Subsequences similarity research for time series based on shape
Zhao Ying · Journal of Shenyang Institute of Engineering · 2009
The representation and similarity measure of time series are the basis of time series research,which is quite important to improve the efficiency and accuracy of the time series data mining.A shape-based discrete symbolic representation is first presented.Its corresponding shape-distance formula to measure the similarity between subsequences of time series is given out.The present method is intuitive and compact,and not sensitive to the shifting,amplitude scaling,compression and stretch of data.The method can reflect the degree of the dynamic change of the tendency and erase the influence of the noises,and it has multi-scale characterization.Experimental results show the effectiveness of the presented algorithm.