New similarity measure for mining time series
Shengrui Wang · Computer Engineering and Applications Journal · 2007
Proposes a new similarity measure-global characters for whole clustering of time series,that replaces the raw data with 11 global characteristics,from the aspects of statistical distribution,non-linear and Fourier transformation,thus can get a characteristic vector,which can hold most information of the original time seiries and reduce the calculating complexity.Experimentally compares the four similarity measures on three database under group-ward hierarchical clustering,evaluates the results objectively and subjecttively respectively,and is shown to yield useful and reasonable clustering,especially for economic time series.