0268] In this way, this system allows users to efficiently and effectively generate catchy slogans that are appropriate for target users. This significantly reduces the time and effort required to create catchy slogans, improving marketing effectiveness. Furthermore, by incorporating the user's emotions, it is possible to generate catchy slogans that are more personal and relatable.

[0269] The processing flow will be explained below.

[0270] Step 1:

[0271] The user inputs the characteristics of the product / service and the attributes of the target user. The user inputs the specific characteristics and selling points of the product / service into a dedicated input form. At the same time, the user also inputs attribute information of the target user, such as age, gender, and interests.

[0272] Step 2:

[0273] The device formats the input information and sends it to the server. The device (such as a computer or smartphone used by the user) converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[0274] Step 3:

[0275] The device acquires the user's emotions and sends them to the server. Using its built-in emotion recognition function, the device recognizes the user's current emotions from facial expressions, voice data, etc., and sends this in data format to the server.

[0276] Step 4:

[0277] The server receives the information and emotion data. The server analyzes the content of the received HTTP POST request and extracts the product / service features, target user attributes, and user emotion data.

[0278] Step 5:

[0279] The server performs natural language processing (NLP), analyzing the product features using NLP tools (e.g., tokenization, part-of-speech tagging) to identify important keywords and phrases.

[0280] Step 6:

[0281] The server references the target user's attribute information. The server then references a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[0282] Step 7:

[0283] The server obtains emotion analysis results using the emotion engine. The server analyzes the received emotion data using the emotion engine and extracts emotion features based on the user's current emotional state.

[0284] Step 8:

[0285] The server integrates the results of natural language processing, target user attribute information, and sentiment analysis results. Based on this information, the server sets up a catchphrase generation algorithm and determines the direction of the catchphrase to be generated.

[0286] Step 9:

[0287] The server applies a catchphrase generation algorithm to generate appropriate catchphrases using machine learning and rule-based models based on keywords obtained through natural language processing, sentiment analysis results, and target user attributes.

[0288] Step 10:

[0289] The server sends the generated catchphrase to the terminal. The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0290] Step 11:

[0291] The device displays the catchphrase to the user. The device analyzes the HTTP response sent from the server and displays the catchphrase content in a format that is easy for the user to read. For example, the generated catchphrase "Achieve beauty in a fun and short time, with the power of healthy natural ingredients" is displayed as part of a web page.

[0292] Example 2

[0293] 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."

[0294] Conventional slogan generation systems have had difficulty generating personalized slogans that incorporate user emotions. Furthermore, generating slogans that take into account the characteristics of products and services and the attributes of target customers takes time, often preventing effective marketing. This has resulted in limitations on the quality of slogans and marketing effectiveness.

[0295] 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.

[0296] In this invention, the server includes: means for a user to input product / service features and target customer attributes; means for a terminal to format the input information and send it to the server; means for the terminal to acquire user emotion data and send it to the server; means for the server to use a natural language processing tool to analyze the received information and emotion data; means for the server to extract important keywords from the analysis results and refer to target customer attributes; means for the server to extract features based on the user's emotion using an emotion engine; means for the server to generate a catchy slogan using a catchy slogan generation algorithm; means for the server to send the generated catchy slogan to the terminal; and means for the terminal to display the catchy slogan to the user. This makes it possible to quickly generate more personalized, high-quality catchy slogans that take into account the user's emotions and the target customer attributes.

[0297] "User" refers to an individual or organization who uses the system to input product / service features and target customer attribute information in order to generate a catchy slogan.

[0298] A "terminal" is a device that allows a user to input information and that transmits that information to a server.

[0299] The "server" is a central processing unit that analyzes information sent from the terminal and generates a catchy slogan.

[0300] "Emotion data" is information that represents the user's current emotional state (e.g., optimistic, positive, etc.).

[0301] "Natural language processing tools" are software and algorithms used to analyze text data and identify important keywords and phrases.

[0302] "Target customers" are a group of consumers with specific attributes that should be targeted by the slogan.

[0303] An "emotion engine" is a function or software that analyzes a user's emotional data and extracts features based on the results.

[0304] The "catchphrase generation algorithm" is an algorithm for generating catchphrases based on input information, sentiment analysis results, and target customer attribute information.

[0305] This invention is a system that generates efficient and effective catchphrases based on the characteristics of products and services entered by users and the attributes of target customers. This system includes a user, a terminal, a server, and an emotion engine. The following describes the role of each entity, the hardware and software used, and specific operation.

[0306] User Input

[0307] The user inputs the characteristics of the product or service and the attributes of the target customer into the terminal. For example, the user might input "short-term results" and "100% natural ingredients" as the characteristics of a new diet supplement, and specify "health-conscious women in their 30s" as the target customer.

[0308] Device operation

[0309] The terminal formats the information entered by the user and sends it to the server. Specific hardware used is a computing device such as a PC or smartphone. Software used is a web browser or dedicated application. The terminal converts the entered data into a format such as JSON and sends it to the server using the HTTP POST method.

[0310] The device also has an emotion recognition function that uses a camera and microphone to analyze the user's facial expressions and voice, and sends the analysis results to a server as text data.

[0311] Server Processing

[0312] The server receives the information sent from the device and begins analysis. The server uses natural language processing tools (e.g., spaCy, NLTK) to analyze the text of the product or service features and extract important keywords. It also uses a stored target profile database to reference the attribute information of target customers.

[0313] The server then uses an emotion engine (e.g., IBM Watson®, Microsoft® Azure® Emotion API) to analyze the user's emotion data and extract emotion-based features. Based on this information, the server applies a catchphrase generation algorithm (e.g., GPT-3) to generate an appropriate catchphrase.

[0314] Creating and displaying catchphrases

[0315] The server sends the generated catchphrase to the terminal as an HTTP response. The terminal parses the received HTTP response and displays the catchphrase to the user. The most common display format is to display the catchphrase as part of a web page or dedicated application.

[0316] Specific examples

[0317] Example input

[0318] Product and service features: "Short-term results" "100% natural ingredients"

[0319] Target customers: "Health-conscious women in their 30s"

[0320] User sentiment: optimistic, positive state

[0321] Example of generated results

[0322] Catchphrase: "Enjoy beauty in a short time with the power of healthy, natural ingredients."

[0323] Prompt Sentence Examples

[0324] Product and service features: "Short-term results" "100% natural ingredients"

[0325] Target customers: "Health-conscious women in their 30s"

[0326] User sentiment: optimistic, positive state

[0327] In this way, this system allows users to efficiently generate catchy slogans that are appropriate for their target customers. This significantly reduces the time and effort required to create catchy slogans, improving marketing effectiveness. Furthermore, by incorporating the user's emotions, it is possible to provide more personalized and relatable catchy slogans.

[0328] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0329] Step 1:

[0330] The user inputs product or service characteristics and target customer attribute information into the terminal. Specifically, the user inputs characteristic information such as "short-term results" and "100% natural ingredients" into the input form, as well as target customer information such as "health-conscious women in their 30s." The information entered is in text format, and the terminal temporarily stores it.

[0331] Step 2:

[0332] The device formats the user's input information and sends it to the server. The specific input is the text information mentioned above, which the device converts into JSON format. The information formatted as follows is sent to the server via the HTTP POST method: { 'features': ['short-term results', '100% natural ingredients'], 'target': {'age': '30s', 'interest': 'health', 'gender': 'female'}}.

[0333] Step 3:

[0334] The device acquires the user's emotional data and sends it to the server. For example, the device uses a camera and microphone to capture the user's facial expressions and voice, and analyzes them using emotion recognition software. As a result of this analysis, emotional data such as "optimistic" or "positive" is obtained. The acquired emotional data is then converted back to JSON format and sent to the server.

[0335] Step 4:

[0336] The server aggregates the information received from the devices and begins the analysis process. Specifically, the server analyzes the received JSON data and extracts information about the product or service's characteristics, target customer information, and user sentiment data. Python natural language processing tools (such as spaCy and NLTK) are used for the analysis to extract important keywords.

[0337] Step 5:

[0338] The server uses natural language processing tools to analyze the characteristics of products and services. For example, from input such as "short-term results" and "100% natural ingredients," it extracts important keywords such as "short-term," "effective," and "natural ingredients." The extracted keywords are then used to generate catchphrases.

[0339] Step 6:

[0340] The server references the target customer's attribute information from the database. For example, based on "Target: Health-conscious women in their 30s," the server retrieves the corresponding profile information from the target profile database. The retrieved profile information is used when generating the catchphrase.

[0341] Step 7:

[0342] The server uses an emotion engine to analyze the user's emotional data, for example, using IBM Watson's emotion analysis API to extract features to emphasize positive expressions from the received emotional data, such as "optimistic" and "positive."

[0343] Step 8:

[0344] The server uses a catchphrase generation algorithm to generate a catchphrase. Specifically, it uses a machine learning model (e.g., GPT-3) to generate a catchphrase using important keywords obtained through natural language processing, attribute information of target customers, and the results of sentiment analysis as prompts. The generated catchphrase will be a phrase such as "Achieve beauty in a short time with fun, healthy use of natural ingredients."

[0345] Step 9:

[0346] The server sends the generated catchphrase to the device. The generated catchphrase is then packaged again in JSON format and returned to the device as an HTTP response. The response content is in the format "{ 'catchphrase': 'Achieve beauty in a fun and short time, with the healthy power of natural ingredients'}".

[0347] Step 10:

[0348] The device displays the catchphrase received from the server to the user. The device parses the received HTTP response and extracts the catchphrase content. The device then displays the catchphrase in a specified location on the web page or dedicated application. For example, a part of the web page may display "Achieve beauty in a fun and short time, with the healthy power of natural ingredients."

[0349] (Application example 2)

[0350] 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."

[0351] In the modern advertising industry, there is a need to quickly and effectively create catchy slogans that appeal to target users. However, conventional methods have difficulty taking user emotions into account, and generating catchy slogans that resonate with users takes a great deal of time and effort. Therefore, there is a need for a system that can generate catchy slogans based on not only user input information but also real-time emotional data.

[0352] 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 the user to input the features of the product / service and the attributes of the target user; means for the terminal to format the input information and send it to the server; means for the terminal to recognize the user's emotions and send the data to the server; means for the server to receive the information and emotion data and start analysis processing; means for the server to perform natural language processing and obtain the analysis results; means for the server to refer to the attributes of the target user and generate a catchy slogan using a catchy slogan generation algorithm; means for the server to send the generated catchy slogan to the terminal; and means for the terminal to display the catchy slogan to the user. This makes it possible to quickly generate target-oriented catchy slogans that take user emotions into consideration.

[0353] A "user" is an entity that can input product features and target user attributes.

[0354] A "terminal" is a device that processes, formats, and transmits information entered by a user to a server.

[0355] The "server" is a central device that receives information and emotion data sent from the terminals, analyzes them, and generates catchphrases.

[0356] "Emotion recognition" is the process of analyzing a user's facial expressions and voice to identify their emotions at any given time.

[0357] "Natural language processing" is a technology that analyzes natural language and extracts important keywords and phrases.

[0358] A "catchphrase generation algorithm" is a calculation method for generating catchphrases optimized for target users based on input information and emotional data.

[0359] "Emotion data" is information about emotions obtained from analysis of the user's facial expressions and voice.

[0360] "Target users" are a group of users with certain attributes who are the target of advertisements and services.

[0361] A "catchphrase" is a short advertisement that effectively promotes a product or service.

[0362] A "machine learning model" is an algorithm that learns from large amounts of data and performs specific tasks.

[0363] The present invention relates to a system that automatically generates catchy slogans based on the features of a product or service and the attributes of target users. In particular, the system generates catchy slogans that are more optimized for target users by combining an emotion engine that recognizes the user's emotions.

[0364] This system is broadly divided into the following four components:

[0365] 1. Users

[0366] 2. Terminal

[0367] 3. Server

[0368] 4. Emotion Engine

[0369] Specific system configuration and operation

[0370] 1. The user enters information

[0371] Users input the characteristics of the product or service they want to advertise, as well as the attributes of the target users (e.g., age, gender, interests, etc.). Furthermore, emotional data is acquired in real time from the user's facial expressions and voice.

[0372] Example: "Characteristics: Sugar-free" "Target: Health-conscious men in their 20s"

[0373] 2. The device sends the information to the server

[0374] The device formats the information entered by the user and sends it to the server. The device also recognizes the user's emotions using the built-in camera and microphone and sends the emotional data to the server. The software module used for this purpose is "EmotionRecognizer."

[0375] 3. The server receives the information and emotion data and starts the analysis process.

[0376] The server receives the information and sentiment data sent from the device and analyzes the characteristics of the product or service using natural language processing (NLP) tools (e.g., tokenization, part-of-speech tagging, etc.). Based on the analysis results, important keywords and phrases are identified.

[0377] 4. The server references the target user's attribute information

[0378] The server references a pre-stored target profile database and extracts data based on the input attribute information (e.g., age, gender, interests, etc.).

[0379] 5. The server applies the tagline generation algorithm

[0380] The server applies a catchphrase generation algorithm (e.g., a machine learning model) based on the user's emotional data and keywords obtained through natural language processing to generate a catchphrase optimized for the target.

[0381] 6. The server sends the generated tagline to the device.

[0382] The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0383] 7. The device displays the tagline to the user.

[0384] The terminal parses the HTTP response sent from the server and displays the catchy slogan in a format that is easy for the user to see.

[0385] Specific examples

[0386] Example input

[0387] Product / service features: "Sugar-free"

[0388] Target users: "Health-conscious men in their 20s"

[0389] User sentiment: optimistic, positive state

[0390] Example of generated results

[0391] Catchphrase: "For the health-conscious, this sugar-free drink is delicious and safe."

[0392] Examples of prompt statements

[0393] For products or services that contain "sugar-free," please generate a catchphrase that is best suited to "optimistic" "men" in their "20s." The target users are interested in "health-conscious."

[0394] In this way, more target-oriented catchphrases can be generated quickly and effectively, taking into account the user's emotions.

[0395] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0396] Step 1:

[0397] The user inputs the characteristics of the product or service and the attributes of the target user. Specifically, the user inputs the product features (e.g., sugar-free) and target attributes (e.g., health-conscious men in their 20s) through the interface of a smartphone or head-mounted display. A string of product features and target attributes is generated as input data.

[0398] Step 2:

[0399] The terminal formats the input information and sends it to the server. The terminal converts the input product features and target attributes into an appropriate format, such as JSON, and sends it to the server. Specifically, it is sent as JSON data in the following format:

[0400] json

[0401] {

[0402] "features": ["sugar-free"],

[0403] "target": {"age": "20s", "interest": "health-conscious", "gender": "male"}

[0404] }

[0405] Step 3:

[0406] The device recognizes the user's emotions and sends the data to the server. The device uses its built-in camera and microphone to analyze the user's facial expressions and voice in real time using an emotion recognition module (EmotionRecognizer). Attributes such as "optimistic" and "positive" are acquired as emotional data and sent to the server.

[0407] Step 4:

[0408] The server receives the information and emotion data and begins the analysis process. The server receives and records the product features, target attributes, and emotion data sent from the device. The received data is organized and saved in JSON format, etc.

[0409] Step 5:

[0410] The server performs natural language processing and obtains the analysis results. Specifically, the server uses a natural language processing tool (e.g., an NLP library) to tokenize the text of the product features and extract important keywords and phrases. An extracted keyword may be "sugar-free."

[0411] Step 6:

[0412] The server references the target user's attribute information. The server retrieves marketing data corresponding to the target user's attributes (e.g., a health-conscious male in his 20s) from a database it has stored in advance. The retrieved data includes interests and concerns related to those attributes.

[0413] Step 7:

[0414] The server applies a catchphrase generation algorithm. The server uses a machine learning model to generate a catchphrase based on the obtained keywords, target user attribute data, and emotional data. For example, a catchphrase such as "For the health-conscious, sugar-free, delicious and safe" may be generated.

