GA-Net: A Genetic Algorithm for Community Detection in Social Networks
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
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A co-clustering algorithm for large sparse binary data matrices, based on a greedy technique and enriched with a local search strategy to escape poor local maxima, is proposed. The algorithm starts with an initial random solution and searches for a locally optimal solution by successive transformations that improve a quality function which combines row and column means together with the size of the co-cluster. Experimental results on synthetic and real data sets show that the method is able to find significant co-clusters.