KR-20260066210-A - AI-Based Personalized Advertising Generation System

Abstract

The present invention relates to an advertising system that generates and provides user-customized advertisements in real time through artificial intelligence (AI) and big data analysis. The present invention collects user data, such as web search history, social media activity, location information, and purchase history, and analyzes users' interests and consumption patterns using deep learning and natural language processing (NLP) technologies. Through this, advertisements are automatically generated to match user characteristics, and advertisements tailored to the user's latest interests can be provided through real-time optimization functions. Furthermore, advertising performance is evaluated in real time through various indicators such as click-through rates and conversion rates, and AI learns from performance data to continuously improve the accuracy and efficiency of the advertisements. Personal information is protected through encryption and anonymization, and advertisers can expect increased advertising efficiency, while users can expect enhanced immersion by experiencing advertisements suitable for them.

Inventors

• 이정윤

Assignees

• 이정윤

Dates

Publication Date

20260512

Application Date

20241104

Claims (5)

1. The present invention relates to a user-customized advertising delivery system comprising a method for collecting user data, analyzing the data, and generating advertisements tailored to the interests and behavioral patterns of individual users. The collected data includes the user's search history, website visit records, location information, purchase history, etc., which can improve the accuracy of advertising targeting. The present claim relates to the configuration of a system for providing advertisements based on user interests.
2. According to Claim 1, the present invention relates to a user-customized advertising delivery system comprising a data filtering and preprocessing module that preprocesses collected user data to provide only refined data suitable for analysis. The preprocessing module removes noise data and distinguishes users' interests by time period, thereby enabling accurate advertising targeting. The present claim claims a system that enhances advertising accuracy through a data refinement and preprocessing process.
3. According to Claim 1, the present invention relates to a system comprising a real-time optimization module that analyzes user behavior data in real time and updates advertising content based thereon to provide timely, customized advertisements to the user. The module utilizes AI algorithms to reflect the user's latest interests and supports the maximization of advertising performance according to goals set by the advertiser. The present claim claims a system that enhances advertising effectiveness through real-time data optimization.
4. According to Claim 1, the present invention relates to a system comprising an advertising performance analysis module that monitors and analyzes advertising performance to evaluate whether an advertiser has achieved their goals and improves advertising content based on performance data. The module collects advertising performance indicators, such as click-through rates and conversion rates, in real time, thereby enabling the advertiser to determine advertising efficiency and formulate an optimized advertising strategy. The present invention claims a system that provides performance analysis and feedback.
5. According to Claim 1, the present invention relates to a system comprising a personal information protection and security management module that includes data encryption and access restriction functions to securely protect collected user data. The module prevents infringement from external sources through the anonymization and encryption of data, and enhances personal information protection by managing data access rights based on user consent. The present claim claims a user-customized advertising system with enhanced personal information protection and security.

Description

AI-Based Personalized Advertising Generation System This invention relates to a technology for an advertising system that automatically generates and provides personalized advertising content for individual users by utilizing artificial intelligence (AI) and big data analysis. Specifically, this invention is a technology that analyzes various online and offline data based on deep learning algorithms and natural language processing (NLP) to identify individual users' interests, preferences, and consumption patterns in real time, and thereby generates customized advertising content. Furthermore, this invention supports efficient advertising operations for advertisers by automating all processes of data collection, analysis, ad generation, and distribution. Unlike conventional mass media advertising or limited targeting methods, this invention enables sophisticated ad targeting based on user data, allowing for high conversion rates and advertising effectiveness. Moreover, by continuously updating advertisements based on real-time user behavior data, it provides advanced advertising technology that reflects changing consumer interests and optimizes interaction with users. This technology is particularly expected to yield innovative advertising effects in the fields of digital marketing, e-commerce, and social media advertising, and relates to a system that enables a highly immersive advertising experience for users and improved performance measurement for advertisers. 1. Big Data Analysis Technology Big data analytics technology is used to collect massive amounts of user data and identify individual users' behavioral patterns, interests, and demographic characteristics. Through this technology, advertising systems process vast amounts of data in real time, securing the foundational data necessary for generating advertising content. In particular, it is utilized to predict user preferences based on factors such as interest in specific products and purchase history. 2. Deep Learning Algorithms Deep learning is a core technology in the field of artificial intelligence and is primarily used for pattern recognition, classification, and predictive modeling. In this invention, deep learning is utilized to build a personalized advertising recommendation model by learning user behavior data. The deep learning model learns autonomously through data to precisely predict users' consumption patterns and preferences, and improves the accuracy and performance of advertisements through continuous learning. 3. Natural Language Processing (NLP) Technology Natural Language Processing (NLP) is a technology that understands and processes text data, playing a crucial role in analyzing various text-based user data, such as social media comments, reviews, and search queries. Through NLP technology, it is possible to analyze text written by users to identify which products or services they are interested in and what emotions they are expressing. This enables the creation of advertising messages optimized for individual emotions and interests. 4. Real-time data processing and streaming technology Real-time data processing technology collects and processes user behavioral data in real time, enabling immediate responses. It provides the capability to detect user actions, such as visiting websites or searching for products, in real time and instantly display relevant advertisements. This real-time data processing allows for sophisticated ad targeting by reflecting users' latest interests. 5. Machine Learning-Based Recommendation System Recommendation systems are technologies that recommend content or products tailored to individual characteristics, playing a crucial role in the advertising field by providing personalized ads. By learning from past user data and behavioral history, recommendation systems perform the function of recommending the most suitable advertising content to each user. These systems are implemented particularly on e-commerce platforms in the form of purchase-inducing ads and product recommendations, playing a key role in increasing ad click-through rates and conversion rates. 1. Build User Data Collection Module This invention establishes a module for collecting various user data for personalized advertising. Key data includes the user's website visit history, search terms, social media activity, location information, consumption and purchase history, etc. This data is utilized as foundational information for analyzing users' interests and behavioral patterns, and is securely stored through encryption and anonymization in compliance with personal information protection regulations. Data collection takes place in real time, enabling targeted advertising tailored to the user based on the data stored on the server. 2. Data Preprocessing and Filtering Process Collected data undergoes preprocessing and filtering before being used to generate advertisements. This process removes unnecessary noise and extracts only the refin