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Continually Evaluating Similarity-Based Pattern Queries on a Streaming Time Series

Summary: Continual similarity queries for streaming time series, using FFT-based cross-correlation to batch-distance the inflow stream against database patterns across future positions. Predicts future values to precompute distances and uses arrival-time errors to prune, delivering fast responses. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3426
Venue
SIGMOD
Year
2002
Pagerank
7.0171134e-05
Overall Rank
3,920 | 73.11%
DOI
10.1145/564691.564734

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{gao_sigmod02,
        title = {{Continually Evaluating Similarity-Based Pattern Queries on a Streaming Time Series}},
        author = {Gao, Like and Wang, X. Sean},
        series = {{SIGMOD} '02},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/564691.564734},
        url = {https://dl.acm.org/doi/10.1145/564691.564734},
        year = {2002}
}

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