Model-based multidimensional clustering of categorical data

	Model-based multidimensional clustering of categorical data
	Tao Chen; Nevin L. Zhang; Tengfei Liu; Kin Man Poon; Yi Wang
刊名	ARTIFICIAL INTELLIGENCE
	2012
英文摘要	Existing models for cluster analysis typically consist of a number of attributes that describe the objects to be partitioned and one single latent variable that represents the clusters to be identified. When one analyzes data using such a model, one is looking for one way to cluster data that is jointly defined by all the attributes. In other words, one performs unidimensional clustering. This is not always appropriate. For complex data with many attributes, it is more reasonable to consider multidimensional clustering, i.e., to partition data along multiple dimensions. In this paper, we present a method for performing multidimensional clustering on categorical data and show its superiority over unidimensional clustering.
收录类别	SCI
原文出处	http://ac.els-cdn.com/S000437021100110X/1-s2.0-S000437021100110X-main.pdf?_tid=e88e9c2c-1a14-11e5-afc5-00000aab0f6b&acdnat=1435111460_d64ed7ec1277bf20568371d7ae81dbad
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/3941]
专题	深圳先进技术研究院_医工所
作者单位	ARTIFICIAL INTELLIGENCE
推荐引用方式 GB/T 7714	Tao Chen,Nevin L. Zhang,Tengfei Liu,et al. Model-based multidimensional clustering of categorical data[J]. ARTIFICIAL INTELLIGENCE,2012.
APA	Tao Chen,Nevin L. Zhang,Tengfei Liu,Kin Man Poon,&Yi Wang.(2012).Model-based multidimensional clustering of categorical data.ARTIFICIAL INTELLIGENCE.
MLA	Tao Chen,et al."Model-based multidimensional clustering of categorical data".ARTIFICIAL INTELLIGENCE (2012).