[0415] Step 8:

[0416] The server sends the generated catchphrase to the terminal. The generated catchphrase is formatted as an HTTP response and sent to the terminal. At this time, the following format is used as the response data.

[0417] json

[0418] {

[0419] "catchcopy": "For the health-conscious, sugar-free, delicious and safe"

[0420] }

[0421] Step 9:

[0422] The device displays the catchphrase to the user. The device parses the response data received from the server and displays the catchphrase on the user interface. Specifically, the catchphrase "For the health-conscious, sugar-free and delicious" is displayed on the smartphone screen or in the field of view of the head-mounted display.

[0423] 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.

[0424] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0425] 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.

[0426] [Second embodiment]

[0427] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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."

[0439] The present invention relates to a system for automatically generating catchy slogans based on the characteristics of a product or service selected by a user and the attributes of a target user. As an embodiment of the invention, the specific operation of the system will be described below.

[0440] System configuration

[0441] This system is broadly divided into the following three components:

[0442] 1. Users

[0443] 2. Terminal

[0444] 3. Server

[0445] System Operation Overview

[0446] 1. The user enters information

[0447] The user specifies the features and selling points of the product or service. They also input the attributes of the target users (e.g., age, gender, interests, etc.). For example, the user can input features of a new diet supplement such as "short-term results" and "100% natural ingredients," and specify "health-conscious women in their 30s" as the target users.

[0448] 2. The device sends the information to the server

[0449] The terminal formats the information the user enters and sends it to the server, for example in the following format:

[0450] json

[0451] {

[0452] "features": ["short-term results", "100% natural ingredients"],

[0453] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0454] }

[0455] 3. The server starts processing

[0456] The server receives the information sent from the device, then analyzes the product / service features using natural language processing tools to extract important keywords, and then references the target user's attribute data to set conditions for generating an appropriate catchphrase.

[0457] 4. Generate a catchphrase

[0458] The server combines the data obtained through natural language processing with the target profile to run a catchphrase generation algorithm. For example, a machine learning model is used to generate a catchphrase such as "Become beautiful in a short time, in a healthy way, with the power of nature."

[0459] 5. Send the generated tagline to the device

[0460] The server sends the generated catchphrase to the terminal as an HTTP response.

[0461] 6. The device displays the tagline to the user.

[0462] The terminal visually displays the received tagline to the user, for example, the text "Get healthy and beautiful in a short time, with the power of nature" on the page of the web browser.

[0463] Specific examples

[0464] 1. Input example

[0465] Product and service features: "Short-term results" "100% natural ingredients"

[0466] Target users: "Health-conscious women in their 30s"

[0467] 2. Example of generated results

[0468] Catchphrase: "Be healthy and beautiful in a short time, with the power of nature."

[0469] In this way, this system allows users to efficiently and effectively generate catchy slogans that are appropriate for target users, significantly reducing the time and effort required to create catchy slogans and improving marketing effectiveness.

[0470] The processing flow will be explained below.

[0471] Step 1:

[0472] The user inputs the characteristics of the product / service and the attributes of the target user. The user inputs the specific characteristics and selling points of the product / service into a dedicated input form. At the same time, the user also inputs attribute information of the target user, such as age, gender, and interests.

[0473] Step 2:

[0474] The device formats the input information and sends it to the server. The device (such as a computer or smartphone used by the user) converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[0475] Step 3:

[0476] The server receives the information and begins the analysis process. The server analyzes the received HTTP POST request and extracts the product / service features and target user attributes.

[0477] Step 4:

[0478] The server performs natural language processing (NLP). The server analyzes the product features using natural language processing tools (e.g., tokenization, part-of-speech tagging) to identify important keywords and phrases.

[0479] Step 5:

[0480] The server references the target user's attribute information. The server then references a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[0481] Step 6:

[0482] The server applies a catchphrase generation algorithm. Based on the keywords obtained through natural language processing and the attributes of the target user, the server uses a catchphrase generation algorithm (e.g., machine learning model, rule-based model) to generate an appropriate catchphrase.

[0483] Step 7:

[0484] The server sends the generated catchphrase to the terminal. The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0485] Step 8:

[0486] The device displays the catchphrase to the user. The device parses the HTTP response sent from the server and displays the catchphrase content in a format that is easy for the user to read. For example, the generated catchphrase "Be healthy, beautiful in a short time, with the power of nature" is displayed as part of a web page.

[0487] Example 1

[0488] 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."

[0489] Currently, in the marketing field, it takes a great deal of time and effort to understand the features of a product and generate a catchy slogan that is effective for target users. Furthermore, the quality of the catchy slogans is not stable, making it difficult to achieve consistent marketing results. To solve these problems, a system is needed that can automatically generate high-quality catchy slogans based on the product's features and the attributes of the target users.

[0490] 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.

[0491] In this invention, the server includes means for receiving information and obtaining analysis results using natural language processing technology, means for referencing attributes of the target user and generating a catchphrase using a catchphrase generation algorithm, and means for transmitting the generated catchphrase to the terminal, thereby enabling the user to quickly and effectively generate a catchphrase that appeals to the target user based on the input information.

[0492] A "user" is an individual or a corporation who inputs product features and target user attributes.

[0493] A "terminal" is a device that transmits information entered by a user to a server, and includes computers, smartphones, tablets, etc.

[0494] A "server" is a computer system that receives information, analyzes it, generates catchphrases, and returns it to the terminal.

[0495] "Product or service features" refer to the specific characteristics and appealing points of the product or service being offered.

[0496] "Target user attributes" refers to characteristic information such as age, gender, and interests of customers who are the target of marketing.

[0497] "Data formatting" is the process of converting information entered by a user into a standardized format (e.g., JSON).

[0498] "Natural language processing technology" is a technology for understanding and analyzing human language, and includes text analysis and keyword extraction.

[0499] A "catchphrase generation algorithm" is an algorithm for generating catchphrases for advertising and marketing purposes from input information.

[0500] A "generative AI model" is a type of artificial intelligence model that uses machine learning or deep learning to make predictions and generate results, and a specific example is GPT-3.

[0501] A "prompt" is an instruction that serves as input to the generative AI model, and specifically describes the requirements and conditions for generating a catchy slogan.

[0502] The present invention relates to a system that automatically generates catchy slogans based on the characteristics of a product or service entered by a user and the attributes of a target user. The following describes how to specifically implement the invention.

[0503] First, the user accesses the system using their own device (e.g., computer, smartphone, tablet). The user enters the product or service features and target user attributes on a form page provided through a web browser. For example, the user might enter "short-term results" and "100% natural ingredients" as features of a new diet supplement, and specify "health-conscious women in their 30s" as the target user attributes.

[0504] The terminal then formats the information you enter into JSON format, which looks like this:

[0505] json

[0506] {

[0507] "features": ["short-term results", "100% natural ingredients"],

[0508] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0509] }

[0510] This data is sent to the server as an HTTP request.

[0511] The server processes the received JSON data. It uses natural language processing technology (e.g., NLTK, SpaCy) to extract important keywords from the characteristics of the product or service. It then references the target user's attribute data and sets the conditions for generating a catchy slogan.

[0512] Next, the server generates a catchphrase using a generative AI model (e.g., GPT-3).

[0513] Please create a catchy slogan for a new diet supplement that is "effective in a short time" and "made from 100% natural ingredients" for health-conscious women in their 30s.

[0514] Sentences such as these are input into a generative AI model.

[0515] Based on this, the generative AI model generates a tagline like this:

[0516] "Healthy, beautiful, and quick, with the power of nature"

[0517] The server sends the generated catchphrase to the terminal as an HTTP response.

[0518] Finally, the terminal visually displays the catchphrase received from the server to the user, thereby enabling the user to efficiently obtain an effective catchphrase for the target users.

[0519] Through the above process, users can quickly generate a catchy slogan that best suits the product's features and target users, thereby strengthening their marketing activities.

[0520] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0521] Step 1: User Enters Information

[0522] The user uses a terminal to access a form page on a web browser and enters the characteristics of the product or service and the attributes of the target user. The information entered is in the following format: a new diet supplement that is "effective in a short period of time" and "made from 100% natural ingredients," and "health-conscious women in their 30s."

[0523] Step 2: The device formats the input and sends it to the server

[0524] The terminal formats the information entered by the user into JSON, which is converted into the following data format:

[0525] json

[0526] {

[0527] "features": ["short-term results", "100% natural ingredients"],

[0528] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0529] }

[0530] This formatted data is sent to the server as an HTTP request.

[0531] Step 3: The server receives the input and begins parsing it

[0532] The server receives the JSON data sent from the device. Based on the received data, it uses natural language processing technology (e.g., NLTK, SpaCy) to extract important keywords from the characteristics of the product or service. This process yields keywords such as "short-term results" and "100% natural ingredients."

[0533] Step 4: The server references the target profile and sets the conditions for generating the catchphrase.

[0534] The server combines the extracted keywords with the target user's attribute data. It references the target profile and generates a prompt for generating a catchphrase. An example of this prompt is, "Please generate a catchphrase for a new diet supplement that is effective in a short period of time and is made from 100% natural ingredients, aimed at health-conscious women in their 30s."

[0535] Step 5: The server generates a tagline using the generative AI model

[0536] The server uses a generative AI model (e.g., GPT-3) to generate a tagline based on the set prompt. The generative AI model receives the prompt as input and outputs the tagline, "Be healthy, beautiful, and fast, with the power of nature."

[0537] Step 6: The server sends the generated tagline to the device

[0538] The server sends the generated catchphrase "Get healthy and beautiful in a short time with the power of nature" to the terminal as an HTTP response. The terminal receives the catchphrase through this response.

[0539] Step 7: The device displays the tagline to the user

[0540] The terminal displays the catchphrase received from the server on the user interface. Specifically, the text "Get healthy, beautiful in a short time, with the power of nature" is displayed on the web browser page. This text display allows the user to obtain an effective catchphrase.

[0541] Through the above processing steps, the user can easily and quickly generate a catchy slogan suitable for the target user and use it in marketing activities.

[0542] (Application example 1)

[0543] 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."

[0544] In modern marketing, it is important to quickly generate catchy slogans that effectively appeal to target users. However, creating catchy slogans requires time and expertise, so an efficient generation method is needed. Current systems do not adequately meet this need, and there are particularly limited systems that are compatible with smart devices. Therefore, there is a need to provide new methods to improve the efficiency and effectiveness of marketing activities.

[0545] 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.

[0546] In this invention, the server includes a means for the user to input the features of the product / service and the attributes of the target user, a means for the terminal to format the input information and send it to the server, and a means for the server to receive the information, perform natural language processing, and obtain an analysis result. This makes it possible to automatically generate a catchy slogan using a catchy slogan generation algorithm by referring to the attributes of the target user, send it to the terminal, and display it on the smart device.

[0547] "User" refers to a person or group who inputs the characteristics of a product or service and the attributes of the target user.

[0548] "Terminal" refers to the equipment or device that formats and transmits information entered by a user to a server.

[0549] "Server" refers to a computer or platform that receives information sent from a terminal, analyzes it, and generates a catchphrase.

[0550] "Natural language processing" refers to techniques and methods that allow computers to understand and analyze human language.

[0551] "Analysis results" refers to the analysis results of data obtained through natural language processing.

[0552] "Target users" refers to groups or individuals who have the attributes of customers or users expected to be targeted at a particular product or service.

[0553] A "catchphrase generation algorithm" refers to a calculation procedure or program for generating effective catchphrases based on the attributes of target users and the characteristics of product services.

[0554] "Smart devices" refer to mobile information terminals and wearable devices that have Internet connectivity and can run applications.

[0555] This invention relates to a system that automatically generates catchy slogans based on the user's input of product / service characteristics and target user attributes. This system consists of three main components: the user, the terminal, and the server.

[0556] System Overview

[0557] 1. User input:

[0558] Users input the product / service features (e.g., short-term results, 100% natural ingredients) and the target user attributes (e.g., health-conscious women in their 30s). This allows for clear targeting of marketing.

[0559] 2. Terminal processing:

[0560] The terminal is responsible for formatting the information entered by the user, converting it into the appropriate format, and sending it to the server. To send data in JSON format, use the Python requests library, for example. For example, format it as follows:

[0561] json

[0562] {

[0563] "features": ["short-term results", "100% natural ingredients"],

[0564] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0565] }

[0566] 3. Server processing:

[0567] The server receives the data sent from the device and analyzes the information using natural language processing tools (e.g., spaCy or Transformers). After analysis, it runs a slogan generation algorithm (e.g., machine learning model) based on the target user's attribute information and the characteristics of the product or service to generate an appropriate slogan.

[0568] 4. Submit and display your tagline:

[0569] The server sends the generated catchphrase to the terminal, which then visually displays it to the user using a web browser or smartphone application.

[0570] Hardware and software used

[0571] Hardware:

[0572] Smartphone (iOS or Android)

[0573] Server (Cloud server or on-premise server)

[0574] software:

[0575] Python

[0576] Flask (server-side framework)

[0577] requests library (for sending HTTP requests)

[0578] spaCy, Transformers (natural language processing tools)

[0579] Machine learning models (e.g., TensorFlow or PyTorch)

[0580] Specific examples

[0581] For example, if you are marketing a new diet supplement, the user might enter information like this:

[0582] Features: "Effective in a short period of time" "100% natural ingredients"

[0583] Target users: "Health-conscious women in their 30s"

[0584] The user enters this information into a smartphone application, which then converts the information into JSON format and sends it to a server. The server analyzes the received information and uses a machine learning model to generate a catchy slogan. The generated catchy slogan is "Become beautiful in a short amount of time, in a healthy way, with the power of nature." The smartphone application displays this to the user.

[0585] An example of a prompt sentence to input to the generative AI model is as follows:

[0586] Prompt: "The features of this product / service are 'short-term results' and '100% natural ingredients'. The target users are 'health-conscious women in their 30s'. Please generate a catchy slogan based on this."

[0587] This system allows users to quickly and effectively generate catchy slogans that appeal to target users, allowing them to efficiently carry out marketing activities.

[0588] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0589] Step 1:

[0590] The user inputs the characteristics of the product service and the attributes of the target user.

[0591] Input: Product / service features (e.g., "short-term results" and "100% natural ingredients") and target user attributes (e.g., "health-conscious women in their 30s")

[0592] Output: The information entered

[0593] Step 2:

[0594] The terminal formats the entered information and sends it to the server.

[0595] Input: Information entered in step 1

[0596] Data processing: Format the input information into JSON format

[0597] Output: Formatted JSON

[0598] Specific operation: The terminal formats the data in JSON format as shown below.

[0599] json

[0600] {

[0601] "features": ["short-term results", "100% natural ingredients"],

[0602] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0603] }

[0604] The device sends the formatted JSON data to the server via an HTTP request.

[0605] Step 3:

[0606] The server receives the information, performs natural language processing, and obtains the analysis results.

[0607] Input: JSON data sent in step 2

[0608] Data Computation: Using natural language processing tools (e.g., spaCy or Transformers) to analyze features and target information within the JSON data

[0609] Output: Analysis results (extraction of important keywords and characteristics)

[0610] Specific operation: The server performs natural language processing to extract keywords such as "short-term," "effective," "natural ingredients," and "health-conscious" based on the product service's characteristics and target attributes.

[0611] Step 4:

[0612] The server refers to the attributes of the target user and generates a catchphrase using a catchphrase generation algorithm.

[0613] Input: Analysis results obtained in Step 3, product features, and target user information

[0614] Data calculation: Using a machine learning model (e.g., TensorFlow or PyTorch), a prompt is generated based on the analysis results, and the copy generation algorithm is driven based on that prompt.

[0615] Output: Generated tagline

[0616] Specific operation: The server generates a catchy slogan such as "Get healthy and beautiful in a short time with the power of nature."

[0617] Step 5:

[0618] The server transmits the generated catchphrase to the terminal.

[0619] Input: Tagline generated in step 4

[0620] Output: JSON data to be sent

[0621] Specific operation: The server sends JSON data containing the generated tagline to the terminal as an HTTP response.

[0622] Step 6:

[0623] The terminal displays the catchphrase to the user.

