TimeExplorer: Similarity search time series by their signatures

Abstract

The analysis of different time series is an important activity in many areas of science and engineering. In this paper, we introduce a new method (feature extraction for time series) and an application (TimeExplorer) for similarity-based time series querying. The method is based on eleven characterizations of line graphs presenting time series. These characterizations include measures, such as, means, standard deviations, differences, and periodicities. A similarity metric is then computed on these measures. Finally, we use the similarity metric to search for similar time series in the database. © 2013 Springer-Verlag.