Networks have become increasingly important to model complex systems composed of
interacting elements. Network data mining has a large number of applications in many …

In social network analysis, link prediction is a fundamental tool to determine new
relationships among users which are most likely to occur in the future. Link prediction by …

Social network analysis has recently attracted lots of attention among researchers due to its
wide applicability in capturing social interactions. Link prediction, related to the likelihood of …

Link prediction aims to predict the missing interactions in evolving networks that may appear
in the future. It has practical importance in various real-world applications, ranging from …

Owning to its extensive range of applications, the study of link prediction has captured
considerable attention from researchers. Recently, hybrid similarity methods, which …

In this article, we aim at developing neighborhood-based neural models for link prediction.
We design a novel multispace neighbor attention mechanism to extract universal …

The traditional complex network theory is particularly focused on network models in which
all network constituents are dealt with equivalently, while fail to consider the supplementary …

The development of methods for anomaly detection in dynamic ubiquitous online social
networks is critical to coincide with the growth in social network usage. This paper presents …

In social networks, link establishment among the users is affected by complex factors. In this
paper, we try to investigate the internal and external factors that affect the formation of links …

Because of its very importance in a plethora of applications, the research of link prediction
has received growing attention from different disciplines. However, link prediction in …