Mining coherence in time series data
George Potamias, Vassilis S. Moustakis, Vassilika Vouton · 2000
This paper presents work on modeling coherence between time series data. Work is based on the elaboration of formula that computes the distance between time series. Based on the computed distances, the method exploits the closest neighbor algorithm and leads to the construction of a phylogeny-clustering tree. Using car sales data (available on the www) we demonstrate work done and present preliminary results. We discuss implications of the work performed in correlating time series data with documents including such data.