[0624] Input: JSON data containing the tagline submitted in Step 5

[0625] Output: The tagline that is visually displayed to the user

[0626] Specific operation: The device displays the tagline "Get healthy and beautiful in a short time, with the power of nature" to the user through a web browser or smartphone application.

[0627] 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.

[0628] The present invention relates to a system for automatically generating catchy slogans based on the characteristics of a product or service selected by a user and the attributes of target users. In particular, the present invention relates to a system for generating catchy slogans that are more optimized for target users by combining an emotion engine that recognizes user emotions.

[0629] System configuration

[0630] This system is broadly divided into the following four components:

[0631] 1. Users

[0632] 2. Terminal

[0633] 3. Server

[0634] 4. Emotion Engine

[0635] System Operation Overview

[0636] 1. The user enters information

[0637] The user inputs the features and selling points of the product or service. They also input the attributes of the target users (e.g., age, gender, interests, etc.). For example, the user inputs features of a new diet supplement such as "short-term results" and "100% natural ingredients," and specifies "health-conscious women in their 30s" as the target users.

[0638] 2. The device sends the information to the server

[0639] The terminal formats the information the user enters and sends it to the server, for example in the following format:

[0640] json

[0641] {

[0642] "features": ["short-term results", "100% natural ingredients"],

[0643] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0644] }

[0645] 3. The device acquires the user's emotions and sends them to the server.

[0646] The device analyzes the user's current emotions using its emotion recognition function and transmits the information to the server, which also transmits the emotion information.

[0647] 4. The server receives the information and emotion data and starts the analysis process.

[0648] The server receives the information and emotion data sent from the device, then analyzes the product / service features using natural language processing tools and extracts important keywords.

[0649] 5. The server performs natural language processing (NLP)

[0650] The server analyzes the product service features using natural language processing tools (e.g., tokenization, part-of-speech tagging), thereby identifying important keywords and phrases.

[0651] 6. The server references the target user's attribute information

[0652] The server refers to a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[0653] 7. The server obtains the emotion analysis results using the emotion engine.

[0654] The server uses an emotion engine to analyze the emotion data and extract features based on the user's emotions.

[0655] 8. The server applies the tagline generation algorithm

[0656] The server generates an appropriate catchphrase using a catchphrase generation algorithm (e.g., machine learning model, rule-based model) based on the keywords obtained through natural language processing, the results of sentiment analysis, and the attributes of the target user.

[0657] 9. The server sends the generated tagline to the device.

[0658] The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0659] 10. The device displays the tagline to the user.

[0660] The device parses the HTTP response sent from the server and displays the content of the tagline in a user-friendly format. For example, the tagline "Be healthy, beautiful, and fast with the power of nature" is displayed as part of a web page.

[0661] Specific examples

[0662] 1. Input example

[0663] Product and service features: "Short-term results" "100% natural ingredients"

[0664] Target users: "Health-conscious women in their 30s"

[0665] User sentiment: optimistic, positive state

[0666] 2. Example of generated results

[0667] Catchphrase: "Enjoy beauty in a short time with the power of healthy, natural ingredients."

[0668] In this way, this system allows users to efficiently and effectively generate catchy slogans that are appropriate for target users. This significantly reduces the time and effort required to create catchy slogans, improving marketing effectiveness. Furthermore, by incorporating the user's emotions, it is possible to generate catchy slogans that are more personal and relatable.

[0669] The processing flow will be explained below.

[0670] Step 1:

[0671] The user inputs the characteristics of the product / service and the attributes of the target user. The user inputs the specific characteristics and selling points of the product / service into a dedicated input form. At the same time, the user also inputs attribute information of the target user, such as age, gender, and interests.

[0672] Step 2:

[0673] The device formats the input information and sends it to the server. The device (such as a computer or smartphone used by the user) converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[0674] Step 3:

[0675] The device acquires the user's emotions and sends them to the server. Using its built-in emotion recognition function, the device recognizes the user's current emotions from facial expressions, voice data, etc., and sends this in data format to the server.

[0676] Step 4:

[0677] The server receives the information and emotion data. The server analyzes the content of the received HTTP POST request and extracts the product / service features, target user attributes, and user emotion data.

[0678] Step 5:

[0679] The server performs natural language processing (NLP), analyzing the product features using NLP tools (e.g., tokenization, part-of-speech tagging) to identify important keywords and phrases.

[0680] Step 6:

[0681] The server references the target user's attribute information. The server then references a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[0682] Step 7:

[0683] The server obtains emotion analysis results using the emotion engine. The server analyzes the received emotion data using the emotion engine and extracts emotion features based on the user's current emotional state.

[0684] Step 8:

[0685] The server integrates the results of natural language processing, target user attribute information, and sentiment analysis results. Based on this information, the server sets up a catchphrase generation algorithm and determines the direction of the catchphrase to be generated.

[0686] Step 9:

[0687] The server applies a catchphrase generation algorithm to generate appropriate catchphrases using machine learning and rule-based models based on keywords obtained through natural language processing, sentiment analysis results, and target user attributes.

[0688] Step 10:

[0689] The server sends the generated catchphrase to the terminal. The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0690] Step 11:

[0691] The device displays the catchphrase to the user. The device analyzes the HTTP response sent from the server and displays the catchphrase content in a format that is easy for the user to read. For example, the generated catchphrase "Achieve beauty in a fun and short time, with the power of healthy natural ingredients" is displayed as part of a web page.

[0692] Example 2

[0693] 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."

[0694] Conventional slogan generation systems have had difficulty generating personalized slogans that incorporate user emotions. Furthermore, generating slogans that take into account the characteristics of products and services and the attributes of target customers takes time, often preventing effective marketing. This has resulted in limitations on the quality of slogans and marketing effectiveness.

[0695] 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.

[0696] In this invention, the server includes: means for a user to input product / service features and target customer attributes; means for a terminal to format the input information and send it to the server; means for the terminal to acquire user emotion data and send it to the server; means for the server to use a natural language processing tool to analyze the received information and emotion data; means for the server to extract important keywords from the analysis results and refer to target customer attributes; means for the server to extract features based on the user's emotion using an emotion engine; means for the server to generate a catchy slogan using a catchy slogan generation algorithm; means for the server to send the generated catchy slogan to the terminal; and means for the terminal to display the catchy slogan to the user. This makes it possible to quickly generate more personalized, high-quality catchy slogans that take into account the user's emotions and the target customer attributes.

[0697] "User" refers to an individual or organization who uses the system to input product / service features and target customer attribute information in order to generate a catchy slogan.

[0698] A "terminal" is a device that allows a user to input information and that transmits that information to a server.

[0699] The "server" is a central processing unit that analyzes information sent from the terminal and generates a catchy slogan.

[0700] "Emotion data" is information that represents the user's current emotional state (e.g., optimistic, positive, etc.).

[0701] "Natural language processing tools" are software and algorithms used to analyze text data and identify important keywords and phrases.

[0702] "Target customers" are a group of consumers with specific attributes that should be targeted by the slogan.

[0703] An "emotion engine" is a function or software that analyzes a user's emotional data and extracts features based on the results.

[0704] The "catchphrase generation algorithm" is an algorithm for generating catchphrases based on input information, sentiment analysis results, and target customer attribute information.

[0705] This invention is a system that generates efficient and effective catchphrases based on the characteristics of products and services entered by users and the attributes of target customers. This system includes a user, a terminal, a server, and an emotion engine. The following describes the role of each entity, the hardware and software used, and specific operation.

[0706] User Input

[0707] The user inputs the characteristics of the product or service and the attributes of the target customer into the terminal. For example, the user might input "short-term results" and "100% natural ingredients" as the characteristics of a new diet supplement, and specify "health-conscious women in their 30s" as the target customer.

[0708] Device operation

[0709] The terminal formats the information entered by the user and sends it to the server. Specific hardware used is a computing device such as a PC or smartphone. Software used is a web browser or dedicated application. The terminal converts the entered data into a format such as JSON and sends it to the server using the HTTP POST method.

[0710] The device also has an emotion recognition function that uses a camera and microphone to analyze the user's facial expressions and voice, and sends the analysis results to a server as text data.

[0711] Server Processing

[0712] The server receives the information sent from the device and begins analysis. The server uses natural language processing tools (e.g., spaCy, NLTK) to analyze the text of the product or service features and extract important keywords. It also uses a stored target profile database to reference the attribute information of target customers.

[0713] Next, the server uses an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) to analyze the user's emotion data and extract emotion-based features. Based on this information, the server applies a catchphrase generation algorithm (e.g., GPT-3) to generate an appropriate catchphrase.

[0714] Creating and displaying catchphrases

[0715] The server sends the generated catchphrase to the terminal as an HTTP response. The terminal parses the received HTTP response and displays the catchphrase to the user. The most common display format is to display the catchphrase as part of a web page or dedicated application.

[0716] Specific examples

[0717] Example input

[0718] Product and service features: "Short-term results" "100% natural ingredients"

[0719] Target customers: "Health-conscious women in their 30s"

[0720] User sentiment: optimistic, positive state

[0721] Example of generated results

[0722] Catchphrase: "Enjoy beauty in a short time with the power of healthy, natural ingredients."

[0723] Prompt Sentence Examples

[0724] Product and service features: "Short-term results" "100% natural ingredients"

[0725] Target customers: "Health-conscious women in their 30s"

[0726] User sentiment: optimistic, positive state

[0727] In this way, this system allows users to efficiently generate catchy slogans that are appropriate for their target customers. This significantly reduces the time and effort required to create catchy slogans, improving marketing effectiveness. Furthermore, by incorporating the user's emotions, it is possible to provide more personalized and relatable catchy slogans.

[0728] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0729] Step 1:

[0730] The user inputs product or service characteristics and target customer attribute information into the terminal. Specifically, the user inputs characteristic information such as "short-term results" and "100% natural ingredients" into the input form, as well as target customer information such as "health-conscious women in their 30s." The information entered is in text format, and the terminal temporarily stores it.

[0731] Step 2:

[0732] The device formats the user's input information and sends it to the server. The specific input is the text information mentioned above, which the device converts into JSON format. The information formatted as follows is sent to the server via the HTTP POST method: { 'features': ['short-term results', '100% natural ingredients'], 'target': {'age': '30s', 'interest': 'health', 'gender': 'female'}}.

[0733] Step 3:

[0734] The device acquires the user's emotional data and sends it to the server. For example, the device uses a camera and microphone to capture the user's facial expressions and voice, and analyzes them using emotion recognition software. As a result of this analysis, emotional data such as "optimistic" or "positive" is obtained. The acquired emotional data is then converted back to JSON format and sent to the server.

[0735] Step 4:

[0736] The server aggregates the information received from the devices and begins the analysis process. Specifically, the server analyzes the received JSON data and extracts information about the product or service's characteristics, target customer information, and user sentiment data. Python natural language processing tools (such as spaCy and NLTK) are used for the analysis to extract important keywords.

[0737] Step 5:

[0738] The server uses natural language processing tools to analyze the characteristics of products and services. For example, from input such as "short-term results" and "100% natural ingredients," it extracts important keywords such as "short-term," "effective," and "natural ingredients." The extracted keywords are then used to generate catchphrases.

[0739] Step 6:

[0740] The server references the target customer's attribute information from the database. For example, based on "Target: Health-conscious women in their 30s," the server retrieves the corresponding profile information from the target profile database. The retrieved profile information is used when generating the catchphrase.

[0741] Step 7:

[0742] The server uses an emotion engine to analyze the user's emotional data, for example, using IBM Watson's emotion analysis API to extract features to emphasize positive expressions from the received emotional data, such as "optimistic" and "positive."

[0743] Step 8:

[0744] The server uses a catchphrase generation algorithm to generate a catchphrase. Specifically, it uses a machine learning model (e.g., GPT-3) to generate a catchphrase using important keywords obtained through natural language processing, attribute information of target customers, and the results of sentiment analysis as prompts. The generated catchphrase will be a phrase such as "Achieve beauty in a short time with fun, healthy use of natural ingredients."

[0745] Step 9:

[0746] The server sends the generated catchphrase to the device. The generated catchphrase is then packaged again in JSON format and returned to the device as an HTTP response. The response content is in the format "{ 'catchphrase': 'Achieve beauty in a fun and short time, with the healthy power of natural ingredients'}".

[0747] Step 10:

[0748] The device displays the catchphrase received from the server to the user. The device parses the received HTTP response and extracts the catchphrase content. The device then displays the catchphrase in a specified location on the web page or dedicated application. For example, a part of the web page may display "Achieve beauty in a fun and short time, with the healthy power of natural ingredients."

[0749] (Application example 2)

[0750] 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."

[0751] In the modern advertising industry, there is a need to quickly and effectively create catchy slogans that appeal to target users. However, conventional methods have difficulty taking user emotions into account, and generating catchy slogans that resonate with users takes a great deal of time and effort. Therefore, there is a need for a system that can generate catchy slogans based on not only user input information but also real-time emotional data.

[0752] 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 the user to input the features of the product / service and the attributes of the target user; means for the terminal to format the input information and send it to the server; means for the terminal to recognize the user's emotions and send the data to the server; means for the server to receive the information and emotion data and start analysis processing; means for the server to perform natural language processing and obtain the analysis results; means for the server to refer to the attributes of the target user and generate a catchy slogan using a catchy slogan generation algorithm; means for the server to send the generated catchy slogan to the terminal; and means for the terminal to display the catchy slogan to the user. This makes it possible to quickly generate target-oriented catchy slogans that take user emotions into consideration.

[0753] A "user" is an entity that can input product features and target user attributes.

[0754] A "terminal" is a device that processes, formats, and transmits information entered by a user to a server.

[0755] The "server" is a central device that receives information and emotion data sent from the terminals, analyzes them, and generates catchphrases.

[0756] "Emotion recognition" is the process of analyzing a user's facial expressions and voice to identify their emotions at any given time.

[0757] "Natural language processing" is a technology that analyzes natural language and extracts important keywords and phrases.

[0758] A "catchphrase generation algorithm" is a calculation method for generating catchphrases optimized for target users based on input information and emotional data.

[0759] "Emotion data" is information about emotions obtained from analysis of the user's facial expressions and voice.

[0760] "Target users" are a group of users with certain attributes who are the target of advertisements and services.

[0761] A "catchphrase" is a short advertisement that effectively promotes a product or service.

[0762] A "machine learning model" is an algorithm that learns from large amounts of data and performs specific tasks.

[0763] The present invention relates to a system that automatically generates catchy slogans based on the features of a product or service and the attributes of target users. In particular, the system generates catchy slogans that are more optimized for target users by combining an emotion engine that recognizes the user's emotions.

[0764] This system is broadly divided into the following four components:

[0765] 1. Users

[0766] 2. Terminal

[0767] 3. Server

[0768] 4. Emotion Engine

[0769] Specific system configuration and operation

[0770] 1. The user enters information

[0771] Users input the characteristics of the product or service they want to advertise, as well as the attributes of the target users (e.g., age, gender, interests, etc.). Furthermore, emotional data is acquired in real time from the user's facial expressions and voice.

[0772] Example: "Characteristics: Sugar-free" "Target: Health-conscious men in their 20s"

[0773] 2. The device sends the information to the server

[0774] The device formats the information entered by the user and sends it to the server. The device also recognizes the user's emotions using the built-in camera and microphone and sends the emotional data to the server. The software module used for this purpose is "EmotionRecognizer."

[0775] 3. The server receives the information and emotion data and starts the analysis process.

[0776] The server receives the information and sentiment data sent from the device and analyzes the characteristics of the product or service using natural language processing (NLP) tools (e.g., tokenization, part-of-speech tagging, etc.). Based on the analysis results, important keywords and phrases are identified.

[0777] 4. The server references the target user's attribute information

[0778] The server references a pre-stored target profile database and extracts data based on the input attribute information (e.g., age, gender, interests, etc.).

[0779] 5. The server applies the tagline generation algorithm

[0780] The server applies a catchphrase generation algorithm (e.g., a machine learning model) based on the user's emotional data and keywords obtained through natural language processing to generate a catchphrase optimized for the target.

