基于核心链路的重叠社区发现算法

Core Link-based Overlapping Community Detection Algorithm in Social Networks

针对当前的社区发现算法难以发现网络中重叠度较高的社区结构的问题,提出一种基于核心链路的重叠社区发现算法.相较于当前的基于节点的重叠社区发现算法,该算法从链路的角度出发,通过选取核心链路,并根据链路影响力的强弱不断吸引外层链路进而形成链路社区结构;再将链路社区转化为节点社区,经过节点社区调整后,得到全局最优的重叠社区结构.该算法是一种无监督算法,无需输入额外参数.将该算法分别应用于计算机生成网络和真实的社会网络,实验结果表明,相较于其它算法,本文所提算法能够更好地发现重叠度较高的社区结构.

For the existing community detection algorithms are difficult to detect high overlapping community structures in the complex networks,this paper proposes a core link-based overlapping community detection algorithm. Compared with conventional algorithms based on node clustering,the proposed algorithm starts from the perspective of the link. First,a core link is detected. Then we utilize it to attract links in the outer space to join in the community which contains the core link. In the end,we transform link communities to node communities. After adjusting the node communities,we can get the global optimal overlapping community structures. The proposed algorithm is an unsupervised algorithm,without inputting additional parameters. Experiments on both artificial networks and real networks show that the proposed algorithm can achieve better efficiency on detecting high overlapping community structures.