Generalizing DTW to the multi-dimensional case requires an adaptive approach

• Published in: Data mining and knowledge discovery Vol. 31; no. 1; pp. 1 - 31
• Main Authors: Shokoohi-Yekta, Mohammad, Hu, Bing, Jin, Hongxia, Wang, Jun, Keogh, Eamonn
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2017; Springer Nature B.V
• Subjects: Accuracy; Artificial Intelligence; Chemistry and Earth Sciences; Classifications; Clustering; Computer Science; Data mining; Data Mining and Knowledge Discovery; Information Storage and Retrieval; Methods; Multidimensional methods; Physics; Production methods; Statistics for Engineering; Time measurement; Time series; Warpage; Warping; Wearable computers; Wearable devices; Dynamic time warping; Classification; Multi-dimensional time series; Gesture recognition

In recent years Dynamic Time Warping (DTW) has emerged as the distance measure of choice for virtually all time series data mining applications. For example, virtually all applications that process data from wearable devices use DTW as a core sub-routine. This is the result of significant progress i...