Efficient Subsequence Matching in Time Series Databases Under Time and Amplitude Transformations

Authors:
Tassos Argyros;Charis Ermopoulos
Affiliations:
-;-
Venue:
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Year:
2003

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Abstract

Subsequence matching in large time series databases hasattracted a lot of interest and many methods have been proposedthat cope with this problem in an adequate extend.However, locating subsequence matches of arbitrary length,under time and amplitude transformations, has received farless attention and is still an open problem. In this paperwe present an efficient algorithm for variable-length subsequencematching under transformations that guaranteesno false dismissals. Further, this algorithm uses a novelsimilarity criterion for determining similarity under amplitudetransformations in a most efficient way. Finally, ouralgorithm has been tested in various experiments on realdata, resulting in a running time improvement of one orderof magnitude compared to the naive approach.