Discovering original motifs with different lengths from time series
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摘要
Finding previously unknown patterns in a time series has received much attention in recent years. Of the associated algorithms, the k-motif algorithm is one of the most effective and efficient. It is also widely used as a time series preprocessing routine for many other data mining tasks. However, the k-motif algorithm depends on the predefine of the parameter w, which is the length of the pattern. This paper introduces a novel k-motif-based algorithm that can solve the existing problem and, moreover, provide a way to generate the original patterns by summarizing the discovered motifs.
论文关键词:Time series,Data mining,Pattern discovery,Motif
论文评审过程:Received 29 June 2007, Accepted 24 March 2008, Available online 31 March 2008.
论文官网地址:https://doi.org/10.1016/j.knosys.2008.03.022