摘要
图的聚类是数据聚类的一种很重要的变体,一方面通常可以用图来表示数据集中数据的相似度;另一方面对大型复杂网络的分析也引起人们越来越多地关注;而且对图进行聚类分析可以增强图的可视性,有助于可视化的分析、观测和导航。将最大最小方法的基本思想应用于非加权图的聚类,提出一种无向连通非加权图的快速聚类方法,该方法具有简单、聚类时间短、运行效率高、对于大型静态图的聚类具有良好的适应性等特点。
An interesting and important variant of data clustering is graph-clustering.On the one hand,the similarity between data objects in data set is often expressed by a graph.On the other hand,there is a growing interest in large complex network analysis.Further more,clustering can strengthen graphs＇ visibility and contribute to visual analysis,observation and navigation.This paper explores to apply the max-min approach to clustering undirected and connected graphs without weights,and provides a new algorithm with the characteristics of simplicity,high efficiency and excellent fitness to clustering large static graphs.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第7期179-181,共3页
Computer Engineering and Applications
基金
山西省自然科学基金(the Natural Science Foundation of Shanxi Province of China under Grant No.2007011043)
关键词
聚类
图形聚类
最大最小聚类方法
非加权图
clustering
graph-clustering
max-rain clustering method
unweighted graph
