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A Comparison of Progressive and Iterative Centroid Estimation Approaches Under Time Warp

Authors
  • Soheily-Khah, Saeid
  • Douzal-Chouakria, Ahlame
  • Gaussier, Eric
Publication Date
Jan 01, 2016
Source
HAL-UPMC
Keywords
Language
English
License
Unknown
External links

Abstract

Estimating the centroid of a set of time series under time warp is a major topic for many temporal data mining applications, as summarization a set of time series, prototype extraction or clustering. The task is challenging as the estimation of centroid of time series faces the problem of multiple temporal alignments. This work compares the major progressive and iterative centroid estimation methods, under the dynamic time warping, which currently is the most relevant similarity measure in this context.

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