SWIFT: Mining Representative Patterns from Large Event Streams
Summary: SWIFT mines compact, MDL-based representative patterns (MRPs) from evolving event-stream windows, avoiding pattern explosion. Its one-pass and lazy batch variants optimally select updates for encoding compactness, achieving up to 4-order-of-magnitude speedups and 50% better compactness. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Yizhou Yan (Worcester Polytechnic Institute)
- 2. Lei Cao (Massachusetts Institute of Technology)
- 3. Samuel Madden (Massachusetts Institute of Technology)
- 4. Elke A. Rundensteiner (Worcester Polytechnic Institute)
BibTeX Citation
@article{yan_vldb19,
title = {{SWIFT: Mining Representative Patterns from Large Event Streams}},
author = {Yan, Yizhou and Cao, Lei and Madden, Samuel and Rundensteiner, Elke A.},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {3},
pages = {265--277},
doi = {10.14778/3291264.3291271},
url = {https://doi.org/10.14778/3291264.3291271},
year = {2019}
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 241 | High-Performance Complex Event Processing over Streams | 2006 | SIGMOD | 0.00023419748 |
| 1,029 | ZStream: A Cost-based Query Processor for Adaptively Detecting Composite Events | 2009 | SIGMOD | 0.00012416974 |
| 5,059 | Active Complex Event Processing over Event Streams | 2011 | VLDB | 6.2917112e-05 |
| 9,942 | Complex Event Analytics: Online Aggregation of Stream Sequence Patterns | 2014 | SIGMOD | 5.1061569e-05 |
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