A new markov model for clustering categorical sequences
文献类型：会议论文
| 作者 | Xiong tengke; Wang shengrui; Jiang qingshan; Huang Joshazhexue |
| 出版日期 | 2011 |
| 会议名称 | 11th IEEE International Conference on Data Mining |
| 会议地点 | Sydney |
| 英文摘要 | Clustering categorical sequences remains an open and challenging task due to the lack of an inherently meaningful measure of pairwise similarity betweensequences. Model initialization is an unsolved problem in model-based clustering algorithms for categorical sequences. In this paper, we propose a simple and effective Markov model to approximate the conditional probability distribution (CPD) model, and use it to design a novel two-tier Markov model to represent asequence cluster. Furthermore, we design a novel divisive hierarchical algorithm for clustering categorical sequences based on the two-tier Markov model. The experimental results on the data sets from three different domains demonstrate the promising performance of our models and clustering algorithm. © 2011 IEEE.(22 refs) |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/3582]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2011 |
| 推荐引用方式 GB/T 7714 | Xiong tengke,Wang shengrui,Jiang qingshan,et al. A new markov model for clustering categorical sequences[C]. 见:11th IEEE International Conference on Data Mining. Sydney. |
入库方式： OAI收割
来源：深圳先进技术研究院
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