Publication | Open Access
Finding maximal k-edge-connected subgraphs from a large graph
102
Citations
26
References
2012
Year
Unknown Venue
Cluster ComputingVertex ClustersEngineeringRelated Vertex ClusterNetwork AnalysisLarge GraphGraph ProcessingData ScienceData MiningStructural Graph TheoryCombinatorial OptimizationSocial Network AnalysisKnowledge DiscoveryHypergraph TheoryComputer ScienceGraph AlgorithmNetwork ScienceGraph TheoryBusinessGraph AnalysisExtremal Graph Theory
In this paper, we study how to find maximal k-edge-connected subgraphs from a large graph. k-edge-connected subgraphs can be used to capture closely related vertices, and finding such vertex clusters is interesting in many applications, e. g., social network analysis, bioinformatics, web link research. Compared with other explicit structures for modeling vertex clusters, such as quasi-clique, k-core, which only set the requirement on vertex degrees, k-edge-connected subgraph further requires high connectivity within a subgraph (a stronger requirement), and hence defines a more closely related vertex cluster.
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