[0781] 6. The server sends the generated tagline to the device.

[0782] The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0783] 7. The device displays the tagline to the user.

[0784] The terminal parses the HTTP response sent from the server and displays the catchy slogan in a format that is easy for the user to see.

[0785] Specific examples

[0786] Example input

[0787] Product / service features: "Sugar-free"

[0788] Target users: "Health-conscious men in their 20s"

[0789] User sentiment: optimistic, positive state

[0790] Example of generated results

[0791] Catchphrase: "For the health-conscious, this sugar-free drink is delicious and safe."

[0792] Examples of prompt statements

[0793] For products or services that contain "sugar-free," please generate a catchphrase that is best suited to "optimistic" "men" in their "20s." The target users are interested in "health-conscious."

[0794] In this way, more target-oriented catchphrases can be generated quickly and effectively, taking into account the user's emotions.

[0795] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0796] Step 1:

[0797] The user inputs the characteristics of the product or service and the attributes of the target user. Specifically, the user inputs the product features (e.g., sugar-free) and target attributes (e.g., health-conscious men in their 20s) through the interface of a smartphone or head-mounted display. A string of product features and target attributes is generated as input data.

[0798] Step 2:

[0799] The terminal formats the input information and sends it to the server. The terminal converts the input product features and target attributes into an appropriate format, such as JSON, and sends it to the server. Specifically, it is sent as JSON data in the following format:

[0800] json

[0801] {

[0802] "features": ["sugar-free"],

[0803] "target": {"age": "20s", "interest": "health-conscious", "gender": "male"}

[0804] }

[0805] Step 3:

[0806] The device recognizes the user's emotions and sends the data to the server. The device uses its built-in camera and microphone to analyze the user's facial expressions and voice in real time using an emotion recognition module (EmotionRecognizer). Attributes such as "optimistic" and "positive" are acquired as emotional data and sent to the server.

[0807] Step 4:

[0808] The server receives the information and emotion data and begins the analysis process. The server receives and records the product features, target attributes, and emotion data sent from the device. The received data is organized and saved in JSON format, etc.

[0809] Step 5:

[0810] The server performs natural language processing and obtains the analysis results. Specifically, the server uses a natural language processing tool (e.g., an NLP library) to tokenize the text of the product features and extract important keywords and phrases. An extracted keyword may be "sugar-free."

[0811] Step 6:

[0812] The server references the target user's attribute information. The server retrieves marketing data corresponding to the target user's attributes (e.g., a health-conscious male in his 20s) from a database it has stored in advance. The retrieved data includes interests and concerns related to those attributes.

[0813] Step 7:

[0814] The server applies a catchphrase generation algorithm. The server uses a machine learning model to generate a catchphrase based on the obtained keywords, target user attribute data, and emotional data. For example, a catchphrase such as "For the health-conscious, sugar-free, delicious and safe" may be generated.

[0815] Step 8:

[0816] The server sends the generated catchphrase to the terminal. The generated catchphrase is formatted as an HTTP response and sent to the terminal. At this time, the following format is used as the response data.

[0817] json

[0818] {

[0819] "catchcopy": "For the health-conscious, sugar-free, delicious and safe"

[0820] }

[0821] Step 9:

[0822] The device displays the catchphrase to the user. The device parses the response data received from the server and displays the catchphrase on the user interface. Specifically, the catchphrase "For the health-conscious, sugar-free and delicious" is displayed on the smartphone screen or in the field of view of the head-mounted display.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] [Third embodiment]

[0827] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0828] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0829] 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).

[0830] 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.

[0831] 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.

[0832] 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).

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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."

[0839] The present invention relates to a system for automatically generating catchy slogans based on the characteristics of a product or service selected by a user and the attributes of a target user. As an embodiment of the invention, the specific operation of the system will be described below.

[0840] System configuration

[0841] This system is broadly divided into the following three components:

[0842] 1. Users

[0843] 2. Terminal

[0844] 3. Server

[0845] System Operation Overview

[0846] 1. The user enters information

[0847] The user specifies the features and selling points of the product or service. They also input the attributes of the target users (e.g., age, gender, interests, etc.). For example, the user can input features of a new diet supplement such as "short-term results" and "100% natural ingredients," and specify "health-conscious women in their 30s" as the target users.

[0848] 2. The device sends the information to the server

[0849] The terminal formats the information the user enters and sends it to the server, for example in the following format:

[0850] json

[0851] {

[0852] "features": ["short-term results", "100% natural ingredients"],

[0853] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0854] }

[0855] 3. The server starts processing

[0856] The server receives the information sent from the device, then analyzes the product / service features using natural language processing tools to extract important keywords, and then references the target user's attribute data to set conditions for generating an appropriate catchphrase.

[0857] 4. Generate a catchphrase

[0858] The server combines the data obtained through natural language processing with the target profile to run a catchphrase generation algorithm. For example, a machine learning model is used to generate a catchphrase such as "Become beautiful in a short time, in a healthy way, with the power of nature."

[0859] 5. Send the generated tagline to the device

[0860] The server sends the generated catchphrase to the terminal as an HTTP response.

[0861] 6. The device displays the tagline to the user.

[0862] The terminal visually displays the received tagline to the user, for example, the text "Get healthy and beautiful in a short time, with the power of nature" on the page of the web browser.

[0863] Specific examples

[0864] 1. Input example

[0865] Product and service features: "Short-term results" "100% natural ingredients"

[0866] Target users: "Health-conscious women in their 30s"

[0867] 2. Example of generated results

[0868] Catchphrase: "Be healthy and beautiful in a short time, with the power of nature."

[0869] In this way, this system allows users to efficiently and effectively generate catchy slogans that are appropriate for target users, significantly reducing the time and effort required to create catchy slogans and improving marketing effectiveness.

[0870] The processing flow will be explained below.

[0871] Step 1:

[0872] The user inputs the characteristics of the product / service and the attributes of the target user. The user inputs the specific characteristics and selling points of the product / service into a dedicated input form. At the same time, the user also inputs attribute information of the target user, such as age, gender, and interests.

[0873] Step 2:

[0874] The device formats the input information and sends it to the server. The device (such as a computer or smartphone used by the user) converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[0875] Step 3:

[0876] The server receives the information and begins the analysis process. The server analyzes the received HTTP POST request and extracts the product / service features and target user attributes.

[0877] Step 4:

[0878] The server performs natural language processing (NLP). The server analyzes the product features using natural language processing tools (e.g., tokenization, part-of-speech tagging) to identify important keywords and phrases.

[0879] Step 5:

[0880] The server references the target user's attribute information. The server then references a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[0881] Step 6:

[0882] The server applies a catchphrase generation algorithm. Based on the keywords obtained through natural language processing and the attributes of the target user, the server uses a catchphrase generation algorithm (e.g., machine learning model, rule-based model) to generate an appropriate catchphrase.

[0883] Step 7:

[0884] The server sends the generated catchphrase to the terminal. The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[0885] Step 8:

[0886] The device displays the catchphrase to the user. The device parses the HTTP response sent from the server and displays the catchphrase content in a format that is easy for the user to read. For example, the generated catchphrase "Be healthy, beautiful in a short time, with the power of nature" is displayed as part of a web page.

[0887] Example 1

[0888] 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."

[0889] Currently, in the marketing field, it takes a great deal of time and effort to understand the features of a product and generate a catchy slogan that is effective for target users. Furthermore, the quality of the catchy slogans is not stable, making it difficult to achieve consistent marketing results. To solve these problems, a system is needed that can automatically generate high-quality catchy slogans based on the product's features and the attributes of the target users.

[0890] 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.

[0891] In this invention, the server includes means for receiving information and obtaining analysis results using natural language processing technology, means for referencing attributes of the target user and generating a catchphrase using a catchphrase generation algorithm, and means for transmitting the generated catchphrase to the terminal, thereby enabling the user to quickly and effectively generate a catchphrase that appeals to the target user based on the input information.

[0892] A "user" is an individual or a corporation who inputs product features and target user attributes.

[0893] A "terminal" is a device that transmits information entered by a user to a server, and includes computers, smartphones, tablets, etc.

[0894] A "server" is a computer system that receives information, analyzes it, generates catchphrases, and returns it to the terminal.

[0895] "Product or service features" refer to the specific characteristics and appealing points of the product or service being offered.

[0896] "Target user attributes" refers to characteristic information such as age, gender, and interests of customers who are the target of marketing.

[0897] "Data formatting" is the process of converting information entered by a user into a standardized format (e.g., JSON).

[0898] "Natural language processing technology" is a technology for understanding and analyzing human language, and includes text analysis and keyword extraction.

[0899] A "catchphrase generation algorithm" is an algorithm for generating catchphrases for advertising and marketing purposes from input information.

[0900] A "generative AI model" is a type of artificial intelligence model that uses machine learning or deep learning to make predictions and generate results, and a specific example is GPT-3.

[0901] A "prompt" is an instruction that serves as input to the generative AI model, and specifically describes the requirements and conditions for generating a catchy slogan.

[0902] The present invention relates to a system that automatically generates catchy slogans based on the characteristics of a product or service entered by a user and the attributes of a target user. The following describes how to specifically implement the invention.

[0903] First, the user accesses the system using their own device (e.g., computer, smartphone, tablet). The user enters the product or service features and target user attributes on a form page provided through a web browser. For example, the user might enter "short-term results" and "100% natural ingredients" as features of a new diet supplement, and specify "health-conscious women in their 30s" as the target user attributes.

[0904] The terminal then formats the information you enter into JSON format, which looks like this:

[0905] json

[0906] {

[0907] "features": ["short-term results", "100% natural ingredients"],

[0908] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0909] }

[0910] This data is sent to the server as an HTTP request.

[0911] The server processes the received JSON data. It uses natural language processing technology (e.g., NLTK, SpaCy) to extract important keywords from the characteristics of the product or service. It then references the target user's attribute data and sets the conditions for generating a catchy slogan.

[0912] Next, the server generates a catchphrase using a generative AI model (e.g., GPT-3).

[0913] Please create a catchy slogan for a new diet supplement that is "effective in a short time" and "made from 100% natural ingredients" for health-conscious women in their 30s.

[0914] Sentences such as these are input into a generative AI model.

[0915] Based on this, the generative AI model generates a tagline like this:

[0916] "Healthy, beautiful, and quick, with the power of nature"

[0917] The server sends the generated catchphrase to the terminal as an HTTP response.

[0918] Finally, the terminal visually displays the catchphrase received from the server to the user, thereby enabling the user to efficiently obtain an effective catchphrase for the target users.

[0919] Through the above process, users can quickly generate a catchy slogan that best suits the product's features and target users, thereby strengthening their marketing activities.

[0920] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0921] Step 1: User Enters Information

[0922] The user uses a terminal to access a form page on a web browser and enters the characteristics of the product or service and the attributes of the target user. The information entered is in the following format: a new diet supplement that is "effective in a short period of time" and "made from 100% natural ingredients," and "health-conscious women in their 30s."

[0923] Step 2: The device formats the input and sends it to the server

[0924] The terminal formats the information entered by the user into JSON, which is converted into the following data format:

[0925] json

[0926] {

[0927] "features": ["short-term results", "100% natural ingredients"],

[0928] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0929] }

[0930] This formatted data is sent to the server as an HTTP request.

[0931] Step 3: The server receives the input and begins parsing it

[0932] The server receives the JSON data sent from the device. Based on the received data, it uses natural language processing technology (e.g., NLTK, SpaCy) to extract important keywords from the characteristics of the product or service. This process yields keywords such as "short-term results" and "100% natural ingredients."

[0933] Step 4: The server references the target profile and sets the conditions for generating the catchphrase.

[0934] The server combines the extracted keywords with the target user's attribute data. It references the target profile and generates a prompt for generating a catchphrase. An example of this prompt is, "Please generate a catchphrase for a new diet supplement that is effective in a short period of time and is made from 100% natural ingredients, aimed at health-conscious women in their 30s."

[0935] Step 5: The server generates a tagline using the generative AI model

[0936] The server uses a generative AI model (e.g., GPT-3) to generate a tagline based on the set prompt. The generative AI model receives the prompt as input and outputs the tagline, "Be healthy, beautiful, and fast, with the power of nature."

[0937] Step 6: The server sends the generated tagline to the device

[0938] The server sends the generated catchphrase "Get healthy and beautiful in a short time with the power of nature" to the terminal as an HTTP response. The terminal receives the catchphrase through this response.

[0939] Step 7: The device displays the tagline to the user

[0940] The terminal displays the catchphrase received from the server on the user interface. Specifically, the text "Get healthy, beautiful in a short time, with the power of nature" is displayed on the web browser page. This text display allows the user to obtain an effective catchphrase.

[0941] Through the above processing steps, the user can easily and quickly generate a catchy slogan suitable for the target user and use it in marketing activities.

[0942] (Application example 1)

[0943] 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."

[0944] In modern marketing, it is important to quickly generate catchy slogans that effectively appeal to target users. However, creating catchy slogans requires time and expertise, so an efficient generation method is needed. Current systems do not adequately meet this need, and there are particularly limited systems that are compatible with smart devices. Therefore, there is a need to provide new methods to improve the efficiency and effectiveness of marketing activities.

[0945] 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.

[0946] In this invention, the server includes a means for the user to input the features of the product / service and the attributes of the target user, a means for the terminal to format the input information and send it to the server, and a means for the server to receive the information, perform natural language processing, and obtain an analysis result. This makes it possible to automatically generate a catchy slogan using a catchy slogan generation algorithm by referring to the attributes of the target user, send it to the terminal, and display it on the smart device.

[0947] "User" refers to a person or group who inputs the characteristics of a product or service and the attributes of the target user.

[0948] "Terminal" refers to the equipment or device that formats and transmits information entered by a user to a server.

[0949] "Server" refers to a computer or platform that receives information sent from a terminal, analyzes it, and generates a catchphrase.

[0950] "Natural language processing" refers to techniques and methods that allow computers to understand and analyze human language.

[0951] "Analysis results" refers to the analysis results of data obtained through natural language processing.

[0952] "Target users" refers to groups or individuals who have the attributes of customers or users expected to be targeted at a particular product or service.

[0953] A "catchphrase generation algorithm" refers to a calculation procedure or program for generating effective catchphrases based on the attributes of target users and the characteristics of product services.

[0954] "Smart devices" refer to mobile information terminals and wearable devices that have Internet connectivity and can run applications.

[0955] This invention relates to a system that automatically generates catchy slogans based on the user's input of product / service characteristics and target user attributes. This system consists of three main components: the user, the terminal, and the server.

[0956] System Overview

[0957] 1. User input:

[0958] Users input the product / service features (e.g., short-term results, 100% natural ingredients) and the target user attributes (e.g., health-conscious women in their 30s). This allows for clear targeting of marketing.

[0959] 2. Terminal processing:

[0960] The terminal is responsible for formatting the information entered by the user, converting it into the appropriate format, and sending it to the server. To send data in JSON format, use the Python requests library, for example. For example, format it as follows:

[0961] json

[0962] {

[0963] "features": ["short-term results", "100% natural ingredients"],

[0964] "target": {"age": "30s", "interest": "health", "gender": "female"}

[0965] }

[0966] 3. Server processing:

[0967] The server receives the data sent from the device and analyzes the information using natural language processing tools (e.g., spaCy or Transformers). After analysis, it runs a slogan generation algorithm (e.g., machine learning model) based on the target user's attribute information and the characteristics of the product or service to generate an appropriate slogan.

[0968] 4. Submit and display your tagline:

[0969] The server sends the generated catchphrase to the terminal, which then visually displays it to the user using a web browser or smartphone application.

