The Community Structure Detection Algorithm Based On Belonging Degree

Community structure of a complex network is one of the most important features. Community is a set of nodes connected more closely in network which means that nodes within a group are much more connected to each other than to the rest of the network. Community discovery is to find communities from the logical link between the network nodes. The community discovery can help us to analyze the function module in a complex network and understand the topological properties of complex networks. The community discovery has the vital significance in computer science and social science. This paper starts the research on the related issues of community detection, and the details are as follows:(1) We give the concept of the node belonging degree. The node belonging degree is the ratio of the number of a node’s neighboring nodes in the community and the number of a node’s neighboring nodes. The belonging degree shows the connection degree of a node connects with nodes in the community. All of the algorithms in this paper is based on the node belonging degree.(2) An algorithm based on the node belonging degree is proposed. This algorithm needs the local information of the network. We work out the belonging degree of a node and known community, and compare it with the threshold of belonging degree which has been set. If the belonging degree greater than the threshold, we divide this node to the community. This algorithm has more advantages in finding the community of a known node.(3) We give the concept of the edge belonging degree. The community is a set of edges connected closely in a network rather than a set of nodes that be usually thought. The edge belonging degree is the ratio of the number of a edge’s neighboring edges in the community and the number of a edge’s neighboring edges.(4) An algorithm based on the edge belonging degree is proposed. Just like the algorithm based on the node belonging degree, this algorithm needs the local information of the network. We work out the belonging degree of an edge and known community, and compare it with the threshold of belonging degree which has been set. If the belonging degree greater than the threshold, we connect this edge to the community.