The reconstruction of complex networks with community structure

Link prediction is a fundamental problem with applications in many fields ranging from biology to computer science. In the literature, most effort has been devoted to estimate the likelihood of the existence of a link between two nodes, based on observed links and nodes’ attributes in a network. In this paper, we apply several representative link prediction methods to reconstruct the network, namely to add the missing links with high likelihood of existence back to the network. We find that all these existing methods fail to identify the links connecting different communities, resulting in a poor reproduction of the topological and dynamical properties of the true network. To solve this problem, we propose a community-based link prediction method. We find that our method has high prediction accuracy and is very effective in reconstructing the inter-community links.