[0970] Hardware and software used

[0971] Hardware:

[0972] Smartphone (iOS or Android)

[0973] Server (Cloud server or on-premise server)

[0974] software:

[0975] Python

[0976] Flask (server-side framework)

[0977] requests library (for sending HTTP requests)

[0978] spaCy, Transformers (natural language processing tools)

[0979] Machine learning models (e.g., TensorFlow or PyTorch)

[0980] Specific examples

[0981] For example, if you are marketing a new diet supplement, the user might enter information like this:

[0982] Features: "Effective in a short period of time" "100% natural ingredients"

[0983] Target users: "Health-conscious women in their 30s"

[0984] The user enters this information into a smartphone application, which then converts the information into JSON format and sends it to a server. The server analyzes the received information and uses a machine learning model to generate a catchy slogan. The generated catchy slogan is "Become beautiful in a short amount of time, in a healthy way, with the power of nature." The smartphone application displays this to the user.

[0985] An example of a prompt sentence to input to the generative AI model is as follows:

[0986] Prompt: "The features of this product / service are 'short-term results' and '100% natural ingredients'. The target users are 'health-conscious women in their 30s'. Please generate a catchy slogan based on this."

[0987] This system allows users to quickly and effectively generate catchy slogans that appeal to target users, allowing them to efficiently carry out marketing activities.

[0988] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0989] Step 1:

[0990] The user inputs the characteristics of the product service and the attributes of the target user.

[0991] Input: Product / service features (e.g., "short-term results" and "100% natural ingredients") and target user attributes (e.g., "health-conscious women in their 30s")

[0992] Output: The information entered

[0993] Step 2:

[0994] The terminal formats the entered information and sends it to the server.

[0995] Input: Information entered in step 1

[0996] Data processing: Format the input information into JSON format

[0997] Output: Formatted JSON

[0998] Specific operation: The terminal formats the data in JSON format as shown below.

[0999] json

[1000] {

[1001] "features": ["short-term results", "100% natural ingredients"],

[1002] "target": {"age": "30s", "interest": "health", "gender": "female"}

[1003] }

[1004] The device sends the formatted JSON data to the server via an HTTP request.

[1005] Step 3:

[1006] The server receives the information, performs natural language processing, and obtains the analysis results.

[1007] Input: JSON data sent in step 2

[1008] Data Computation: Using natural language processing tools (e.g., spaCy or Transformers) to analyze features and target information within the JSON data

[1009] Output: Analysis results (extraction of important keywords and characteristics)

[1010] Specific operation: The server performs natural language processing to extract keywords such as "short-term," "effective," "natural ingredients," and "health-conscious" based on the product service's characteristics and target attributes.

[1011] Step 4:

[1012] The server refers to the attributes of the target user and generates a catchphrase using a catchphrase generation algorithm.

[1013] Input: Analysis results obtained in Step 3, product features, and target user information

[1014] Data calculation: Using a machine learning model (e.g., TensorFlow or PyTorch), a prompt is generated based on the analysis results, and the copy generation algorithm is driven based on that prompt.

[1015] Output: Generated tagline

[1016] Specific operation: The server generates a catchy slogan such as "Get healthy and beautiful in a short time with the power of nature."

[1017] Step 5:

[1018] The server transmits the generated catchphrase to the terminal.

[1019] Input: Tagline generated in step 4

[1020] Output: JSON data to be sent

[1021] Specific operation: The server sends JSON data containing the generated tagline to the terminal as an HTTP response.

[1022] Step 6:

[1023] The terminal displays the catchphrase to the user.

[1024] Input: JSON data containing the tagline submitted in Step 5

[1025] Output: The tagline that is visually displayed to the user

[1026] Specific operation: The device displays the tagline "Get healthy and beautiful in a short time, with the power of nature" to the user through a web browser or smartphone application.

[1027] 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.

[1028] The present invention relates to a system for automatically generating catchy slogans based on the characteristics of a product or service selected by a user and the attributes of target users. In particular, the present invention relates to a system for generating catchy slogans that are more optimized for target users by combining an emotion engine that recognizes user emotions.

[1029] System configuration

[1030] This system is broadly divided into the following four components:

[1031] 1. Users

[1032] 2. Terminal

[1033] 3. Server

[1034] 4. Emotion Engine

[1035] System Operation Overview

[1036] 1. The user enters information

[1037] The user inputs the features and selling points of the product or service. They also input the attributes of the target users (e.g., age, gender, interests, etc.). For example, the user inputs features of a new diet supplement such as "short-term results" and "100% natural ingredients," and specifies "health-conscious women in their 30s" as the target users.

[1038] 2. The device sends the information to the server

[1039] The terminal formats the information the user enters and sends it to the server, for example in the following format:

[1040] json

[1041] {

[1042] "features": ["short-term results", "100% natural ingredients"],

[1043] "target": {"age": "30s", "interest": "health", "gender": "female"}

[1044] }

[1045] 3. The device acquires the user's emotions and sends them to the server.

[1046] The device analyzes the user's current emotions using its emotion recognition function and transmits the information to the server, which also transmits the emotion information.

[1047] 4. The server receives the information and emotion data and starts the analysis process.

[1048] The server receives the information and emotion data sent from the device, then analyzes the product / service features using natural language processing tools and extracts important keywords.

[1049] 5. The server performs natural language processing (NLP)

[1050] The server analyzes the product service features using natural language processing tools (e.g., tokenization, part-of-speech tagging), thereby identifying important keywords and phrases.

[1051] 6. The server references the target user's attribute information

[1052] The server refers to a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[1053] 7. The server obtains the emotion analysis results using the emotion engine.

[1054] The server uses an emotion engine to analyze the emotion data and extract features based on the user's emotions.

[1055] 8. The server applies the tagline generation algorithm

[1056] The server generates an appropriate catchphrase using a catchphrase generation algorithm (e.g., machine learning model, rule-based model) based on the keywords obtained through natural language processing, the results of sentiment analysis, and the attributes of the target user.

[1057] 9. The server sends the generated tagline to the device.

[1058] The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[1059] 10. The device displays the tagline to the user.

[1060] The device parses the HTTP response sent from the server and displays the content of the tagline in a user-friendly format. For example, the tagline "Be healthy, beautiful, and fast with the power of nature" is displayed as part of a web page.

[1061] Specific examples

[1062] 1. Input example

[1063] Product and service features: "Short-term results" "100% natural ingredients"

[1064] Target users: "Health-conscious women in their 30s"

[1065] User sentiment: optimistic, positive state

[1066] 2. Example of generated results

[1067] Catchphrase: "Enjoy beauty in a short time with the power of healthy, natural ingredients."

[1068] In this way, this system allows users to efficiently and effectively generate catchy slogans that are appropriate for target users. This significantly reduces the time and effort required to create catchy slogans, improving marketing effectiveness. Furthermore, by incorporating the user's emotions, it is possible to generate catchy slogans that are more personal and relatable.

[1069] The processing flow will be explained below.

[1070] Step 1:

[1071] The user inputs the characteristics of the product / service and the attributes of the target user. The user inputs the specific characteristics and selling points of the product / service into a dedicated input form. At the same time, the user also inputs attribute information of the target user, such as age, gender, and interests.

[1072] Step 2:

[1073] The device formats the input information and sends it to the server. The device (such as a computer or smartphone used by the user) converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[1074] Step 3:

[1075] The device acquires the user's emotions and sends them to the server. Using its built-in emotion recognition function, the device recognizes the user's current emotions from facial expressions, voice data, etc., and sends this in data format to the server.

[1076] Step 4:

[1077] The server receives the information and emotion data. The server analyzes the content of the received HTTP POST request and extracts the product / service features, target user attributes, and user emotion data.

[1078] Step 5:

[1079] The server performs natural language processing (NLP), analyzing the product features using NLP tools (e.g., tokenization, part-of-speech tagging) to identify important keywords and phrases.

[1080] Step 6:

[1081] The server references the target user's attribute information. The server then references a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[1082] Step 7:

[1083] The server obtains emotion analysis results using the emotion engine. The server analyzes the received emotion data using the emotion engine and extracts emotion features based on the user's current emotional state.

[1084] Step 8:

[1085] The server integrates the results of natural language processing, target user attribute information, and sentiment analysis results. Based on this information, the server sets up a catchphrase generation algorithm and determines the direction of the catchphrase to be generated.

[1086] Step 9:

[1087] The server applies a catchphrase generation algorithm to generate appropriate catchphrases using machine learning and rule-based models based on keywords obtained through natural language processing, sentiment analysis results, and target user attributes.

[1088] Step 10:

[1089] The server sends the generated catchphrase to the terminal. The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[1090] Step 11:

[1091] The device displays the catchphrase to the user. The device analyzes the HTTP response sent from the server and displays the catchphrase content in a format that is easy for the user to read. For example, the generated catchphrase "Achieve beauty in a fun and short time, with the power of healthy natural ingredients" is displayed as part of a web page.

[1092] Example 2

[1093] 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."

[1094] Conventional slogan generation systems have had difficulty generating personalized slogans that incorporate user emotions. Furthermore, generating slogans that take into account the characteristics of products and services and the attributes of target customers takes time, often preventing effective marketing. This has resulted in limitations on the quality of slogans and marketing effectiveness.

[1095] 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.

[1096] In this invention, the server includes: means for a user to input product / service features and target customer attributes; means for a terminal to format the input information and send it to the server; means for the terminal to acquire user emotion data and send it to the server; means for the server to use a natural language processing tool to analyze the received information and emotion data; means for the server to extract important keywords from the analysis results and refer to target customer attributes; means for the server to extract features based on the user's emotion using an emotion engine; means for the server to generate a catchy slogan using a catchy slogan generation algorithm; means for the server to send the generated catchy slogan to the terminal; and means for the terminal to display the catchy slogan to the user. This makes it possible to quickly generate more personalized, high-quality catchy slogans that take into account the user's emotions and the target customer attributes.

[1097] "User" refers to an individual or organization who uses the system to input product / service features and target customer attribute information in order to generate a catchy slogan.

[1098] A "terminal" is a device that allows a user to input information and that transmits that information to a server.

[1099] The "server" is a central processing unit that analyzes information sent from the terminal and generates a catchy slogan.

[1100] "Emotion data" is information that represents the user's current emotional state (e.g., optimistic, positive, etc.).

[1101] "Natural language processing tools" are software and algorithms used to analyze text data and identify important keywords and phrases.

[1102] "Target customers" are a group of consumers with specific attributes that should be targeted by the slogan.

[1103] An "emotion engine" is a function or software that analyzes a user's emotional data and extracts features based on the results.

[1104] The "catchphrase generation algorithm" is an algorithm for generating catchphrases based on input information, sentiment analysis results, and target customer attribute information.

[1105] This invention is a system that generates efficient and effective catchphrases based on the characteristics of products and services entered by users and the attributes of target customers. This system includes a user, a terminal, a server, and an emotion engine. The following describes the role of each entity, the hardware and software used, and specific operation.

[1106] User Input

[1107] The user inputs the characteristics of the product or service and the attributes of the target customer into the terminal. For example, the user might input "short-term results" and "100% natural ingredients" as the characteristics of a new diet supplement, and specify "health-conscious women in their 30s" as the target customer.

[1108] Device operation

[1109] The terminal formats the information entered by the user and sends it to the server. Specific hardware used is a computing device such as a PC or smartphone. Software used is a web browser or dedicated application. The terminal converts the entered data into a format such as JSON and sends it to the server using the HTTP POST method.

[1110] The device also has an emotion recognition function that uses a camera and microphone to analyze the user's facial expressions and voice, and sends the analysis results to a server as text data.

[1111] Server Processing

[1112] The server receives the information sent from the device and begins analysis. The server uses natural language processing tools (e.g., spaCy, NLTK) to analyze the text of the product or service features and extract important keywords. It also uses a stored target profile database to reference the attribute information of target customers.

[1113] Next, the server uses an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) to analyze the user's emotion data and extract emotion-based features. Based on this information, the server applies a catchphrase generation algorithm (e.g., GPT-3) to generate an appropriate catchphrase.

[1114] Creating and displaying catchphrases

[1115] The server sends the generated catchphrase to the terminal as an HTTP response. The terminal parses the received HTTP response and displays the catchphrase to the user. The most common display format is to display the catchphrase as part of a web page or dedicated application.

[1116] Specific examples

[1117] Example input

[1118] Product and service features: "Short-term results" "100% natural ingredients"

[1119] Target customers: "Health-conscious women in their 30s"

[1120] User sentiment: optimistic, positive state

[1121] Example of generated results

[1122] Catchphrase: "Enjoy beauty in a short time with the power of healthy, natural ingredients."

[1123] Prompt Sentence Examples

[1124] Product and service features: "Short-term results" "100% natural ingredients"

[1125] Target customers: "Health-conscious women in their 30s"

[1126] User sentiment: optimistic, positive state

[1127] In this way, this system allows users to efficiently generate catchy slogans that are appropriate for their target customers. This significantly reduces the time and effort required to create catchy slogans, improving marketing effectiveness. Furthermore, by incorporating the user's emotions, it is possible to provide more personalized and relatable catchy slogans.

[1128] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1129] Step 1:

[1130] The user inputs product or service characteristics and target customer attribute information into the terminal. Specifically, the user inputs characteristic information such as "short-term results" and "100% natural ingredients" into the input form, as well as target customer information such as "health-conscious women in their 30s." The information entered is in text format, and the terminal temporarily stores it.

[1131] Step 2:

[1132] The device formats the user's input information and sends it to the server. The specific input is the text information mentioned above, which the device converts into JSON format. The information formatted as follows is sent to the server via the HTTP POST method: { 'features': ['short-term results', '100% natural ingredients'], 'target': {'age': '30s', 'interest': 'health', 'gender': 'female'}}.

[1133] Step 3:

[1134] The device acquires the user's emotional data and sends it to the server. For example, the device uses a camera and microphone to capture the user's facial expressions and voice, and analyzes them using emotion recognition software. As a result of this analysis, emotional data such as "optimistic" or "positive" is obtained. The acquired emotional data is then converted back to JSON format and sent to the server.

[1135] Step 4:

[1136] The server aggregates the information received from the devices and begins the analysis process. Specifically, the server analyzes the received JSON data and extracts information about the product or service's characteristics, target customer information, and user sentiment data. Python natural language processing tools (such as spaCy and NLTK) are used for the analysis to extract important keywords.

[1137] Step 5:

[1138] The server uses natural language processing tools to analyze the characteristics of products and services. For example, from input such as "short-term results" and "100% natural ingredients," it extracts important keywords such as "short-term," "effective," and "natural ingredients." The extracted keywords are then used to generate catchphrases.

[1139] Step 6:

[1140] The server references the target customer's attribute information from the database. For example, based on "Target: Health-conscious women in their 30s," the server retrieves the corresponding profile information from the target profile database. The retrieved profile information is used when generating the catchphrase.

[1141] Step 7:

[1142] The server uses an emotion engine to analyze the user's emotional data, for example, using IBM Watson's emotion analysis API to extract features to emphasize positive expressions from the received emotional data, such as "optimistic" and "positive."

[1143] Step 8:

[1144] The server uses a catchphrase generation algorithm to generate a catchphrase. Specifically, it uses a machine learning model (e.g., GPT-3) to generate a catchphrase using important keywords obtained through natural language processing, attribute information of target customers, and the results of sentiment analysis as prompts. The generated catchphrase will be a phrase such as "Achieve beauty in a short time with fun, healthy use of natural ingredients."

[1145] Step 9:

[1146] The server sends the generated catchphrase to the device. The generated catchphrase is then packaged again in JSON format and returned to the device as an HTTP response. The response content is in the format "{ 'catchphrase': 'Achieve beauty in a fun and short time, with the healthy power of natural ingredients'}".

[1147] Step 10:

[1148] The device displays the catchphrase received from the server to the user. The device parses the received HTTP response and extracts the catchphrase content. The device then displays the catchphrase in a specified location on the web page or dedicated application. For example, a part of the web page may display "Achieve beauty in a fun and short time, with the healthy power of natural ingredients."

[1149] (Application example 2)

[1150] 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."

[1151] In the modern advertising industry, there is a need to quickly and effectively create catchy slogans that appeal to target users. However, conventional methods have difficulty taking user emotions into account, and generating catchy slogans that resonate with users takes a great deal of time and effort. Therefore, there is a need for a system that can generate catchy slogans based on not only user input information but also real-time emotional data.

