Subsequence Matching on Structured Time Series Data
Summary: Leverages time-series structure with a piecewise-linear representation from a state machine for subsequence matching. Introduces subsequence stability and weighted L1 similarity prioritizing frequency and timing, enabling radiotherapy motion analysis. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Huanmei Wu
- 2. Betty Salzberg
- 3. Gregory C Sharp
- 4. Steve B Jiang
- 5. Hiroki Shirato
- 6. David Kaeli
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,294 | Approximate Embedding-Based Subsequence Matching of Time Series | 2008 | SIGMOD | 7.2619257e-05 |
| 6,535 | Effective Variation Management for Pseudo Periodical Streams | 2007 | SIGMOD | 5.0243433e-05 |
| 8,228 | Mining Approximate Top-K Subspace Anomalies in Multi-Dimensional Time-Series Data | 2007 | VLDB | 4.5549459e-05 |
| 8,306 | Online Windowed Subsequence Matching over Probabilistic Sequences | 2012 | SIGMOD | 4.5435639e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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