Correlation Joins over Time Series Data Streams Utilizing Complementary Dimension Reduction and Transformation
Summary: CorrJoin hybridizes PAA and SVD to compress time-series windows and enable bucketing-based coarse filtering for correlation joins over streams. A second Euclidean-distance filter prunes false positives before exact correlation, delivering up to 20× speedups over Quickjoin. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. AmirReza Alizade Nikoo (University of Zurich)
- 2. Michael H. Böhlen (University of Zurich)
- 3. Sven Helmer (University of Zurich)
BibTeX Citation
@inproceedings{nikoo_sigmod23,
title = {{Correlation Joins over Time Series Data Streams Utilizing Complementary Dimension Reduction and Transformation}},
author = {Nikoo, AmirReza Alizade and Böhlen, Michael H. and Helmer, Sven},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3626722},
url = {https://dl.acm.org/doi/10.1145/3626722},
year = {2023}
}
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