SWIFT: Mining Representative Patterns from Large Event Streams
Summary: SWIFT MDL-based Representative Patterns (MRP) for IoT streams, yielding a compact set and mitigating explosion. One-pass SWIFT with lazy-B-SWIFT updates preserves encoding compactness, achieving up to 50% gains and four orders of magnitude speedups. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yizhou Yan
- 2. Lei Cao
- 3. Samuel Madden
- 4. Elke A. Rundensteiner
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 259 | High-Performance Complex Event Processing over Streams | 2006 | SIGMOD | 0.00030174924 |
| 1,418 | ZStream: A Cost-based Query Processor for Adaptively Detecting Composite Events | 2009 | SIGMOD | 0.00012089363 |
| 5,182 | Active Complex Event Processing over Event Streams | 2011 | VLDB | 5.6410216e-05 |
| 9,617 | Complex Event Analytics: Online Aggregation of Stream Sequence Patterns | 2014 | SIGMOD | 4.3176634e-05 |
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