Author(s)

D. WangDa & RongGang

Abstract

The pattern model representation (PMR) of time series is proposed in this paper. PMR is based on a piecewise linear representation (PLR) and is effective at describing the tendency of time series. Then, the pattern distance can be calculated to measure the similarity of tendency. This method overcomes the problem of time series mismatch based on point distance. According to the numbers of series' segmentations, pattern distance has a multi-scale feature and can reflect different similarities with various bandwidths. Because normalization is unnecessary, the calculation consumption of pattern distance is low. 1 Introduction Knowledge discovery of time series plays an important role in data mining. In particular, dynamic information can be found by analysing the tendency change of time series. Commonly, matching time series is

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