The number of network science applications across many different fields has been rapidly
increasing. Surprisingly, the development of theory and domain-specific applications often …

Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …

Most real systems consist of a large number of interacting, multi-typed components, while
most contemporary researches model them as homogeneous information networks, without …

The increasing growth of online social networks has drawn researchers' attention to link
prediction and has been adopted in many fields, including computer sciences, information …

Most objects and data in the real world are of multiple types, interconnected, forming
complex, heterogeneous but often semi-structured information networks. However, most …

Real world physical and abstract data objects are interconnected, forming gigantic,
interconnected networks. By structuring these data objects and interactions between these …

Given a snapshot of a social network, can we infer which new interactions among its
members are likely to occur in the near future? We formalize this question as the link …

Networks and network analysis are arguably one of the largest growth areas of the early
twenty-first century in the quantitative sciences. Despite roots in social network analysis …

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 …

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 …