Ranked Subsequence Matching in Time-Series Databases
Summary: Introduces ranked subsequence matching under time warping (DTW) for top-k similarity from data sequences, a first-of-its-kind solution. MDMWP-distance enables pre-access pruning; deferred group retrieval and window-group distance cut I/O and accesses. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wook-Shin Han
- 2. Jinsoo Lee
- 3. Yang-Sae Moon
- 4. Haifeng Jiang
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,294 | Approximate Embedding-Based Subsequence Matching of Time Series | 2008 | SIGMOD | 7.2619257e-05 |
| 5,936 | Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning | 2020 | VLDB | 5.2654071e-05 |
| 6,983 | A Generic Framework for Efficient and Effective Subsequence Retrieval | 2012 | VLDB | 4.8732757e-05 |
| 8,035 | A New Approach for Processing Ranked Subsequence Matching Based on Ranked Union | 2011 | SIGMOD | 4.6009403e-05 |
| 8,778 | The Inherent Time Complexity and An Efficient Algorithm for Subsequence Matching Problem | 2022 | VLDB | 4.4543399e-05 |
| 11,921 | SMiLer: A Semi-Lazy Time Series Prediction System for Sensors | 2015 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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