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Kernel spectral clustering for community detection in complex networks
2012
The 2012 International Joint Conference on Neural Networks (IJCNN)
This paper is related to community detection in complex networks. We show the use of kernel spectral clustering for the analysis of unweighted networks. We employ the primaldual framework and make use of out-of-sample extensions. In particular, we propose a method to extract from a network a small subgraph representative for its overall community structure. We use a model selection procedure based on the modularity statistic which is novel, because modularity is commonly used only at a training
doi:10.1109/ijcnn.2012.6252726
dblp:conf/ijcnn/LangoneAS12
fatcat:vtzvesp3nvetppawtxcrrntqpm