[1152] 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 the user to input the features of the product / service and the attributes of the target user; means for the terminal to format the input information and send it to the server; means for the terminal to recognize the user's emotions and send the data to the server; means for the server to receive the information and emotion data and start analysis processing; means for the server to perform natural language processing and obtain the analysis results; means for the server to refer to the attributes of the target user and generate a catchy slogan using a catchy slogan generation algorithm; means for the server to send the generated catchy slogan to the terminal; and means for the terminal to display the catchy slogan to the user. This makes it possible to quickly generate target-oriented catchy slogans that take user emotions into consideration.

[1153] A "user" is an entity that can input product features and target user attributes.

[1154] A "terminal" is a device that processes, formats, and transmits information entered by a user to a server.

[1155] The "server" is a central device that receives information and emotion data sent from the terminals, analyzes them, and generates catchphrases.

[1156] "Emotion recognition" is the process of analyzing a user's facial expressions and voice to identify their emotions at any given time.

[1157] "Natural language processing" is a technology that analyzes natural language and extracts important keywords and phrases.

[1158] A "catchphrase generation algorithm" is a calculation method for generating catchphrases optimized for target users based on input information and emotional data.

[1159] "Emotion data" is information about emotions obtained from analysis of the user's facial expressions and voice.

[1160] "Target users" are a group of users with certain attributes who are the target of advertisements and services.

[1161] A "catchphrase" is a short advertisement that effectively promotes a product or service.

[1162] A "machine learning model" is an algorithm that learns from large amounts of data and performs specific tasks.

[1163] The present invention relates to a system that automatically generates catchy slogans based on the features of a product or service and the attributes of target users. In particular, the system generates catchy slogans that are more optimized for target users by combining an emotion engine that recognizes the user's emotions.

[1164] This system is broadly divided into the following four components:

[1165] 1. Users

[1166] 2. Terminal

[1167] 3. Server

[1168] 4. Emotion Engine

[1169] Specific system configuration and operation

[1170] 1. The user enters information

[1171] Users input the characteristics of the product or service they want to advertise, as well as the attributes of the target users (e.g., age, gender, interests, etc.). Furthermore, emotional data is acquired in real time from the user's facial expressions and voice.

[1172] Example: "Characteristics: Sugar-free" "Target: Health-conscious men in their 20s"

[1173] 2. The device sends the information to the server

[1174] The device formats the information entered by the user and sends it to the server. The device also recognizes the user's emotions using the built-in camera and microphone and sends the emotional data to the server. The software module used for this purpose is "EmotionRecognizer."

[1175] 3. The server receives the information and emotion data and starts the analysis process.

[1176] The server receives the information and sentiment data sent from the device and analyzes the characteristics of the product or service using natural language processing (NLP) tools (e.g., tokenization, part-of-speech tagging, etc.). Based on the analysis results, important keywords and phrases are identified.

[1177] 4. The server references the target user's attribute information

[1178] The server references a pre-stored target profile database and extracts data based on the input attribute information (e.g., age, gender, interests, etc.).

[1179] 5. The server applies the tagline generation algorithm

[1180] The server applies a catchphrase generation algorithm (e.g., a machine learning model) based on the user's emotional data and keywords obtained through natural language processing to generate a catchphrase optimized for the target.

[1181] 6. The server sends the generated tagline to the device.

[1182] The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[1183] 7. The device displays the tagline to the user.

[1184] The terminal parses the HTTP response sent from the server and displays the catchy slogan in a format that is easy for the user to see.

[1185] Specific examples

[1186] Example input

[1187] Product / service features: "Sugar-free"

[1188] Target users: "Health-conscious men in their 20s"

[1189] User sentiment: optimistic, positive state

[1190] Example of generated results

[1191] Catchphrase: "For the health-conscious, this sugar-free drink is delicious and safe."

[1192] Examples of prompt statements

[1193] For products or services that contain "sugar-free," please generate a catchphrase that is best suited to "optimistic" "men" in their "20s." The target users are interested in "health-conscious."

[1194] In this way, more target-oriented catchphrases can be generated quickly and effectively, taking into account the user's emotions.

[1195] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1196] Step 1:

[1197] The user inputs the characteristics of the product or service and the attributes of the target user. Specifically, the user inputs the product features (e.g., sugar-free) and target attributes (e.g., health-conscious men in their 20s) through the interface of a smartphone or head-mounted display. A string of product features and target attributes is generated as input data.

[1198] Step 2:

[1199] The terminal formats the input information and sends it to the server. The terminal converts the input product features and target attributes into an appropriate format, such as JSON, and sends it to the server. Specifically, it is sent as JSON data in the following format:

[1200] json

[1201] {

[1202] "features": ["sugar-free"],

[1203] "target": {"age": "20s", "interest": "health-conscious", "gender": "male"}

[1204] }

[1205] Step 3:

[1206] The device recognizes the user's emotions and sends the data to the server. The device uses its built-in camera and microphone to analyze the user's facial expressions and voice in real time using an emotion recognition module (EmotionRecognizer). Attributes such as "optimistic" and "positive" are acquired as emotional data and sent to the server.

[1207] Step 4:

[1208] The server receives the information and emotion data and begins the analysis process. The server receives and records the product features, target attributes, and emotion data sent from the device. The received data is organized and saved in JSON format, etc.

[1209] Step 5:

[1210] The server performs natural language processing and obtains the analysis results. Specifically, the server uses a natural language processing tool (e.g., an NLP library) to tokenize the text of the product features and extract important keywords and phrases. An extracted keyword may be "sugar-free."

[1211] Step 6:

[1212] The server references the target user's attribute information. The server retrieves marketing data corresponding to the target user's attributes (e.g., a health-conscious male in his 20s) from a database it has stored in advance. The retrieved data includes interests and concerns related to those attributes.

[1213] Step 7:

[1214] The server applies a catchphrase generation algorithm. The server uses a machine learning model to generate a catchphrase based on the obtained keywords, target user attribute data, and emotional data. For example, a catchphrase such as "For the health-conscious, sugar-free, delicious and safe" may be generated.

[1215] Step 8:

[1216] The server sends the generated catchphrase to the terminal. The generated catchphrase is formatted as an HTTP response and sent to the terminal. At this time, the following format is used as the response data.

[1217] json

[1218] {

[1219] "catchcopy": "For the health-conscious, sugar-free, delicious and safe"

[1220] }

[1221] Step 9:

[1222] The device displays the catchphrase to the user. The device parses the response data received from the server and displays the catchphrase on the user interface. Specifically, the catchphrase "For the health-conscious, sugar-free and delicious" is displayed on the smartphone screen or in the field of view of the head-mounted display.

[1223] 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.

[1224] 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.

[1225] 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.

[1226] [Fourth embodiment]

[1227] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1228] 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.

[1229] 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).

[1230] 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.

[1231] 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.

[1232] 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).

[1233] 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.

[1234] 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.

[1235] 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.

[1236] 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.

[1237] 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.

[1238] 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.

[1239] 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."

[1240] The present invention relates to a system for automatically generating catchy slogans based on the characteristics of a product or service selected by a user and the attributes of a target user. As an embodiment of the invention, the specific operation of the system will be described below.

[1241] System configuration

[1242] This system is broadly divided into the following three components:

[1243] 1. Users

[1244] 2. Terminal

[1245] 3. Server

[1246] System Operation Overview

[1247] 1. The user enters information

[1248] The user specifies the features and selling points of the product or service. They also input the attributes of the target users (e.g., age, gender, interests, etc.). For example, the user can input features of a new diet supplement such as "short-term results" and "100% natural ingredients," and specify "health-conscious women in their 30s" as the target users.

[1249] 2. The device sends the information to the server

[1250] The terminal formats the information the user enters and sends it to the server, for example in the following format:

[1251] json

[1252] {

[1253] "features": ["short-term results", "100% natural ingredients"],

[1254] "target": {"age": "30s", "interest": "health", "gender": "female"}

[1255] }

[1256] 3. The server starts processing

[1257] The server receives the information sent from the device, then analyzes the product / service features using natural language processing tools to extract important keywords, and then references the target user's attribute data to set conditions for generating an appropriate catchphrase.

[1258] 4. Generate a catchphrase

[1259] The server combines the data obtained through natural language processing with the target profile to run a catchphrase generation algorithm. For example, a machine learning model is used to generate a catchphrase such as "Become beautiful in a short time, in a healthy way, with the power of nature."

[1260] 5. Send the generated tagline to the device

[1261] The server sends the generated catchphrase to the terminal as an HTTP response.

[1262] 6. The device displays the tagline to the user.

[1263] The terminal visually displays the received tagline to the user, for example, the text "Get healthy and beautiful in a short time, with the power of nature" on the page of the web browser.

[1264] Specific examples

[1265] 1. Input example

[1266] Product and service features: "Short-term results" "100% natural ingredients"

[1267] Target users: "Health-conscious women in their 30s"

[1268] 2. Example of generated results

[1269] Catchphrase: "Be healthy and beautiful in a short time, with the power of nature."

[1270] In this way, this system allows users to efficiently and effectively generate catchy slogans that are appropriate for target users, significantly reducing the time and effort required to create catchy slogans and improving marketing effectiveness.

[1271] The processing flow will be explained below.

[1272] Step 1:

[1273] The user inputs the characteristics of the product / service and the attributes of the target user. The user inputs the specific characteristics and selling points of the product / service into a dedicated input form. At the same time, the user also inputs attribute information of the target user, such as age, gender, and interests.

[1274] Step 2:

[1275] The device formats the input information and sends it to the server. The device (such as a computer or smartphone used by the user) converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[1276] Step 3:

[1277] The server receives the information and begins the analysis process. The server analyzes the received HTTP POST request and extracts the product / service features and target user attributes.

[1278] Step 4:

[1279] The server performs natural language processing (NLP). The server analyzes the product features using natural language processing tools (e.g., tokenization, part-of-speech tagging) to identify important keywords and phrases.

[1280] Step 5:

[1281] The server references the target user's attribute information. The server then references a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[1282] Step 6:

[1283] The server applies a catchphrase generation algorithm. Based on the keywords obtained through natural language processing and the attributes of the target user, the server uses a catchphrase generation algorithm (e.g., machine learning model, rule-based model) to generate an appropriate catchphrase.

[1284] Step 7:

[1285] The server sends the generated catchphrase to the terminal. The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[1286] Step 8:

[1287] The device displays the catchphrase to the user. The device parses the HTTP response sent from the server and displays the catchphrase content in a format that is easy for the user to read. For example, the generated catchphrase "Be healthy, beautiful in a short time, with the power of nature" is displayed as part of a web page.

[1288] Example 1

[1289] 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."

[1290] Currently, in the marketing field, it takes a great deal of time and effort to understand the features of a product and generate a catchy slogan that is effective for target users. Furthermore, the quality of the catchy slogans is not stable, making it difficult to achieve consistent marketing results. To solve these problems, a system is needed that can automatically generate high-quality catchy slogans based on the product's features and the attributes of the target users.

[1291] 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.

[1292] In this invention, the server includes means for receiving information and obtaining analysis results using natural language processing technology, means for referencing attributes of the target user and generating a catchphrase using a catchphrase generation algorithm, and means for transmitting the generated catchphrase to the terminal, thereby enabling the user to quickly and effectively generate a catchphrase that appeals to the target user based on the input information.

[1293] A "user" is an individual or a corporation who inputs product features and target user attributes.

[1294] A "terminal" is a device that transmits information entered by a user to a server, and includes computers, smartphones, tablets, etc.

[1295] A "server" is a computer system that receives information, analyzes it, generates catchphrases, and returns it to the terminal.

[1296] "Product or service features" refer to the specific characteristics and appealing points of the product or service being offered.

[1297] "Target user attributes" refers to characteristic information such as age, gender, and interests of customers who are the target of marketing.

[1298] "Data formatting" is the process of converting information entered by a user into a standardized format (e.g., JSON).

[1299] "Natural language processing technology" is a technology for understanding and analyzing human language, and includes text analysis and keyword extraction.

[1300] A "catchphrase generation algorithm" is an algorithm for generating catchphrases for advertising and marketing purposes from input information.

[1301] A "generative AI model" is a type of artificial intelligence model that uses machine learning or deep learning to make predictions and generate results, and a specific example is GPT-3.

[1302] A "prompt" is an instruction that serves as input to the generative AI model, and specifically describes the requirements and conditions for generating a catchy slogan.

[1303] The present invention relates to a system that automatically generates catchy slogans based on the characteristics of a product or service entered by a user and the attributes of a target user. The following describes how to specifically implement the invention.

[1304] First, the user accesses the system using their own device (e.g., computer, smartphone, tablet). The user enters the product or service features and target user attributes on a form page provided through a web browser. For example, the user might enter "short-term results" and "100% natural ingredients" as features of a new diet supplement, and specify "health-conscious women in their 30s" as the target user attributes.

[1305] The terminal then formats the information you enter into JSON format, which looks like this:

[1306] json

[1307] {

[1308] "features": ["short-term results", "100% natural ingredients"],

[1309] "target": {"age": "30s", "interest": "health", "gender": "female"}

[1310] }

[1311] This data is sent to the server as an HTTP request.

[1312] The server processes the received JSON data. It uses natural language processing technology (e.g., NLTK, SpaCy) to extract important keywords from the characteristics of the product or service. It then references the target user's attribute data and sets the conditions for generating a catchy slogan.

[1313] Next, the server generates a catchphrase using a generative AI model (e.g., GPT-3).

[1314] Please create a catchy slogan for a new diet supplement that is "effective in a short time" and "made from 100% natural ingredients" for health-conscious women in their 30s.

[1315] Sentences such as these are input into a generative AI model.

[1316] Based on this, the generative AI model generates a tagline like this:

[1317] "Healthy, beautiful, and quick, with the power of nature"

[1318] The server sends the generated catchphrase to the terminal as an HTTP response.

[1319] Finally, the terminal visually displays the catchphrase received from the server to the user, thereby enabling the user to efficiently obtain an effective catchphrase for the target users.

[1320] Through the above process, users can quickly generate a catchy slogan that best suits the product's features and target users, thereby strengthening their marketing activities.

[1321] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1322] Step 1: User Enters Information

[1323] The user uses a terminal to access a form page on a web browser and enters the characteristics of the product or service and the attributes of the target user. The information entered is in the following format: a new diet supplement that is "effective in a short period of time" and "made from 100% natural ingredients," and "health-conscious women in their 30s."

[1324] Step 2: The device formats the input and sends it to the server

[1325] The terminal formats the information entered by the user into JSON, which is converted into the following data format:

[1326] json

[1327] {

[1328] "features": ["short-term results", "100% natural ingredients"],

[1329] "target": {"age": "30s", "interest": "health", "gender": "female"}

[1330] }

[1331] This formatted data is sent to the server as an HTTP request.

[1332] Step 3: The server receives the input and begins parsing it

[1333] The server receives the JSON data sent from the device. Based on the received data, it uses natural language processing technology (e.g., NLTK, SpaCy) to extract important keywords from the characteristics of the product or service. This process yields keywords such as "short-term results" and "100% natural ingredients."

[1334] Step 4: The server references the target profile and sets the conditions for generating the catchphrase.

[1335] The server combines the extracted keywords with the target user's attribute data. It references the target profile and generates a prompt for generating a catchphrase. An example of this prompt is, "Please generate a catchphrase for a new diet supplement that is effective in a short period of time and is made from 100% natural ingredients, aimed at health-conscious women in their 30s."

[1336] Step 5: The server generates a tagline using the generative AI model

[1337] The server uses a generative AI model (e.g., GPT-3) to generate a tagline based on the set prompt. The generative AI model receives the prompt as input and outputs the tagline, "Be healthy, beautiful, and fast, with the power of nature."

[1338] Step 6: The server sends the generated tagline to the device

[1339] The server sends the generated catchphrase "Get healthy and beautiful in a short time with the power of nature" to the terminal as an HTTP response. The terminal receives the catchphrase through this response.

