A Novel Variable-order Markov Model for Clustering Categorical Sequences
Xiong, Tengke; Wang, Shengrui; Jiang, Qingshan; Huang, Joshua Zhexue
刊名IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
2014
英文摘要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 modelinitialization. To initialize the WCPD model, we propose to use a first-order Markov model built on a weighted fuzzy indicator vector representation ofcategorical sequences, which we call the WFI Markov model. Based on a cascade optimization framework that combines the WCPD and WFI models, we design a new divisive hierarchical clustering algorithm for clustering categorical sequences. Experimental results on data sets from three different domains demonstrate the promising performance of our models and clustering algorithm.
收录类别SCI
原文出处http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6547142
语种英语
内容类型期刊论文
源URL[http://ir.siat.ac.cn:8080/handle/172644/5966]  
专题深圳先进技术研究院_数字所
作者单位IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
推荐引用方式
GB/T 7714
Xiong, Tengke,Wang, Shengrui,Jiang, Qingshan,et al. A Novel Variable-order Markov Model for Clustering Categorical Sequences[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2014.
APA Xiong, Tengke,Wang, Shengrui,Jiang, Qingshan,&Huang, Joshua Zhexue.(2014).A Novel Variable-order Markov Model for Clustering Categorical Sequences.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING.
MLA Xiong, Tengke,et al."A Novel Variable-order Markov Model for Clustering Categorical Sequences".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2014).
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