Community detection is one of the popular research topics in the field of complex networks
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …

Friend recommendation (FR) in social networks has been widely studied in recent years,
which mainly focuses on social relationships and user interests. Friend of Friend method is …

Detecting and tracking communities in dynamic social networks has been a grand
multidisciplinary challenge. There are two key steps in tracking the community evolution of …

Circle structure of online brand communities allows companies to conduct cross-marketing
activities by the influence of friends in different circles and build strong and lasting …

Dating recommendation becomes a critical task since the rapidly development of the online
dating sites and it is beneficial for users to find their ideal relationships from a large number …

Friend recommendation plays a key role in promoting user experience in online social
networks (OSNs). However, existing studies usually neglect users' fine-grained interest as …

Abstract Nonnegative Matrix Factorization (NMF) has been widely used to resolve the
problem of community detection in complex networks. The present NMF-based methods for …

Graph partitioning methods in data mining have been widely used to discover protein
complexes in protein–protein interaction (PPI) network. However, PPI networks with …

Nonnegative matrix factorization (NMF) has become a powerful model for community
discovery in complex networks. Existing NMF-based methods for community discovery often …

Network embedding, aiming to learn low-dimensional representations of nodes in networks,
is very useful for many vector-based machine learning algorithms and has become a hot …