Symbolic representation algorithm for time series based on sliding window and local features
基于滑动窗口及局部特征的时间序列符号化方法

This paper put forward a symbolic method for time series which based on the sliding window and the local features. Firstly, this method divided time series according to the sliding window method, and used multiple slopes to show the each subsection of time series. Then it used K-means clustering algorithm to clustering the slope representation of subsection, and realized the symbolization of time series. Experiments show that the method is effective and accurate.