Similarity measure based on piecewise linear approximation and derivative dynamic time warping for time series mining

Authors:
Hailin Li;Chonghui Guo;Wangren Qiu
Affiliations:
Institute of Systems Engineering, Dalian University of Technology, Dalian 116024, China;Institute of Systems Engineering, Dalian University of Technology, Dalian 116024, China;Research Center of Information and Control, Dalian University of Technology, Dalian 116024, China
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

We propose a new method to calculate the similarity of time series based on piecewise linear approximation (PLA) and derivative dynamic time warping (DDTW). The proposed method includes two phases. One is the divisive approach of piecewise linear approximation based on the middle curve of original time series. Apart from the attractive results, it can create line segments to approximate time series faster than conventional linear approximation. Meanwhile, high dimensional space can be reduced into a lower one and the line segments approximating the time series are used to calculate the similarity. In the other phase, we utilize the main idea of DDTW to provide another similarity measure based on the line segments just we got from the first phase. We empirically compare our new approach to other techniques and demonstrate its superiority.