Exact indexing of dynamic time warping
 Eamonn Keogh,
 Chotirat Ann Ratanamahatana
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The problem of indexing time series has attracted much interest. Most algorithms used to index time series utilize the Euclidean distance or some variation thereof. However, it has been forcefully shown that the Euclidean distance is a very brittle distance measure. Dynamic time warping (DTW) is a much more robust distance measure for time series, allowing similar shapes to match even if they are out of phase in the time axis. Because of this flexibility, DTW is widely used in science, medicine, industry and finance. Unfortunately, however, DTW does not obey the triangular inequality and thus has resisted attempts at exact indexing. Instead, many researchers have introduced approximate indexing techniques or abandoned the idea of indexing and concentrated on speeding up sequential searches. In this work, we introduce a novel technique for the exact indexing of DTW. We prove that our method guarantees no false dismissals and we demonstrate its vast superiority over all competing approaches in the largest and most comprehensive set of time series indexing experiments ever undertaken.
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 Title
 Exact indexing of dynamic time warping
 Journal

Knowledge and Information Systems
Volume 7, Issue 3 , pp 358386
 Cover Date
 20050301
 DOI
 10.1007/s1011500401549
 Print ISSN
 02191377
 Online ISSN
 02193116
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 Dynamic time warping
 Indexing
 Lower bounding
 Time series
 Industry Sectors
 Authors

 Eamonn Keogh ^{(1)}
 Chotirat Ann Ratanamahatana ^{(1)}
 Author Affiliations

 1. Computer Science and Engineering Department, University of California–Riverside, Riverside, CA, 92521, USA