Intelligent Content Discovery System for Automated User Profile Filtering
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Solution Overview
Problem
Content consumers face difficulties in discovering relevant content on the global Internet due to the vastness of the network, as they must manually search or subscribe to specific sources, leading to potentially interesting content going undiscovered.
Innovation Solution
A method and system for intelligent content discovery that parses previously viewed content, identifies and crawls content sources, filters updates based on user profiles and preferences, and presents a list of recommended content without requiring manual search or subscription.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual search or subscription to specific sources is used, then content consumers can discover relevant content, but the vastness of the network causes potentially interesting content to go undiscovered and requires significant user effort
Solution Approach 1:
The system enables self-service content discovery by automatically monitoring and crawling content sources based on user profiles and preferences without requiring manual user action. The content discovery system autonomously identifies, retrieves, and presents relevant content updates to users, eliminating the need for users to manually search or subscribe to multiple sources while ensuring comprehensive content coverage.
Solution Approach 2:
The patent introduces an intermediary content discovery system that acts as a mediator between users and the vast network of content sources. This intermediary automatically monitors content sources, filters content based on user profiles, and delivers relevant content to users, thereby resolving the contradiction between reducing user effort and preventing loss of relevant content.
2Ease of operation
If RSS feeds are used for automated content delivery, then content consumers are notified of changes without manual search, but users must still choose to subscribe to specific sources beforehand
Solution Approach 1:
The system provides universal content discovery by combining automated monitoring of multiple content sources with adaptive filtering based on user profiles. Unlike RSS feeds that require pre-selection of specific sources, this system universally monitors numerous content sources simultaneously and adapts the content delivery to each user's preferences, thereby achieving both automated delivery and source selection flexibility.
Solution Approach 2:
The content discovery system dynamically adapts to user preferences and behaviors by continuously learning from user interactions and adjusting content source monitoring and filtering accordingly. This dynamic adaptation allows the system to automatically subscribe to relevant content sources based on user needs without requiring manual user decisions, while maintaining flexibility to adjust to changing user preferences.
3Loss of information
If the system crawls multiple content sources to retrieve updated content, then comprehensive content coverage is achieved, but system complexity and resource consumption increase
Solution Approach 1:
The system applies local quality by differentiating the crawling and monitoring intensity for different content sources based on their relevance to user profiles. Instead of uniformly crawling all content sources with equal complexity, the system adjusts the monitoring depth and frequency for each source according to its importance, thereby achieving comprehensive coverage while optimizing system resources and reducing unnecessary complexity.
4Adaptability or versatility
If user profiles and preferences are used to filter content, then personalized content delivery is achieved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary action by pre-processing and organizing content from monitored sources according to user profiles and preferences before actual content delivery. Content is pre-filtered, categorized, and prepared in advance, so that when users request content or when updates are available, the personalized filtering has already been performed, significantly reducing the processing time required at the moment of content delivery.
Data Source
AI summary
Embodiments of the present invention provide a method, system and computer program product for intelligent content discovery for content consumers in the global Internet. In an embodiment of the invention, a method for intelligent content discovery for content consumers includes parsing a list of previously viewed content in a content browser executing in memory of a computer to identify different content sources for the previously viewed content. The method also includes directing crawling of the content sources over a computer communications network to retrieve updated content from the content sources. The method yet further includes filtering the updated content into a subset of updated content according to at least one parameter corresponding to one of an end user profile of an end user and an end user preference of the end user. Finally, the method includes presenting a list of the subset of updated content in the content browser.