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DLACEP: A Deep-Learning Based Framework for Approximate Complex Event Processing

Summary: DLACEP fuses deep learning with CEP to prune candidate event sets and approximate pattern matches in streams. Empirical results show throughput gains up to 1,000× with minor loss in matches, enabling a scalable DL-CEP framework for pattern detection. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6449
Venue
SIGMOD
Year
2022
Pagerank
4.4430954e-05
Overall Rank
8,816 | 38.67%
DOI
10.1145/3514221.3526136

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,505 SuSe: Summary Selection for Regular Expression Subsequence Aggregation over Streams 2025 SIGMOD 4.1945683e-05
10,523 Scalable Complex Event Processing on Video Streams 2025 SIGMOD 4.1945683e-05
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Showing 13 of 13 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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