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Online Event-driven Subsequence Matching over Financial Data Streams

Summary: Online, event-driven approximate subsequence matching over massive financial streams via online segmentation and pruning to a concise piecewise-linear representation. Permutation-based similarity with a metric distance enables flexible indexing and selective, event-driven search; validated on real stock data for trend prediction. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3566
Venue
SIGMOD
Year
2004
Pagerank
6.339805e-05
Overall Rank
5,162 | 64.59%
DOI
10.1145/1007568.1007574

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wu_sigmod04,
        title = {{Online Event-driven Subsequence Matching over Financial Data Streams}},
        author = {Wu, Huanmei and Salzberg, Betty and Zhang, Donghui},
        series = {{SIGMOD} '04},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1007568.1007574},
        url = {https://dl.acm.org/doi/10.1145/1007568.1007574},
        year = {2004}
}

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