A Novel Variable-order Markov Model for Clustering Categorical Sequences

  title={A Novel Variable-order Markov Model for Clustering Categorical Sequences},
  author={Tengke Xiong and Shengrui Wang and Qingshan Jiang and Joshua Zhexue Huang},
  journal={IEEE Transactions on Knowledge and Data Engineering},
Clustering categorical sequences is an important and difficult data mining task. Despite recent efforts, the challenge remains, due to the lack of an inherently meaningful measure of pairwise similarity. In this paper, we propose a novel variable-order Markov framework, named weighted conditional probability distribution (WCPD), to model clusters of categorical sequences. We propose an efficient and effective approach to solve the challenging problem of model initialization. To initialize the… CONTINUE READING


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