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An augmented Lagrangian alternating direction method for overlapping community detection based on symmetric nonnegative matrix factorization

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In this paper, we present an augmented Lagrangian alternating direction algorithm for symmetric nonnegative matrix factorization. The convergence of the algorithm is also proved in detail and strictly. Then we… Click to show full abstract

In this paper, we present an augmented Lagrangian alternating direction algorithm for symmetric nonnegative matrix factorization. The convergence of the algorithm is also proved in detail and strictly. Then we present a modified overlapping community detection method which is based on the presented symmetric nonnegative matrix factorization algorithm. We apply the modified community detection method to several real world networks. The obtained results show the capability of our method in detecting overlapping communities, hubs and outliers. We find that our experimental results have better quality than several competing methods for identifying communities.

Keywords: matrix factorization; community detection; symmetric nonnegative; nonnegative matrix

Journal Title: International Journal of Machine Learning and Cybernetics
Year Published: 2020

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