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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