Partitioned Search Indexes for Real-Time Media Segment Identification
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Solution Overview
Problem
The challenge of managing and efficiently identifying thousands of broadcast and on-demand content channels in television systems, particularly with automated content recognition (ACR) systems, due to the vast amount of data required for accurate and real-time content identification.
Innovation Solution
Partitioning large volumes of content into multiple indexes or 'buckets' based on parameters such as popularity and type, and searching these buckets in parallel to enhance accuracy and efficiency of content recognition, using techniques like path pursuit and automated speech recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a single large index is used to store all content identifiers, then the system can maintain a comprehensive database of all broadcast and on-demand content, but the search time and computational resources increase significantly
Solution Approach 1:
The patent divides the large content database into multiple smaller indexes organized in a tree structure with hierarchical levels. Each index contains a subset of content identifiers, allowing the system to maintain comprehensive content coverage while reducing search time by only examining relevant portions of the database.
2Loss of time
If the content database is divided into multiple smaller indexes, then the search time and computational resources are reduced, but the system complexity increases due to multiple indexes to manage
Solution Approach 1:
The patent implements a nested tree structure where indexes are organized in hierarchical levels with parent-child relationships. Each level contains indexes that reference or contain indexes from the next level, creating a nested organization that reduces overall system complexity while enabling efficient searches through the hierarchical navigation.
3Measurement precision
If content is segregated into different indexes based on popularity or type, then the accuracy of content identification is improved by reducing false positives, but the device complexity increases due to multiple segmentation criteria
Solution Approach 1:
The patent applies different segmentation strategies to different portions of the content database based on local characteristics. Popular content, local channels, and on-demand content are segregated into specific indexes appropriate to their nature, allowing optimized search paths for different content types while maintaining overall system efficiency.
Data Source
AI summary
Systems and methods for identifying a media segment of audio or video content are described. The video segment is identified by deriving data from media content and comparing said data to a reference database in order to identify said video segment. Embodiments of the invention improve the speed and accuracy of the media identification process by advantageously partitioning the indexes in subdivisions where high value reference information is separated from the bulk information, for example.