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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)

Paper ID
9945
Venue
VLDB
Year
2009
Pagerank
4.5770301e-05
Overall Rank
8,139 | 43.38%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
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
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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