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Improving heuristics for network modularity maximization using an exact algorithm

Abstract : Heuristics are widely applied to modularity maximization models for the identification of communities in complex networks. We present an approach to be applied as a post-processing to heuristic methods in order to improve their performances. Starting from a given partition, we test with an exact algorithm for bipartitioning if it is worthwhile to split some communities or to merge two of them. A combination of merge and split actions is also performed. Computational experiments show that the proposed approach is effective in improving heuristic results.
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Submitted on : Thursday, April 3, 2014 - 3:36:40 PM
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Sonia Cafieri, Pierre Hansen, Leo Liberti. Improving heuristics for network modularity maximization using an exact algorithm. Discrete Applied Mathematics, Elsevier, 2014, 163 (1), pp 65-72. ⟨10.1016/j.dam.2012.03.030⟩. ⟨hal-00935211⟩



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