The problem of missing link prediction in complex networks has attracted much attention
recently. Two difficulties in link prediction are the sparsity and huge size of the target …

Link prediction is an elemental challenge in network science, which has already found
applications in guiding laboratorial experiments, digging out drug targets, recommending …

Link prediction is one of the most important and challenging tasks in complex network
analysis, which aims to predict missing link based on existing ones in a network. This …

Link prediction in complex networks has attracted increasing attention from both physical
and computer science communities. The algorithms can be used to extract missing …

Link prediction is an open problem in the complex network, which attracts much research
interest currently. However, little attention has been paid to the relation between network …

The common-neighbor–based method is simple yet effective to predict missing links, which
assume that two nodes are more likely to be connected if they have more common …

Topological properties of networks are widely applied to study the link-prediction problem
recently. Common Neighbors, for example, is a natural yet efficient framework. Many …

Inspired by the practical importance of social networks, economic networks, biological
networks and so on, studies on large and complex networks have attracted a surge of …

Real world complex networks are indirect representation of complex systems. They grow
over time. These networks are fragmented and raucous in practice. An important concern …

Missing link prediction in networks is of both theoretical interest and practical significance in
modern science. In this paper, we empirically investigate a simple framework of link …