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Fast Approximate Correlation for Massive Time-series Data

Summary: Fast all-pair Pearson correlation over massive time-series using DFT and graph partitioning to cut I/O and CPU. Two approximation methods with guarantees: bounded-error similarity and thresholding with no false positives/negatives, plus batch caching; up to 17× faster than prior exact methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4242
Venue
SIGMOD
Year
2010
Pagerank
0.00010558719
Overall Rank
1,786 | 87.58%
DOI
-

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