Uncovering Community Structures with Initialized Bayesian Nonnegative Matrix Factorization

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Correction: Uncovering Community Structures with Initialized Bayesian Nonnegative Matrix Factorization

Uncovering community structures is important for understanding networks. Currently, several nonnegative matrix factorization algorithms have been proposed for discovering community structure in complex networks. However, these algorithms exhibit some drawbacks, such as unstable results and inefficient running times. In view of the problems, a novel approach that utilizes an initialized Bayesian...

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ژورنال

عنوان ژورنال: PLoS ONE

سال: 2014

ISSN: 1932-6203

DOI: 10.1371/journal.pone.0107884