sDTW: Computing DTW Distances using Locally Relevant Constraints based on Salient Feature Alignments
Summary: Salient features define locally relevant DTW constraints to bound the warp path. Proposes fixed core/adaptive width, adaptive core/fixed width, and adaptive core/adaptive width strategies, outperforming fixed-core DTW accuracy and time-series retrieval. (summarized by gpt-5-nano on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 362 | Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases | 1995 | VLDB | 0.00025758421 |
| 696 | Exact Indexing of Dynamic Time Warping | 2002 | VLDB | 0.00017991162 |
| 1,164 | Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures | 2008 | VLDB | 0.00013572951 |
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