【摘要】 提出了一种快速寻找复杂网路中社团结构的新算法.首先通过寻找网络中度最大的节点和其邻居节点,构造出其相应的邻居矩阵和稠密集.然后重复这一过程,最后得到了网络的社团结构.由于算法仅仅涉及局部信息,因此计算量较小.实验结果表明,算法可行且可用于研究文本聚类、图像聚类和视频聚类等数据挖掘领域中的其他问题.更多还原

【Abstract】 In this paper,a new algorithm is proposed to fast detect community structures in complex network.The node with the highest degree and its neighbors in complex network are firstly found,and then its neighbor matrix and density set are constructed.All community structures will be obtained by repeating this process.Using of the local information will lead to the reduction of running time.The experiment results show the validity of the algorithm.Furthermore,the proposal is also applied to solve other problems in data mining,such as text cluster,image cluster,video cluster and etc.更多还原