Anticipatory DTW for Efficient Similarity Search in Time Series Databases
Summary: Anticipatory DTW reuses filter-step info during refinement to prune candidates earlier. It leverages state-of-the-art DTW lower bounds with negligible overhead, no false dismissals, and scales to multivariate, long series and wide bands. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ira Assent (Aalborg University)
- 2. Marc Wichterich (Rheinisch-Westfaelische Technische Hochschule Aachen)
- 3. Ralph Krieger (Rheinisch-Westfaelische Technische Hochschule Aachen)
- 4. Hardy Kremer (Rheinisch-Westfaelische Technische Hochschule Aachen)
- 5. Thomas Seidl (Rheinisch-Westfaelische Technische Hochschule Aachen)
BibTeX Citation
@article{assent_vldb09,
title = {{Anticipatory DTW for Efficient Similarity Search in Time Series Databases}},
author = {Assent, Ira and Wichterich, Marc and Krieger, Ralph and Kremer, Hardy and Seidl, Thomas},
journal = {PVLDB},
series = {{VLDB} '09},
doi = {10.14778/1687627.1687721},
url = {https://doi.org/10.14778/1687627.1687721},
year = {2009}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,858 | A Generic Framework for Efficient and Effective Subsequence Retrieval | 2012 | VLDB | 5.7523396e-05 |
| 8,026 | A New Approach for Processing Ranked Subsequence Matching Based on Ranked Union | 2011 | SIGMOD | 5.5049255e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 190 | Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases | 2001 | SIGMOD | 0.00026105472 |
| 303 | On The Marriage of Lp-norms and Edit Distance | 2004 | VLDB | 0.00021956234 |
| 601 | Exact Indexing of Dynamic Time Warping | 2002 | VLDB | 0.00015870156 |
| 796 | Optimal Multi-Step k-Nearest Neighbor Search | 1998 | SIGMOD | 0.00013932561 |
| 898 | Querying and Mining of Time Series Data: Experimental Comparison of Representations and Distance Measures | 2008 | VLDB | 0.00013339042 |
| 1,046 | Warping Indexes with Envelope Transforms for Query by Humming | 2003 | SIGMOD | 0.00012440091 |
| 3,267 | FTW: Fast Similarity Search under the Time Warping Distance | 2005 | PODS | 7.5816553e-05 |
| 3,440 | Approximate Embedding-Based Subsequence Matching of Time Series | 2008 | SIGMOD | 7.4142918e-05 |
| 7,230 | LB_Keogh Supports Exact Indexing of Shapes under Rotation Invariance with Arbitrary Representations and Distance Measures | 2006 | VLDB | 5.6665222e-05 |
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|---|---|---|---|---|
| 1 | 6,517 | Interactive Time Series Exploration Powered by the Marriage of Similarity Distances | 2017 | VLDB |
| 2 | 371 | Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases | 1995 | VLDB |
| 3 | 810 | Similarity-Based Queries for Time Series Data | 1997 | SIGMOD |
| 4 | 12,329 | sDTW: Computing DTW Distances using Locally Relevant Constraints based on Salient Feature Alignments | 2012 | VLDB |
| 5 | 6,756 | On Efficiently Searching Trajectories and Archival Data for Historical Similarities | 2008 | VLDB |
| 6 | 10,938 | FSMDTW: A Fast Index-free Subsequence Matching Algorithm for Dynamic Time Warping | 2025 | VLDB |
| 7 | 3,440 | Approximate Embedding-Based Subsequence Matching of Time Series | 2008 | SIGMOD |
| 8 | 601 | Exact Indexing of Dynamic Time Warping | 2002 | VLDB |
| 9 | 5,592 | Ranked Subsequence Matching in Time-Series Databases | 2007 | VLDB |
| 10 | 3,267 | FTW: Fast Similarity Search under the Time Warping Distance | 2005 | PODS |