基于拓扑聚类的密度聚类算法研究

聚类分析是重要的数据挖掘方法,在商务智能、地理信息系统、医学等方面有广泛的应用.随着聚类分析的蓬勃发展,涌现出了许多聚类算法,其中最重要的算法之一是基于密度的空间聚类以及其多种变种——基于密度连通链、基于加权密度、基于引力连通集合的算法.这些算法在概念上相似但没有统一的描述.本文针对基于密度的空间聚类及其变种提出了拓扑的概念.给出了聚类拓扑结构的定义,把簇定义为拓扑连通集合.此外,本文运用全新的拓扑思想改进典型的算法,提出了一种拓扑聚类的新算法.实例证明此算法有效.

RESEARCH ON DENSITY- BASED SPATIAL CLUSTERING BY TOPOLOGY CLUSTER

Clustering analysis has become an important tool in knowledge engineering and business intelligence.There are rapidly growing number of clustering algorithms,however,one of the most important clustering algorithms is the density based spatial clustering,and its various variations.These algorithms are either based on the density connected chains,or weighted density,or the gravity based connected sets.They seem similar in idea but there does not exist a unified presentation.The purpose of this paper is to give a topological view to the spatial clustering focusing on density based clustering with its variations.We propose the definition of cluster topology,define clusters as various kinds of topological connected sets.Moreover,the topological cluster forming algorithms are presented.Then we reform some typical algorithms with the new topological view.Examples are given to show the theories.