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Fast Algorithms for Time Series with applications to Finance, Physics, Music, Biology, and other Suspects

Summary: A database-focused tutorial on high-performance time-series methods across finance, physics, music, and biology: sliding-window correlations, burst detection, hum-to-music matching, and time-ordered data management. Draws on High Performance Discovery in Time Series, with case studies and open problems for streams and scientific computing. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3617
Venue
SIGMOD
Year
2004
Pagerank
4.1945683e-05
Overall Rank
12,584 | 12.46%
DOI
-

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Rank Citing Paper Year Venue Pagerank
2,276 Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series 2020 VLDB 9.1261944e-05
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