Video Graph Content Identification via Segmentation and Fingerprints
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Solution Overview
Problem
The challenge in identifying and discovering desired electronic content, such as video content, across multiple websites in a network environment like the Internet is exacerbated by the abundance of duplicative content, making it difficult for users to find relevant content based on their preferences or social networking recommendations.
Innovation Solution
A computer-implemented system and method that utilizes video graph data to identify similar video content by analyzing audio and visual similarities between video clips, generating fingerprints, and applying association rules to connect similar content, thereby recommending relevant videos to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If electronic content is widely distributed across multiple websites to maximize viewership, then the reach and accessibility of content is improved, but the difficulty of identifying desired content increases due to abundant duplicative content
Solution Approach 1:
The patent segments video content into distinct clips and organizes them in a hierarchical tree structure with categories and subcategories. This segmentation allows users to navigate through organized content rather than searching through all distributed content indiscriminately, resolving the contradiction by maintaining wide distribution while enabling efficient identification through structured organization.
Solution Approach 2:
The patent introduces an intermediary recommendation system that analyzes user profiles, viewing history, and content metadata to generate personalized recommendations. This intermediary layer mediates between the user and the vast distributed content, filtering and prioritizing content based on relevance rather than requiring users to search through all available content directly.
2Adaptability or versatility
If duplicative video content is allowed to maximize content availability, then content accessibility is improved, but user experience deteriorates due to difficulty in finding relevant content
Solution Approach 1:
The patent performs preliminary organization of video content into a hierarchical tree structure with categories, subcategories, and metadata tagging before user interaction. This preliminary structuring enables users to quickly locate desired content through organized navigation rather than searching through duplicative content, improving ease of operation while maintaining content availability.
Solution Approach 2:
The patent implements feedback mechanisms that analyze user viewing behavior, preferences, and interactions with recommended content. This feedback is used to continuously refine and personalize recommendations, improving user experience by learning from user responses while maintaining broad content availability through the organized structure.
3Measurement precision
If comprehensive video content analysis is performed to improve content identification accuracy, then identification precision is improved, but processing time and computational resources increase
Solution Approach 1:
The patent segments video content into smaller clips and analyzes them individually, generating fingerprints for each segment. This segmentation allows for efficient comparison and matching without requiring analysis of entire videos, improving identification precision while reducing processing time through divide-and-conquer approach.
Solution Approach 2:
The patent applies different analysis depths to different content segments based on their relevance and user interaction patterns. Frequently accessed or highly relevant content receives more detailed analysis, while less critical content receives lighter processing. This local quality approach optimizes the balance between identification accuracy and processing efficiency.
Data Source
AI summary
Systems and methods are provided for identifying and recommending electronic content to consumers. In accordance with an implementation, one or more elements of electronic content are identified based on video graph data. In an exemplary method, information associated with a first element of video content is received, and corresponding video graph data is obtained. One or more second elements of video content that are similar to the first element of video content are identified based on the obtained video graph data. A subset the first and second elements of video content is subsequently identified for delivery to the user.