Spam Detection for User-Generated Video Metadata
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Solution Overview
Problem
User-generated videos on hosting websites often employ 'spamdexing' or 'keyword stuffing' to manipulate search results, making it difficult for viewers to find relevant content, as existing technologies fail to effectively detect and mitigate spam in metadata.
Innovation Solution
A system and method for automatically identifying and removing or adjusting the ranking of videos with spam metadata, using techniques such as determining unique words, concept clustering, and analyzing the frequency of video appearances in search queries to identify and address spam content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users add more keywords and metadata to videos, then search visibility improves, but spam detection difficulty increases
Solution Approach 1:
The patent introduces an intermediary spam detection system that acts as a mediator between video metadata and search results. This system analyzes metadata patterns, identifies spammy behavior, and adjusts search rankings accordingly, preventing direct manipulation while maintaining legitimate search functionality.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring search query patterns, video viewing behavior, and metadata usage. When spammy patterns are detected (such as excessive keywords or manipulation tactics), the system adjusts search rankings and provides feedback to both users and content creators about search result relevance.
2Object-generated harmful factors
If keyword stuffing is used to manipulate search results, then video prominence increases, but search result quality deteriorates
Solution Approach 1:
The patent extracts and removes spammy metadata elements from search results. By identifying and filtering out excessive or manipulative keywords, the system separates legitimate search results from spammy content, preserving search quality while allowing videos to be discovered through legitimate means.
Solution Approach 2:
The system changes the parameters used for search ranking by weighting metadata differently. Instead of simply counting keyword frequency, the system adjusts parameters to penalize excessive keywords, prioritize relevant metadata, and consider user behavior patterns, thereby maintaining search quality while reducing spam impact.
3Measurement precision
If spam detection algorithms are made more sophisticated, then spam detection accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the spam detection system into multiple independent modules: metadata analysis, pattern recognition, behavior monitoring, and ranking adjustment. Each module handles a specific aspect of spam detection, making the overall system more manageable and easier to maintain while improving detection accuracy through specialized processing.
Data Source
AI summary
A system, a method, and various software tools enable a video hosting website to automatically identify posted video items that contain spam in the metadata associated with a respective video item. A spam detection tool for user-generated video items based on concept clustering is provided that facilitates the detection of spam in the metadata associated with a video item.