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L. Feng, K. Ju and K. H. Chon, “A Method for Segmentation of Switching Dynamic Modes in Time Series,” IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, Vol. 35, No. 5, 2005, pp. 1058-1064. doi:10.1109/TSMCB.2005.850174

has been cited by the following article:

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

  AUTHORS: Zhaohong Deng, Fu-Lai Chung, Shitong Wang

  KEYWORDS: Pattern-Based Time Series Segmentation, Clustering-Inverse, Dynamic Time Warping, Perceptually Important Points, Evolution Computation, Particle Swarm Optimization, Genetic Algorithm

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.3 No.1, February 24, 2011

  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.