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Clustering-Inverse: A Generalized Model for Pattern-Based Time Series Segmentation
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作者 zhaohong deng Fu-Lai Chung Shitong Wang 《Journal of Intelligent Learning Systems and Applications》 2011年第1期26-36,共11页
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. Fi... 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. 展开更多
关键词 Pattern-Based TIME Series Segmentation Clustering-Inverse Dynamic TIME WARPING Perceptually Important POINTS Evolution Computation Particle SWARM Optimization Genetic Algorithm
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