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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Motif-Based Method for Initialization the K-Means Clustering for Time Series Data
verfasst von : Le Phu, Duong Tuan Anh
Erschienen in: AI 2011: Advances in Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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Time series clustering by
k
-Means algorithm still has to overcome the dilemma of choosing the initial cluster centers. In this paper, we present a new method for initializing the
k
-Means clustering algorithm of time series data. Our initialization method hinges on the use of time series motif information detected by a previous task in choosing
k
time series in the database to be the seeds. Experimental results show that our proposed clustering approach performs better than ordinary
k
-Means in terms of clustering quality, robustness and running time.