Generative AI Content Adaptation From Scrolling Behavior Signals
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Solution Overview
Problem
Existing web content environments struggle to provide real-time, user-customized content that accurately reflects user preferences and behaviors, leading to suboptimal engagement and satisfaction.
Innovation Solution
A method and system utilizing generative artificial intelligence to collect user content and behavior information, infer preferences, and generate targeted content in real-time, adjusting based on scrolling behavior and content consumption time, while considering provider settings and user consent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional content delivery methods are used, then system complexity is low, but user engagement and content personalization are insufficient
Solution Approach 1:
The patent introduces a generative AI model as an intermediary component between the user behavior data and the content delivery system. This mediator processes user behavior information, infers preferences, and generates personalized content recommendations, thereby enabling content adaptation without requiring complex restructuring of the entire delivery system.
Solution Approach 2:
The system performs preliminary actions by collecting and storing user behavior information in advance, and using the generative AI model to pre-infer user preferences before content delivery. This allows the system to quickly provide personalized content without performing complex real-time analysis during the actual delivery process.
2Productivity
If real-time content generation is implemented, then user engagement improves, but processing time and computational resources increase
Solution Approach 1:
The system collects and stores user behavior information in advance, and the generative AI model pre-processes this data to infer user preferences before actual content delivery requests. This preliminary processing reduces the computational burden and time required during real-time content generation.
Solution Approach 2:
The generative AI model creates simplified representations or copies of user preference patterns based on historical behavior data. These copied preference models can be quickly applied to generate personalized content without performing full complex analysis each time, thereby reducing processing time while maintaining personalization quality.
Data Source
AI summary
A method and system for providing customized content using generative artificial intelligence is disclosed. According to one example embodiment, a method for providing content may include collecting content information of original content and behavior information of a user for the original content, in relation to the original content already provided to the user, inferring preference information of the user based on the content information and the behavior information, generating target content through a generative artificial intelligence model based on the inferred preference information of the user, and providing the generated target content.