Socially aware networking is an emerging research field that aims to improve the current
networking technologies and realize novel network services by applying social network …

Recently, the topic of truss computation has gained plenty of attention, where the k-truss of a
graph is the maximum subgraph in which each edge participates in at least (k-2) triangles …

User engagement and tie strength are fundamental and important components in social
networks. The model of k-truss not only captures actively engaged users, but also ensures …

In public-private graphs, users share one public graph and have their own private graphs. A
private graph consists of personal private contacts that only can be visible to its owner, eg …

Structural clustering (SCAN) is one of the most popular graph clustering paradigms.
However, SCAN assumes that the input graph is undirected and can not cluster the directed …

This paper deals with the information transfer mechanisms underlying causal relations
between brain regions under resting condition. fMRI images of a large set of healthy …

Community search (CS) aims at personalized subgraph discovery which is the key to
understanding the organisation of many real-world networks. CS in undirected networks has …

Networks in many real-world applications come with an inherent uncertainty in their
structure, due to eg, noisy measurements, inference and prediction models, or for privacy …

Dense regions in networks are an indicator of interesting and unusual information. However,
most existing methods only consider simple, undirected, unweighted networks. Complex …

Social decisions made by individuals are easily influenced by information from their social
neighborhoods. A key predictor of social contagion is the multiplicity of social contexts inside …