Time Series Classification Method Based on Longest Common Subsequence and Textual Approximation

Abstract

Many symbolic representations of time series have been proposed by researchers over past decades. However, it is still not enough to classify time series with high accuracy in such applications as ubiquitous systems or sensor systems. In this paper, we propose a new symbolic representation of time series called l-TAX to increase the accuracy of time series… (More)
DOI: 10.1109/ICDIM.2012.6360087

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