Nowadays, online social networks are considered as one of the most important emerging phenomena of human societies. In these networks, prediction of link by relying on the knowledge existing of the interaction between network actors provides an estimation of the probability of creation of a new relationship in future. A wide range of applications can be found for link prediction such as electro...

Background: The link prediction issue is one of the most widely used problems in complex network analysis. Link prediction requires knowing the background of previous link connections and combining them with available information. The link prediction local approaches with node structure objectives are fast in case of speed but are not accurate enough. On the other hand, the global link predicti...

Link prediction is an important task for analying social networks which also has applications in other domains like, information retrieval, bioinformatics and e-commerce. There exist a variety of techniques for link prediction, ranging from feature-based classification and kernelbased method to matrix factorization and probabilistic graphical models. These methods differ from each other with re...

Link prediction on dynamic networks has been extensively studied and widely applied in various applications. However, existing methods only consider either the network structure or temporal information, ignoring potentialities of using both types information together to comprehend complex behaviors networks. Moreover, unlink prediction, which also plays an important role evolution social networ...