摘要： 针对复杂网络社区检测过程复杂、时间复杂度高的问题,根据节点间三角环数量关系,设计一种基于三角环吸引子的社区检测算法。从任意一个节点开始,将一个节点的三角环吸引子中的最大节点划分到同一个社区中,直到所有节点均被访问,将整个网络划分为多个社区。通过确定一个社区数量的门限阈值,将划分社区进行优化直至社区个数为确定的门限阈值个数。实验结果表明,该算法的时间复杂度低,能较好地划分出真实网络和benchmark网络的社区结构。

关键词: 复杂网络, 社区检测, 社区优化, 三角环, 门限阈值

Abstract: Aiming at the problem that complex network community detection process is complex and time complexity is high,according to the numerical relationship of triangle clique between nodes,a community detection algorithm is designed based on triangle clique attractors.This algorithm can start on an arbitrary node.The maximum node of a triangle clique attractor of a node is divided into the same community,till all nodes in the network are visited,and the network is divided into several communities.By determining the threshold of a number of communities,all these communities will be optimized until the number of the communities reaches the threshold.Experimental results show that the time complexity of the proposed algorithm is low,and the community structure of the real network and benchmark network can be classified well.

Key words: complex network, community detection, community optimization, triangle clique, threshold

中图分类号: 

• TP18