Complex networks are widely used to represent an abundance of real-world relations
ranging from social networks to brain networks. Inferring missing links or predicting future …

The problem of predicting the missing links between nodes or the links that may form in the
future in a network is an important task of network analysis. However, the problem is not …

Predicting links in information networks requires deep understanding and careful modeling
of network structure. Network embedding, which aims to learn low-dimensional …

Link prediction is a crucial task in graph analysis that aims to predict the existence of missing
links in a graph. Graph embedding methods have gained popularity for link prediction by …

Link prediction is an important task attracting much attention in the field of complex network,
and it can be applied to many real-world scenarios such as recommendation engines …

Link prediction is an important task in social network analysis and mining because of its
various applications. A large number of link prediction methods have been proposed …

Link prediction plays an important role in network analysis and applications. Recently,
approaches for link prediction have evolved from traditional similarity-based algorithms into …

To enjoy more social network services, users nowadays are usually involved in multiple
online sites at the same time. Aligned social networks provide more information to alleviate …

Dynamic link prediction aims to predict future connections among unconnected nodes in a
network. It can be applied for friend recommendations, link completion, and other tasks …

A network is a form of data representation and is widely used in many fields. For example, in
social networks, we regard nodes as individuals or groups, and the edges between nodes …