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E. Keogh and S. Kasetty, “On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration,” Data Mining and Knowledge Discovery, Vol. 7, No. 4, 2002, pp. 349-371. doi:10.1023/A:1024988 512476

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.