Complete Event Trend Detection in High-Rate Event Streams
Summary: Introduces the CET graph to compactly encode all Complete Event Trends matched by a query in high-rate streams. Time-centric graphlets with cached partial CETs enable reuse; a cost-monotone optimizer prunes plans under memory limits, yielding up to 42× speedup vs prior methods. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Olga Poppe (Worcester Polytechnic Institute)
- 2. Chuan Lei (NEC Corporation)
- 3. Salah Ahmed (Worcester Polytechnic Institute)
- 4. Elke A. Rundensteiner (Worcester Polytechnic Institute)
BibTeX Citation
@inproceedings{poppe_sigmod17,
title = {{Complete Event Trend Detection in High-Rate Event Streams}},
author = {Poppe, Olga and Lei, Chuan and Ahmed, Salah and Rundensteiner, Elke A.},
series = {{SIGMOD} '17},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3035918.3035947},
url = {https://dl.acm.org/doi/10.1145/3035918.3035947},
year = {2017}
}
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