ABSTRACT
An important task in temporal data mining, in fields ranging from medicine to finance, is the computation of similarity between time series data or a series of events. Similarity computation is an important part of time series indexing, classification, and clustering. For example, in medicine, comparison of patient physiological signals with “normal” signals can be useful in disease detection. In another example, identification of patients with similar series of events can be useful in choosing treatment. In finance, similarity of stock value fluctuations with older stock data can be useful in prediction. The results of the similarity computation depend on the temporal data representation scheme.