[1340] Step 7: The device displays the tagline to the user

[1341] The terminal displays the catchphrase received from the server on the user interface. Specifically, the text "Get healthy, beautiful in a short time, with the power of nature" is displayed on the web browser page. This text display allows the user to obtain an effective catchphrase.

[1342] Through the above processing steps, the user can easily and quickly generate a catchy slogan suitable for the target user and use it in marketing activities.

[1343] (Application example 1)

[1344] 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."

[1345] In modern marketing, it is important to quickly generate catchy slogans that effectively appeal to target users. However, creating catchy slogans requires time and expertise, so an efficient generation method is needed. Current systems do not adequately meet this need, and there are particularly limited systems that are compatible with smart devices. Therefore, there is a need to provide new methods to improve the efficiency and effectiveness of marketing activities.

[1346] 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.

[1347] In this invention, the server includes a means for the user to input the features of the product / service and the attributes of the target user, a means for the terminal to format the input information and send it to the server, and a means for the server to receive the information, perform natural language processing, and obtain an analysis result. This makes it possible to automatically generate a catchy slogan using a catchy slogan generation algorithm by referring to the attributes of the target user, send it to the terminal, and display it on the smart device.

[1348] "User" refers to a person or group who inputs the characteristics of a product or service and the attributes of the target user.

[1349] "Terminal" refers to the equipment or device that formats and transmits information entered by a user to a server.

[1350] "Server" refers to a computer or platform that receives information sent from a terminal, analyzes it, and generates a catchphrase.

[1351] "Natural language processing" refers to techniques and methods that allow computers to understand and analyze human language.

[1352] "Analysis results" refers to the analysis results of data obtained through natural language processing.

[1353] "Target users" refers to groups or individuals who have the attributes of customers or users expected to be targeted at a particular product or service.

[1354] A "catchphrase generation algorithm" refers to a calculation procedure or program for generating effective catchphrases based on the attributes of target users and the characteristics of product services.

[1355] "Smart devices" refer to mobile information terminals and wearable devices that have Internet connectivity and can run applications.

[1356] This invention relates to a system that automatically generates catchy slogans based on the user's input of product / service characteristics and target user attributes. This system consists of three main components: the user, the terminal, and the server.

[1357] System Overview

[1358] 1. User input:

[1359] Users input the product / service features (e.g., short-term results, 100% natural ingredients) and the target user attributes (e.g., health-conscious women in their 30s). This allows for clear targeting of marketing.

[1360] 2. Terminal processing:

[1361] The terminal is responsible for formatting the information entered by the user, converting it into the appropriate format, and sending it to the server. To send data in JSON format, use the Python requests library, for example. For example, format it as follows:

[1362] json

[1363] {

[1364] "features": ["short-term results", "100% natural ingredients"],

[1365] "target": {"age": "30s", "interest": "health", "gender": "female"}

[1366] }

[1367] 3. Server processing:

[1368] The server receives the data sent from the device and analyzes the information using natural language processing tools (e.g., spaCy or Transformers). After analysis, it runs a slogan generation algorithm (e.g., machine learning model) based on the target user's attribute information and the characteristics of the product or service to generate an appropriate slogan.

[1369] 4. Submit and display your tagline:

[1370] The server sends the generated catchphrase to the terminal, which then visually displays it to the user using a web browser or smartphone application.

[1371] Hardware and software used

[1372] Hardware:

[1373] Smartphone (iOS or Android)

[1374] Server (Cloud server or on-premise server)

[1375] software:

[1376] Python

[1377] Flask (server-side framework)

[1378] requests library (for sending HTTP requests)

[1379] spaCy, Transformers (natural language processing tools)

[1380] Machine learning models (e.g., TensorFlow or PyTorch)

[1381] Specific examples

[1382] For example, if you are marketing a new diet supplement, the user might enter information like this:

[1383] Features: "Effective in a short period of time" "100% natural ingredients"

[1384] Target users: "Health-conscious women in their 30s"

[1385] The user enters this information into a smartphone application, which then converts the information into JSON format and sends it to a server. The server analyzes the received information and uses a machine learning model to generate a catchy slogan. The generated catchy slogan is "Become beautiful in a short amount of time, in a healthy way, with the power of nature." The smartphone application displays this to the user.

[1386] An example of a prompt sentence to input to the generative AI model is as follows:

[1387] Prompt: "The features of this product / service are 'short-term results' and '100% natural ingredients'. The target users are 'health-conscious women in their 30s'. Please generate a catchy slogan based on this."

[1388] This system allows users to quickly and effectively generate catchy slogans that appeal to target users, allowing them to efficiently carry out marketing activities.

[1389] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1390] Step 1:

[1391] The user inputs the characteristics of the product service and the attributes of the target user.

[1392] Input: Product / service features (e.g., "short-term results" and "100% natural ingredients") and target user attributes (e.g., "health-conscious women in their 30s")

[1393] Output: The information entered

[1394] Step 2:

[1395] The terminal formats the entered information and sends it to the server.

[1396] Input: Information entered in step 1

[1397] Data processing: Format the input information into JSON format

[1398] Output: Formatted JSON

[1399] Specific operation: The terminal formats the data in JSON format as shown below.

[1400] json

[1401] {

[1402] "features": ["short-term results", "100% natural ingredients"],

[1403] "target": {"age": "30s", "interest": "health", "gender": "female"}

[1404] }

[1405] The device sends the formatted JSON data to the server via an HTTP request.

[1406] Step 3:

[1407] The server receives the information, performs natural language processing, and obtains the analysis results.

[1408] Input: JSON data sent in step 2

[1409] Data Computation: Using natural language processing tools (e.g., spaCy or Transformers) to analyze features and target information within the JSON data

[1410] Output: Analysis results (extraction of important keywords and characteristics)

[1411] Specific operation: The server performs natural language processing to extract keywords such as "short-term," "effective," "natural ingredients," and "health-conscious" based on the product service's characteristics and target attributes.

[1412] Step 4:

[1413] The server refers to the attributes of the target user and generates a catchphrase using a catchphrase generation algorithm.

[1414] Input: Analysis results obtained in Step 3, product features, and target user information

[1415] Data calculation: Using a machine learning model (e.g., TensorFlow or PyTorch), a prompt is generated based on the analysis results, and the copy generation algorithm is driven based on that prompt.

[1416] Output: Generated tagline

[1417] Specific operation: The server generates a catchy slogan such as "Get healthy and beautiful in a short time with the power of nature."

[1418] Step 5:

[1419] The server transmits the generated catchphrase to the terminal.

[1420] Input: Tagline generated in step 4

[1421] Output: JSON data to be sent

[1422] Specific operation: The server sends JSON data containing the generated tagline to the terminal as an HTTP response.

[1423] Step 6:

[1424] The terminal displays the catchphrase to the user.

[1425] Input: JSON data containing the tagline submitted in Step 5

[1426] Output: The tagline that is visually displayed to the user

[1427] Specific operation: The device displays the tagline "Get healthy and beautiful in a short time, with the power of nature" to the user through a web browser or smartphone application.

[1428] 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.

[1429] The present invention relates to a system for automatically generating catchy slogans based on the characteristics of a product or service selected by a user and the attributes of target users. In particular, the present invention relates to a system for generating catchy slogans that are more optimized for target users by combining an emotion engine that recognizes user emotions.

[1430] System configuration

[1431] This system is broadly divided into the following four components:

[1432] 1. Users

[1433] 2. Terminal

[1434] 3. Server

[1435] 4. Emotion Engine

[1436] System Operation Overview

[1437] 1. The user enters information

[1438] The user inputs the features and selling points of the product or service. They also input the attributes of the target users (e.g., age, gender, interests, etc.). For example, the user inputs features of a new diet supplement such as "short-term results" and "100% natural ingredients," and specifies "health-conscious women in their 30s" as the target users.

[1439] 2. The device sends the information to the server

[1440] The terminal formats the information the user enters and sends it to the server, for example in the following format:

[1441] json

[1442] {

[1443] "features": ["short-term results", "100% natural ingredients"],

[1444] "target": {"age": "30s", "interest": "health", "gender": "female"}

[1445] }

[1446] 3. The device acquires the user's emotions and sends them to the server.

[1447] The device analyzes the user's current emotions using its emotion recognition function and transmits the information to the server, which also transmits the emotion information.

[1448] 4. The server receives the information and emotion data and starts the analysis process.

[1449] The server receives the information and emotion data sent from the device, then analyzes the product / service features using natural language processing tools and extracts important keywords.

[1450] 5. The server performs natural language processing (NLP)

[1451] The server analyzes the product service features using natural language processing tools (e.g., tokenization, part-of-speech tagging), thereby identifying important keywords and phrases.

[1452] 6. The server references the target user's attribute information

[1453] The server refers to a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[1454] 7. The server obtains the emotion analysis results using the emotion engine.

[1455] The server uses an emotion engine to analyze the emotion data and extract features based on the user's emotions.

[1456] 8. The server applies the tagline generation algorithm

[1457] The server generates an appropriate catchphrase using a catchphrase generation algorithm (e.g., machine learning model, rule-based model) based on the keywords obtained through natural language processing, the results of sentiment analysis, and the attributes of the target user.

[1458] 9. The server sends the generated tagline to the device.

[1459] The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[1460] 10. The device displays the tagline to the user.

[1461] The device parses the HTTP response sent from the server and displays the content of the tagline in a user-friendly format. For example, the tagline "Be healthy, beautiful, and fast with the power of nature" is displayed as part of a web page.

[1462] Specific examples

[1463] 1. Input example

[1464] Product and service features: "Short-term results" "100% natural ingredients"

[1465] Target users: "Health-conscious women in their 30s"

[1466] User sentiment: optimistic, positive state

[1467] 2. Example of generated results

[1468] Catchphrase: "Enjoy beauty in a short time with the power of healthy, natural ingredients."

[1469] In this way, this system allows users to efficiently and effectively generate catchy slogans that are appropriate for target users. This significantly reduces the time and effort required to create catchy slogans, improving marketing effectiveness. Furthermore, by incorporating the user's emotions, it is possible to generate catchy slogans that are more personal and relatable.

[1470] The processing flow will be explained below.

[1471] Step 1:

[1472] The user inputs the characteristics of the product / service and the attributes of the target user. The user inputs the specific characteristics and selling points of the product / service into a dedicated input form. At the same time, the user also inputs attribute information of the target user, such as age, gender, and interests.

[1473] Step 2:

[1474] The device formats the input information and sends it to the server. The device (such as a computer or smartphone used by the user) converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[1475] Step 3:

[1476] The device acquires the user's emotions and sends them to the server. Using its built-in emotion recognition function, the device recognizes the user's current emotions from facial expressions, voice data, etc., and sends this in data format to the server.

[1477] Step 4:

[1478] The server receives the information and emotion data. The server analyzes the content of the received HTTP POST request and extracts the product / service features, target user attributes, and user emotion data.

[1479] Step 5:

[1480] The server performs natural language processing (NLP), analyzing the product features using NLP tools (e.g., tokenization, part-of-speech tagging) to identify important keywords and phrases.

[1481] Step 6:

[1482] The server references the target user's attribute information. The server then references a pre-stored target profile database and extracts data according to the input attribute information (age, gender, interests, etc.).

[1483] Step 7:

[1484] The server obtains emotion analysis results using the emotion engine. The server analyzes the received emotion data using the emotion engine and extracts emotion features based on the user's current emotional state.

[1485] Step 8:

[1486] The server integrates the results of natural language processing, target user attribute information, and sentiment analysis results. Based on this information, the server sets up a catchphrase generation algorithm and determines the direction of the catchphrase to be generated.

[1487] Step 9:

[1488] The server applies a catchphrase generation algorithm to generate appropriate catchphrases using machine learning and rule-based models based on keywords obtained through natural language processing, sentiment analysis results, and target user attributes.

[1489] Step 10:

[1490] The server sends the generated catchphrase to the terminal. The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[1491] Step 11:

[1492] The device displays the catchphrase to the user. The device analyzes the HTTP response sent from the server and displays the catchphrase content in a format that is easy for the user to read. For example, the generated catchphrase "Achieve beauty in a fun and short time, with the power of healthy natural ingredients" is displayed as part of a web page.

[1493] Example 2

[1494] 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."

[1495] Conventional slogan generation systems have had difficulty generating personalized slogans that incorporate user emotions. Furthermore, generating slogans that take into account the characteristics of products and services and the attributes of target customers takes time, often preventing effective marketing. This has resulted in limitations on the quality of slogans and marketing effectiveness.

[1496] 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.

[1497] In this invention, the server includes: means for a user to input product / service features and target customer attributes; means for a terminal to format the input information and send it to the server; means for the terminal to acquire user emotion data and send it to the server; means for the server to use a natural language processing tool to analyze the received information and emotion data; means for the server to extract important keywords from the analysis results and refer to target customer attributes; means for the server to extract features based on the user's emotion using an emotion engine; means for the server to generate a catchy slogan using a catchy slogan generation algorithm; means for the server to send the generated catchy slogan to the terminal; and means for the terminal to display the catchy slogan to the user. This makes it possible to quickly generate more personalized, high-quality catchy slogans that take into account the user's emotions and the target customer attributes.

[1498] "User" refers to an individual or organization who uses the system to input product / service features and target customer attribute information in order to generate a catchy slogan.

[1499] A "terminal" is a device that allows a user to input information and that transmits that information to a server.

[1500] The "server" is a central processing unit that analyzes information sent from the terminal and generates a catchy slogan.

[1501] "Emotion data" is information that represents the user's current emotional state (e.g., optimistic, positive, etc.).

[1502] "Natural language processing tools" are software and algorithms used to analyze text data and identify important keywords and phrases.

[1503] "Target customers" are a group of consumers with specific attributes that should be targeted by the slogan.

[1504] An "emotion engine" is a function or software that analyzes a user's emotional data and extracts features based on the results.

[1505] The "catchphrase generation algorithm" is an algorithm for generating catchphrases based on input information, sentiment analysis results, and target customer attribute information.

[1506] This invention is a system that generates efficient and effective catchphrases based on the characteristics of products and services entered by users and the attributes of target customers. This system includes a user, a terminal, a server, and an emotion engine. The following describes the role of each entity, the hardware and software used, and specific operation.

[1507] User Input

[1508] The user inputs the characteristics of the product or service and the attributes of the target customer into the terminal. For example, the user might input "short-term results" and "100% natural ingredients" as the characteristics of a new diet supplement, and specify "health-conscious women in their 30s" as the target customer.

[1509] Device operation

[1510] The terminal formats the information entered by the user and sends it to the server. Specific hardware used is a computing device such as a PC or smartphone. Software used is a web browser or dedicated application. The terminal converts the entered data into a format such as JSON and sends it to the server using the HTTP POST method.

[1511] The device also has an emotion recognition function that uses a camera and microphone to analyze the user's facial expressions and voice, and sends the analysis results to a server as text data.

[1512] Server Processing

[1513] The server receives the information sent from the device and begins analysis. The server uses natural language processing tools (e.g., spaCy, NLTK) to analyze the text of the product or service features and extract important keywords. It also uses a stored target profile database to reference the attribute information of target customers.

[1514] Next, the server uses an emotion engine (e.g., IBM Watson, Microsoft Azure Emotion API) to analyze the user's emotion data and extract emotion-based features. Based on this information, the server applies a catchphrase generation algorithm (e.g., GPT-3) to generate an appropriate catchphrase.

[1515] Creating and displaying catchphrases

[1516] The server sends the generated catchphrase to the terminal as an HTTP response. The terminal parses the received HTTP response and displays the catchphrase to the user. The most common display format is to display the catchphrase as part of a web page or dedicated application.

[1517] Specific examples

[1518] Example input

[1519] Product and service features: "Short-term results" "100% natural ingredients"

[1520] Target customers: "Health-conscious women in their 30s"

[1521] User sentiment: optimistic, positive state

[1522] Example of generated results

[1523] Catchphrase: "Enjoy beauty in a short time with the power of healthy, natural ingredients."

