A number of predictors have been suggested to detect the most influential spreaders of
information in online social media across various domains such as Twitter or Facebook. In …

The k-truss is a type of cohesive subgraphs proposed recently for the study of networks.
While the problem of computing most cohesive subgraphs is NP-hard, there exists a …

The k-core of a graph is the largest subgraph in which every vertex is connected to at least k
other vertices within the subgraph. Core decomposition finds the k-core of the graph for …

Graphs have been widely used in many applications such as social networks, collaboration
networks, and biological networks. One important graph analytics is to explore cohesive …

Core decomposition is a fundamental graph problem with a large number of applications.
Most existing approaches for core decomposition assume that the graph is kept in memory …

Core decomposition has been applied widely in the visualization and analysis of massive
networks. However, existing studies of core decomposition were only limited to non …

Capturing sets of closely related vertices from large networks is an essential task in many
applications such as social network analysis, bioinformatics, and web link research …

Core decomposition is a fundamental graph problem with a large number of applications.
Most existing approaches for core decomposition assume that the graph is kept in memory …

Super-spreaders are the nodes of a network that can maximize their impacts on other nodes,
eg, in the case of information spreading or virus propagation. Many centrality measures …

The problem of computing k-edge connected components (k-ECC ECC s) of a graph G for a
specific k is a fundamental graph problem and has been investigated recently. In this paper …