A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets

Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thanawin Rakthanmanon, Eamonn J. Keogh. A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets. In Proceedings of the Twelfth SIAM International Conference on Data Mining, Anaheim, California, USA, April 26-28, 2012. pages 999-1010, SIAM / Omnipress, 2012. [doi]

Abstract

Abstract is missing.