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2012
ACM

Finding maximal k-edge-connected subgraphs from a large graph

8 years 5 months ago
Finding maximal k-edge-connected subgraphs from a large graph
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. To find maximal k-edge-connected subgraphs from a graph, a basic approach is to repeatedly apply minimum cut algorithm to the connected components of the input graph until all connected components are k-connected. However, the basic approach is very expensive if the input graph is large. To tackle the problem, we propose three major techniques: vertex reduction, edge reduction ...
Rui Zhou, Chengfei Liu, Jeffrey Xu Yu, Weifa Liang
Added 29 Sep 2012
Updated 29 Sep 2012
Type Journal
Year 2012
Where EDBT
Authors Rui Zhou, Chengfei Liu, Jeffrey Xu Yu, Weifa Liang, Baichen Chen, Jianxin Li
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