Concatenated Media Content Representation Database Indexing
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Solution Overview
Problem
Existing content identification systems rely on pre-indexed databases and separate buckets for media content recognition, which can lead to inefficient search processes and increased overhead, especially when dealing with large databases of media recordings.
Innovation Solution
A method that involves concatenating representations of multiple media content recordings into a single data file, allowing for a single search operation and mapping identifiers to global positions, enabling efficient content recognition by eliminating the need for separate buckets and simplifying data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separate buckets are used for each media content recording in the database index, then content identification can be performed, but search efficiency decreases and overhead increases when dealing with large databases
Solution Approach 1:
The patent merges multiple separate buckets containing representations of individual media content recordings into a single unified data file. This consolidation eliminates the overhead of managing multiple separate data structures while maintaining the ability to perform accurate content identification through unified sequential access and bulk processing operations.
2Adaptability or versatility
If separate buckets are used for each media content recording, then content can be indexed individually, but device complexity and overhead increase
Solution Approach 1:
Multiple separate bucket data structures are merged into a single unified data file, reducing the complexity of managing multiple indexed structures while preserving the ability to index and retrieve individual media content recordings through positional information and metadata associations.
3Reliability
If a traditional pre-indexed database with separate buckets is used, then content recognition can be performed, but processing time increases for large databases
Solution Approach 1:
The system performs preliminary organization of media content representations into a unified sequential data file with associated metadata, enabling efficient bulk processing and reduced search time during content recognition operations without sacrificing identification accuracy.
Solution Approach 2:
By combining all media content representations into a single unified data structure, the system enables more efficient bulk processing operations and reduces the time required to search through large databases during content recognition tasks.
Data Source
AI summary
Methods and systems for arranging and searching a database of media content recordings are provided. In one example, a method is provided that comprises receiving a sample of media content, and performing, by a computing device, a content recognition of the sample of media content using a data file including a concatenation of representations for each of a plurality of media content recordings. In other examples, another method is provided that comprises receiving media content recordings, determining a representation for each media content recording, concatenating by a computing device the representation for each media content recording as a data file, and storing by the computing device a mapping between an identifier for a respective media content recording and a global position in the data file that corresponds to the representation of the respective media content recording.