Multimedia Duplicate Detection via Block Hashing
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Solution Overview
Problem
Current service systems face challenges in reliably identifying and reducing duplicates of multimedia data items, which affects the reliability of multimedia content provided to users.
Innovation Solution
A method involving maintaining service system hash values, hashing received multimedia data items, and searching for matches within these values to determine duplicates, with approved items being stored and rejected items triggering further evaluation or rejection messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multimedia data items are uploaded to the service system without duplicate checking, then the upload process is fast and simple, but duplicate content accumulates and reduces system reliability
Solution Approach 1:
The multimedia data is segmented into fixed-size blocks, and hash values are computed for each block individually. This segmentation allows the system to efficiently compare only relevant portions of data without processing entire large files, reducing computational complexity while maintaining duplicate detection accuracy.
Solution Approach 2:
The patent replaces direct comparison of entire multimedia files with a computational hashing mechanism. Instead of mechanically comparing byte-by-byte across large data items, the system uses hash function computations to generate compact representations that can be quickly compared, significantly reducing processing complexity.
2Measurement precision
If hash values for all multimedia data items are maintained and compared, then duplicate detection accuracy is high, but processing time and computational resources increase
Solution Approach 1:
By dividing multimedia data into blocks and computing hashes for each block separately, the system achieves accurate duplicate detection through block-level comparison while reducing the overall computational burden compared to hashing entire large files. This segmentation enables parallel processing and faster search operations.
Solution Approach 2:
The patent changes the parameter of data representation from complete multimedia files to condensed hash values. This parameter transformation maintains the ability to identify duplicates accurately while dramatically reducing the time and resources required for comparison and search operations.
3Measurement precision
If block size for hashing is small, then duplicate detection precision is high, but processing overhead increases
Solution Approach 1:
The system optimizes the block size parameter to achieve an optimal balance between detection precision and processing efficiency. By carefully selecting the block size, the patent ensures sufficient granularity for accurate duplicate identification while maintaining reasonable processing throughput and minimizing overhead.
Data Source
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AI summary
A method reducing duplicates of multimedia data items in a service system, wherein the method comprises maintaining service system hash values for the multimedia data items of the service system; receiving a first multimedia data item; and hashing the received multimedia data item to provide a first hash value. The method further comprises searching the first hash value from the service system hash values; and approving the received multimedia data item to the service system in response to the first hash value being not found when searching from the service system hash values.