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Topic Name Methods Used Abstract by rahmashifapk415 is a document available to read on EtoBox.
This paper introduces a parallel algorithm for processing unstructured data in machine learning using multiple GPUs and LZ-complexity-based string distance. The method significantly improves efficiency, achieving up to 528× speed-up over traditional methods, and enhances accuracy in time-series classification tasks compared to TFIDF-based approaches. The system processes raw data directly with minimal formatting, demonstrating its effectiveness for large-scale unstructured data analysis.
- Author
- rahmashifapk415
- Language
- EN