Many real-world networks are dynamic, whose structure keeps changing over time. Link
prediction, which can foretell the emergence of future links, is one crucial task in dynamic …

Any complex real-world system that changes over time can be represented as a network. We
analyze these networks using network theory-based techniques to infer useful information …

In recent years, social network analysis has received a lot of interest. Link prediction is an
important area of research in this field that uses information from current networks to predict …

Recently, the analysis of heterogeneous networks has become more popular due to the
growing number of social networks. These networks are capable of covering a variety of …

Finding future or missing associations is an essential problem in complex systems because
of its numerous application areas. These applications use link prediction methods to provide …

This paper presents a link prediction algorithm for dynamic social networks based on B+
trees. The authors pointed out the need for precise link prediction in social network analysis …

Abstract Location Based Social Networks (LBSNs) have been widely used as a primary data
source to study friendship inference. Traditional approaches mainly focused on exploring …

Link prediction is an attractive and sought-after topic for research in network analysis. Link
prediction has a great importance in various social networks like Facebook, Twitter …

In a dynamic heterogeneous network, the number of nodes in the network will continue to
increase over time, which brings great challenges to the link prediction task. To address this …

In recent times, with the immense availability and usability of Internet, the revealing of
adverse drug reaction (ADR) in pharmacovigilance has seen a surge in use of social media …