基于商空间粒度的覆盖聚类算法的研究  

Research of Covering Clustering Algorithm Based on Quotient Granularity

作　　者：闵鹏鹏[1] 郑诚[1] 胡哲[1] 

机构地区：[1]安徽大学计算机学院,安徽合肥230039

出　　处：《计算机与现代化》2008年第11期62-65,共4页Computer and Modernization

摘　　要：聚类技术就是将数据分为自然的群体,并给出每个群的特征描述的一种数据方法。但是传统的聚类算法对高维大规模数据的处理效率不高,张铃教授提出的交叉覆盖算法可以有效地处理大规模的聚类问题,因而本文提出基于覆盖算法的聚类。同时注意到可以用粒度来描述聚类粗细,因此在聚类中引入粒度。In data clustering technology, data has been divided into natural colony, and each colony characteristic describes one data mining method. This is one basic way of data mining and knowledge discovering, but traditional clustering algorithms can not efficiently handle a large number of data. One cross-over algorithm has been developed to effectively cope with the large-scale data clustering problem, thus, the paper introduces clustering based on cross-over algorithm. In the mean time, the paper realizes that the thickness of clustering can be described by granularity, so the granularity concept is introduced into clustering base on the cross-over algorithm.

关 键 词：聚类 覆盖算法 商空间 粒度 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]