[1524] Prompt Sentence Examples

[1525] Product and service features: "Short-term results" "100% natural ingredients"

[1526] Target customers: "Health-conscious women in their 30s"

[1527] User sentiment: optimistic, positive state

[1528] In this way, this system allows users to efficiently generate catchy slogans that are appropriate for their target customers. This significantly reduces the time and effort required to create catchy slogans, improving marketing effectiveness. Furthermore, by incorporating the user's emotions, it is possible to provide more personalized and relatable catchy slogans.

[1529] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1530] Step 1:

[1531] The user inputs product or service characteristics and target customer attribute information into the terminal. Specifically, the user inputs characteristic information such as "short-term results" and "100% natural ingredients" into the input form, as well as target customer information such as "health-conscious women in their 30s." The information entered is in text format, and the terminal temporarily stores it.

[1532] Step 2:

[1533] The device formats the user's input information and sends it to the server. The specific input is the text information mentioned above, which the device converts into JSON format. The information formatted as follows is sent to the server via the HTTP POST method: { 'features': ['short-term results', '100% natural ingredients'], 'target': {'age': '30s', 'interest': 'health', 'gender': 'female'}}.

[1534] Step 3:

[1535] The device acquires the user's emotional data and sends it to the server. For example, the device uses a camera and microphone to capture the user's facial expressions and voice, and analyzes them using emotion recognition software. As a result of this analysis, emotional data such as "optimistic" or "positive" is obtained. The acquired emotional data is then converted back to JSON format and sent to the server.

[1536] Step 4:

[1537] The server aggregates the information received from the devices and begins the analysis process. Specifically, the server analyzes the received JSON data and extracts information about the product or service's characteristics, target customer information, and user sentiment data. Python natural language processing tools (such as spaCy and NLTK) are used for the analysis to extract important keywords.

[1538] Step 5:

[1539] The server uses natural language processing tools to analyze the characteristics of products and services. For example, from input such as "short-term results" and "100% natural ingredients," it extracts important keywords such as "short-term," "effective," and "natural ingredients." The extracted keywords are then used to generate catchphrases.

[1540] Step 6:

[1541] The server references the target customer's attribute information from the database. For example, based on "Target: Health-conscious women in their 30s," the server retrieves the corresponding profile information from the target profile database. The retrieved profile information is used when generating the catchphrase.

[1542] Step 7:

[1543] The server uses an emotion engine to analyze the user's emotional data, for example, using IBM Watson's emotion analysis API to extract features to emphasize positive expressions from the received emotional data, such as "optimistic" and "positive."

[1544] Step 8:

[1545] The server uses a catchphrase generation algorithm to generate a catchphrase. Specifically, it uses a machine learning model (e.g., GPT-3) to generate a catchphrase using important keywords obtained through natural language processing, attribute information of target customers, and the results of sentiment analysis as prompts. The generated catchphrase will be a phrase such as "Achieve beauty in a short time with fun, healthy use of natural ingredients."

[1546] Step 9:

[1547] The server sends the generated catchphrase to the device. The generated catchphrase is then packaged again in JSON format and returned to the device as an HTTP response. The response content is in the format "{ 'catchphrase': 'Achieve beauty in a fun and short time, with the healthy power of natural ingredients'}".

[1548] Step 10:

[1549] The device displays the catchphrase received from the server to the user. The device parses the received HTTP response and extracts the catchphrase content. The device then displays the catchphrase in a specified location on the web page or dedicated application. For example, a part of the web page may display "Achieve beauty in a fun and short time, with the healthy power of natural ingredients."

[1550] (Application example 2)

[1551] 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."

[1552] In the modern advertising industry, there is a need to quickly and effectively create catchy slogans that appeal to target users. However, conventional methods have difficulty taking user emotions into account, and generating catchy slogans that resonate with users takes a great deal of time and effort. Therefore, there is a need for a system that can generate catchy slogans based on not only user input information but also real-time emotional data.

[1553] 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 the user to input the features of the product / service and the attributes of the target user; means for the terminal to format the input information and send it to the server; means for the terminal to recognize the user's emotions and send the data to the server; means for the server to receive the information and emotion data and start analysis processing; means for the server to perform natural language processing and obtain the analysis results; means for the server to refer to the attributes of the target user and generate a catchy slogan using a catchy slogan generation algorithm; means for the server to send the generated catchy slogan to the terminal; and means for the terminal to display the catchy slogan to the user. This makes it possible to quickly generate target-oriented catchy slogans that take user emotions into consideration.

[1554] A "user" is an entity that can input product features and target user attributes.

[1555] A "terminal" is a device that processes, formats, and transmits information entered by a user to a server.

[1556] The "server" is a central device that receives information and emotion data sent from the terminals, analyzes them, and generates catchphrases.

[1557] "Emotion recognition" is the process of analyzing a user's facial expressions and voice to identify their emotions at any given time.

[1558] "Natural language processing" is a technology that analyzes natural language and extracts important keywords and phrases.

[1559] A "catchphrase generation algorithm" is a calculation method for generating catchphrases optimized for target users based on input information and emotional data.

[1560] "Emotion data" is information about emotions obtained from analysis of the user's facial expressions and voice.

[1561] "Target users" are a group of users with certain attributes who are the target of advertisements and services.

[1562] A "catchphrase" is a short advertisement that effectively promotes a product or service.

[1563] A "machine learning model" is an algorithm that learns from large amounts of data and performs specific tasks.

[1564] The present invention relates to a system that automatically generates catchy slogans based on the features of a product or service and the attributes of target users. In particular, the system generates catchy slogans that are more optimized for target users by combining an emotion engine that recognizes the user's emotions.

[1565] This system is broadly divided into the following four components:

[1566] 1. Users

[1567] 2. Terminal

[1568] 3. Server

[1569] 4. Emotion Engine

[1570] Specific system configuration and operation

[1571] 1. The user enters information

[1572] Users input the characteristics of the product or service they want to advertise, as well as the attributes of the target users (e.g., age, gender, interests, etc.). Furthermore, emotional data is acquired in real time from the user's facial expressions and voice.

[1573] Example: "Characteristics: Sugar-free" "Target: Health-conscious men in their 20s"

[1574] 2. The device sends the information to the server

[1575] The device formats the information entered by the user and sends it to the server. The device also recognizes the user's emotions using the built-in camera and microphone and sends the emotional data to the server. The software module used for this purpose is "EmotionRecognizer."

[1576] 3. The server receives the information and emotion data and starts the analysis process.

[1577] The server receives the information and sentiment data sent from the device and analyzes the characteristics of the product or service using natural language processing (NLP) tools (e.g., tokenization, part-of-speech tagging, etc.). Based on the analysis results, important keywords and phrases are identified.

[1578] 4. The server references the target user's attribute information

[1579] The server references a pre-stored target profile database and extracts data based on the input attribute information (e.g., age, gender, interests, etc.).

[1580] 5. The server applies the tagline generation algorithm

[1581] The server applies a catchphrase generation algorithm (e.g., a machine learning model) based on the user's emotional data and keywords obtained through natural language processing to generate a catchphrase optimized for the target.

[1582] 6. The server sends the generated tagline to the device.

[1583] The server formats the generated catchphrase as an HTTP response and sends it to the terminal.

[1584] 7. The device displays the tagline to the user.

[1585] The terminal parses the HTTP response sent from the server and displays the catchy slogan in a format that is easy for the user to see.

[1586] Specific examples

[1587] Example input

[1588] Product / service features: "Sugar-free"

[1589] Target users: "Health-conscious men in their 20s"

[1590] User sentiment: optimistic, positive state

[1591] Example of generated results

[1592] Catchphrase: "For the health-conscious, this sugar-free drink is delicious and safe."

[1593] Examples of prompt statements

[1594] For products or services that contain "sugar-free," please generate a catchphrase that is best suited to "optimistic" "men" in their "20s." The target users are interested in "health-conscious."

[1595] In this way, more target-oriented catchphrases can be generated quickly and effectively, taking into account the user's emotions.

[1596] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1597] Step 1:

[1598] The user inputs the characteristics of the product or service and the attributes of the target user. Specifically, the user inputs the product features (e.g., sugar-free) and target attributes (e.g., health-conscious men in their 20s) through the interface of a smartphone or head-mounted display. A string of product features and target attributes is generated as input data.

[1599] Step 2:

[1600] The terminal formats the input information and sends it to the server. The terminal converts the input product features and target attributes into an appropriate format, such as JSON, and sends it to the server. Specifically, it is sent as JSON data in the following format:

[1601] json

[1602] {

[1603] "features": ["sugar-free"],

[1604] "target": {"age": "20s", "interest": "health-conscious", "gender": "male"}

[1605] }

[1606] Step 3:

[1607] The device recognizes the user's emotions and sends the data to the server. The device uses its built-in camera and microphone to analyze the user's facial expressions and voice in real time using an emotion recognition module (EmotionRecognizer). Attributes such as "optimistic" and "positive" are acquired as emotional data and sent to the server.

[1608] Step 4:

[1609] The server receives the information and emotion data and begins the analysis process. The server receives and records the product features, target attributes, and emotion data sent from the device. The received data is organized and saved in JSON format, etc.

[1610] Step 5:

[1611] The server performs natural language processing and obtains the analysis results. Specifically, the server uses a natural language processing tool (e.g., an NLP library) to tokenize the text of the product features and extract important keywords and phrases. An extracted keyword may be "sugar-free."

[1612] Step 6:

[1613] The server references the target user's attribute information. The server retrieves marketing data corresponding to the target user's attributes (e.g., a health-conscious male in his 20s) from a database it has stored in advance. The retrieved data includes interests and concerns related to those attributes.

[1614] Step 7:

[1615] The server applies a catchphrase generation algorithm. The server uses a machine learning model to generate a catchphrase based on the obtained keywords, target user attribute data, and emotional data. For example, a catchphrase such as "For the health-conscious, sugar-free, delicious and safe" may be generated.

[1616] Step 8:

[1617] The server sends the generated catchphrase to the terminal. The generated catchphrase is formatted as an HTTP response and sent to the terminal. At this time, the following format is used as the response data.

[1618] json

[1619] {

[1620] "catchcopy": "For the health-conscious, sugar-free, delicious and safe"

[1621] }

[1622] Step 9:

[1623] The device displays the catchphrase to the user. The device parses the response data received from the server and displays the catchphrase on the user interface. Specifically, the catchphrase "For the health-conscious, sugar-free and delicious" is displayed on the smartphone screen or in the field of view of the head-mounted display.

[1624] 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.

[1625] 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.

[1626] 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.

[1627] 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.

[1628] 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.

[1629] 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.

[1630] 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).

[1631] 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.

[1632] 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."

[1633] 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.

[1634] 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).

[1635] 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.

[1636] 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.

[1637] 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.

[1638] 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.

[1639] 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.

[1640] 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.

[1641] 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.

[1642] 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.

[1643] 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.

[1644] 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.

[1645] The following is further disclosed regarding the above embodiment.

[1646] (Claim 1)

[1647] [Means for users to input the characteristics of the product service and the attributes of the target users;

[1648] [means for the terminal to format and transmit input information to a server;

[1649] [Means for the server to receive information, perform natural language processing, and obtain analysis results;

[1650] [Means for the server to refer to the attributes of the target user and generate a catchphrase using a catchphrase generation algorithm;

[1651] [Means for the server to send the generated catchphrase to the terminal;

[1652] [Means for the device to display the catchphrase to the user;

[1653] A system including:

[1654] (Claim 2)

[1655] [The system according to claim 1, wherein the server performs natural language processing on the characteristics of the product service and the attributes of the target user.

[1656] (Claim 3)

[1657] [The system of claim 1, wherein the server uses a machine learning model as a catchphrase generation algorithm.

[1658] "Example 1"

[1659] (Claim 1)

[1660] A means for a user to input the characteristics of a product or service and attributes of a target user;

[1661] A means for the terminal to data format the input information and transmit it to the server;

[1662] A means for the server to receive the information and obtain an analysis result using natural language processing technology;

[1663] A means for the server to refer to the attributes of the target user and generate a catchphrase using a catchphrase generation algorithm;

[1664] A means for the server to transmit the generated catchphrase to the terminal;

[1665] a means for the terminal to display the catchphrase to the user;

[1666] A system including:

[1667] (Claim 2)

[1668] 2. The system of claim 1, wherein the server performs natural language processing techniques on the characteristics of the product or service and the attributes of the target user.

[1669] (Claim 3)

[1670] The system of claim 1, wherein the server uses a generative AI model as a catchphrase generation algorithm.

[1671] "Application Example 1"

[1672] (Claim 1)

[1673] A means for a user to input the characteristics of a product service and the attributes of a target user;

[1674] means for the terminal to format and transmit the input information to the server;

[1675] A means for the server to receive the information, perform natural language processing, and obtain the analysis results;

[1676] A means for the server to refer to the attributes of the target user and generate a catchphrase using a catchphrase generation algorithm;

[1677] A means for the server to transmit the generated catchphrase to the terminal;

[1678] a means for the terminal to display the catchphrase to the user;

[1679] an application means for displaying the generated catchphrase on a smart device;

[1680] A system including:

[1681] (Claim 2)

[1682] The system according to claim 1, wherein the server performs natural language processing on the characteristics of the product service and the attributes of the target user.

[1683] (Claim 3)

[1684] The system of claim 1, wherein the server uses a machine learning model as a catchphrase generation algorithm.

[1685] "Example 2: Combining Emotion Engines"

[1686] (Claim 1)

[1687] A means for a user to input the characteristics of a product or service and attributes of a target customer;

[1688] means for the terminal to format and transmit the input information to the server;

[1689] A means for the terminal to acquire user emotion data and transmit it to a server;

[1690] means for using natural language processing tools to analyze the information and emotion data received by the server;

[1691] A means for the server to extract important keywords from the analysis results and refer to the attributes of target customers;

[1692] A means for extracting features based on the user's emotions using an emotion engine in the server;

[1693] A means for the server to generate a catchphrase using a catchphrase generation algorithm;

[1694] A means for the server to transmit the generated catchphrase to the terminal;

[1695] a means for the terminal to display the catchphrase to the user;

[1696] A system including:

[1697] (Claim 2)

[1698] The system according to claim 1, wherein the server performs natural language processing on the characteristics of the product service and the attributes of the target customers.

[1699] (Claim 3)

[1700] The system of claim 1, wherein the server uses a machine learning model as a catchphrase generation algorithm.

[1701] "Application example 2 when combining emotion engines"

[1702] (Claim 1)

[1703] A means for a user to input the characteristics of a product service and the attributes of a target user;

[1704] means for the terminal to format and transmit the input information to the server;

[1705] A means for the terminal to recognize the user's emotion and transmit the data to a server;

[1706] A means for the server to receive the information and emotion data and start an analysis process;

[1707] A means for the server to perform natural language processing and obtain analysis results;

[1708] A means for the server to refer to the attributes of the target user and generate a catchphrase using a catchphrase generation algorithm;

[1709] A means for the server to transmit the generated catchphrase to the terminal;

[1710] a means for the terminal to display the catchphrase to the user;

[1711] A system including:

[1712] (Claim 2)

[1713] The system according to claim 1, wherein the server performs natural language processing on the characteristics of the product service and the attributes of the target user.

[1714] (Claim 3)

[1715] 2. The system of claim 1, wherein the server uses a machine learning model to generate catchy slogans using emotional data. [Explanation of symbols]

[1716] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for a user to input the characteristics of a product service and the attributes of a target user; means for the terminal to format and transmit the input information to the server; A means for the server to receive the information, perform natural language processing, and obtain the analysis results; A means for the server to refer to the attributes of the target user and generate a catchphrase using a catchphrase generation algorithm; A means for the server to transmit the generated catchphrase to the terminal; a means for the terminal to display the catchphrase to the user; A system including:

2. The system according to claim 1, wherein the server performs natural language processing on the features of the product service and the attributes of the target user.

3. The system of claim 1 , wherein the server uses a machine learning model as a catchphrase generation algorithm.

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