The modern science of networks has brought significant advances to our understanding of
complex systems. One of the most relevant features of graphs representing real systems is …

The increasing availability of large-scale protein-protein interaction data has made it
possible to understand the basic components and organization of cell machinery from the …

To meet the requirement of social influence analytics in various applications, the problem of
influence maximization has been studied in recent years. The aim is to find a limited number …

Complex networks exist in a wide range of real world systems, such as social networks,
technological networks, and biological networks. During the last decades, many researchers …

In this paper, we first discuss the definition of modularity (Q) used as a metric for community
quality and then we review the modularity maximization approaches which were used for …

Community discovery in complex networks is an interesting problem with a number of
applications, especially in the knowledge extraction task in social and information networks …

This work proposes V-SMART-Join, a scalable MapReduce-based framework for
discovering all pairs of similar entities. The V-SMART-Join framework is applicable to sets …

In this paper we present and evaluate a parallel community detection algorithm derived from
the state-of-the-art Louvain modularity maximization method. Our algorithm adopts a novel …

Given a social graph, the problem of influence maximization is to determine a set of nodes
that maximizes the spread of influences. While some recent research has studied the …

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