聚类分析算法CLIQUE的研究及改进  

Research and Impovement of Cluster Analysis CLIQUE Algorithm

作　　者：陈朝华[1] 王伟平[1] 

机构地区：[1]中南大学信息科学与工程学院

出　　处：《科技广场》2007年第5期9-11,共3页Science Mosaic

摘　　要：CLIQUE是一种基于密度和基于网格的混合聚类方法。在高维空间中,它能够有效地进行聚类,并且能够发现嵌套在高维数据空间子空间中的聚类。但是,CLIQUE算法存在着很多的局限性,主要有以下两点:首先是子空间的剪枝;其次是CLIQUE算法追求方法简单化。针对CLIQUE算法的局限性,采用基于约束条件的聚类技术、自适应网格技术和边界调整技术来对CLIQUE算法进行改进,提出了基于约束条件和自适应网格的CAG-CLIQUE算法。CLIQUE is an omnibus cluster method that is density-based and grid-based. It can effectively cluster on data set with high dimensions and discover clusters in the subspace of high dimensional data. But, there are many limitations in CLIQUE algorithm. The main two limitations are as follows. First , Subspace pruning. Second , CLIQUE algorithm oversimplifies at some aspects and many steps are approximate algorithm. In view of CLIQUE algorithm limitations, CAG-CLIQUE algorithm is proposed that is constraint-based and self-adaptive grid. CLIQUE is modified by constraint-based cluster technique, self-adaptive grid division technique and boundary adjustment technique.

关 键 词：数据挖掘 聚类分析 CLIQUE算法 CAG-CLIQUE算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]