Abstract: 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.

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。