In recent years, bipartite-networks-based recommendations have attracted the attention of many researchers. Many of them are committed to improving the recommendation algorithms such as network-based inference (NBI) or probability spreading (ProbS). However, usually one or two parameters are...

Recently, in complex network, link prediction has brought a surge of researches, among which similarity based link prediction outstandingly gains considerable success, especially similarity in terms of paths. In investigation of paths based similarity, we find that the effective influence of...

Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction...

Link directions are essential to the functionality of networks and their prediction is helpful toward a better knowledge of directed networks from incomplete real-world data. We study the problem of predicting the directions of some links by using the existence and directions of the rest of...

Lehman Brothers' failure in 2008 demonstrated the importance of understanding interconnectedness in interbank networks. The interbank market plays a significant role in facilitating market liquidity and providing short-term funding for each other to smooth liquidity shortages. Knowing the...