Media Fingerprint Hash Seeding for Uniform Bucket Distribution
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Solution Overview
Problem
Existing audio fingerprinting systems face inefficiencies due to irregular hash table bucket distributions caused by sub-optimal hash seed selection, leading to increased computational resources and search times during fingerprint retrieval.
Innovation Solution
A computing system calculates entropy values to determine optimal hash seeds for distributing subfingerprints among buckets, promoting uniformity and reducing search times by selecting hash seeds that maximize entropy values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sub-optimal hash seeds are used for distributing subfingerprints, then the system is simpler to implement, but the hash table bucket distribution becomes irregular leading to increased search times and computational resources
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing optimal hash seeds in a lookup table before actual fingerprinting operations. The system pre-processes potential hash seeds, evaluates their distribution quality using entropy calculations, and stores the best candidates for immediate retrieval during runtime, eliminating the need for complex real-time hash seed optimization
Solution Approach 2:
The patent changes the parameter of hash seed selection from arbitrary or simple sequential values to optimized values selected based on entropy-based distribution metrics. By evaluating multiple hash seed candidates and selecting those that produce the most uniform bucket distributions, the system transforms a simple parameter into an optimized one that directly improves search performance
2Stability of the object's composition
If optimal hash seeds are calculated using entropy values to maximize uniformity, then the distribution of subfingerprints becomes even, but the computational complexity and time for determining hash seeds increases
Solution Approach 1:
The patent resolves this contradiction by performing the time-consuming entropy calculation and optimal hash seed selection in advance, before the actual fingerprinting and search operations begin. The pre-computed optimal hash seeds are stored in a lookup table, allowing the system to achieve uniform distribution without paying the computational cost during runtime
Solution Approach 2:
The patent creates a copy of the optimal hash seed selection process during system initialization or offline processing. Instead of repeatedly performing complex entropy calculations during operational phases, the system copies the results of these calculations into a reusable lookup table that can be quickly referenced during actual fingerprinting operations
3Measurement precision
If vast quantities of known audio information are stored for comparison, then the accuracy of fingerprint matching improves, but the time and resources required for comparison increase significantly
Solution Approach 1:
The patent applies segmentation by dividing the large database of known audio information into multiple hash tables, each organized with optimized hash seeds. This segmentation allows the system to distribute query load across multiple smaller, efficiently-organized data structures, maintaining high matching accuracy while reducing the time required to search through vast quantities of audio data
Solution Approach 2:
The patent changes the organizational parameter of the audio database from conventional storage to entropy-optimized hash table distribution. By organizing known audio information according to optimal hash seeds determined through entropy analysis, the system enables faster retrieval and comparison operations while preserving the ability to accurately match fingerprints against vast quantities of stored audio data
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed for efficient media indexing. An example method disclosed herein includes means for initiating a list of hash seeds, the list of hash seeds including at least a first hash seed value and a second hash seed value among other hash seed values, means for generating to generate a first bucket distribution based on the first hash seed value and a first hash function and generate a second bucket distribution based on the second hash seed value used in combination with the first hash seed value, means for determining to determine a first entropy value of the first bucket distribution, wherein data associated with the first bucket distribution is stored in a first hash table and determine a second entropy value of the second bucket distribution.