Partition of Time Series Using Hierarchical Clustering |Applications to Linguistic Expressions of Time Series and Retrieval of Similar Time Series

Abstract

We have proposed a method to partition a time-series data into several periods based on changes of trends and features, where we unify the adjacent two clusters that have the maximum total similarity. We have also proposed a method to represent a time-series data in linguistic expressions and appled to retrieval of similar time-series data using a similarity of linguistic expressions. We have linguitic expressions from some values in three fuzzy periods, called the first, second and third terms, which are fixed in the previous papers but changed based on trends and features of the data in this paper. We partion the time-series data into two periods, whose boundary is considered as the changing time from the firt to the third terms, that is, the center of the second term. We restrict it in the range of not too early and not too late times. We apply this mathod to lingusitic expressions and retrival of times-series data and we have better result than the previous ones.