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Clustering-Inverse: A Generalized Model for Pattern-Based Time Series Segmentation

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DOI: 10.4236/jilsa.2011.31004    4,797 Downloads   9,907 Views   Citations

ABSTRACT

Patterned-based time series segmentation (PTSS) is an important task for many time series data mining applications. In this paper, according to the characteristics of PTSS, a generalized model is proposed for PTSS. First, a new inter-pretation for PTSS is given by comparing this problem with the prototype-based clustering (PC). Then, a novel model, called clustering-inverse model (CI-model), is presented. Finally, two algorithms are presented to implement this model. Our experimental results on artificial and real-world time series demonstrate that the proposed algorithms are quite effective.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Z. Deng, F. Chung and S. Wang, "Clustering-Inverse: A Generalized Model for Pattern-Based Time Series Segmentation," Journal of Intelligent Learning Systems and Applications, Vol. 3 No. 1, 2011, pp. 26-36. doi: 10.4236/jilsa.2011.31004.

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