AI Personalized Webpage Aggregation for Information Overload
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Solution Overview
Problem
Users face challenges in navigating and filtering relevant information on various websites and applications, as existing systems lack personalized and consistent presentation, leading to information overload and the need to sift through non-interest content, including advertisements.
Innovation Solution
A method and apparatus that uses an AI algorithm to categorize and filter information into 'of interest' and 'of non-interest' items, presenting them in a consistent format, allowing users to customize preferences such as font size and layout, and employing dynamic content blocking and personalized notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple different webpages are presented to users, then information diversity is improved, but navigation complexity and user learning burden increase
Solution Approach 1:
The patent creates a universal personalized webpage interface that aggregates content from multiple different webpages (FoxNews.com, CNN.com, etc.) into a single consistent format. This universal interface allows users to access diverse information sources without learning multiple navigation systems, as all content is presented through a standardized personalized layout that adapts to user preferences.
Solution Approach 2:
The system introduces an intermediary personalized webpage that sits between the user and multiple source webpages. This intermediary layer extracts and represents content from various sources in a unified format, mediating the interaction between diverse information sources and the user's need for consistent navigation while maintaining information diversity.
2Quantity of substance
If comprehensive webpage content is displayed to users, then information completeness is improved, but information overload and relevance filtering difficulty increase
Solution Approach 1:
The system extracts only the most relevant items from comprehensive webpage content using AI algorithms. Instead of displaying all content from source webpages, the system selectively extracts and presents items that are most likely to be of interest to the user, based on AI-driven relevance assessment and user feedback, thereby maintaining information completeness while reducing overload.
Solution Approach 2:
The personalized webpage applies local quality by presenting different types of content with different levels of detail and prominence based on their relevance to the user. The AI algorithm determines which items receive prominent display and which are filtered or summarized, creating a non-uniform presentation that optimizes relevance detection for each specific content item.
3Measurement precision
If AI filtering is applied to reduce information overload, then relevance precision is improved, but system complexity increases
Solution Approach 1:
The system employs feedback mechanisms where user interactions with the personalized webpage (clicks, time spent, selections) are continuously fed back to the AI algorithm. This feedback loop allows the system to refine its relevance precision over time without requiring increasingly complex filtering logic, as the AI learns from actual user behavior patterns to improve content selection accuracy.
Solution Approach 2:
The AI-driven personalized webpage performs self-service by automatically adapting its content selection and presentation based on user feedback without requiring manual configuration or complex rule-based filtering systems. The system autonomously improves its relevance precision through machine learning from user interactions, reducing the need for manually maintained complex filtering mechanisms.
Data Source
AI summary
A method and apparatus comprising generating a dynamic personalized webpage is disclosed. At least two webpages are loaded in a fashion that is hidden from the user. Content from the at least two webpages is extracted based on classification “of interest” by an artificial intelligence algorithm. A dynamic personalized webpage comprising extracted content is then generated and displayed to the user. In the preferred embodiment, the user's dynamic personalized webpage will be filled with advertisements tailored to the user and the user would receive at least some revenue from advertisements.