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- W2569392167 abstract "Community structure is one of the most important properties existing in complex networks, and community detection in complex networks is an intensively investigated problem in recent years. In real-world networks, a node is usually shared by several overlapping communities. The problem of detecting overlapping communities is much more complicated than the hard-partition problem. In this paper, a multi-objective immune algorithm with nonnegative matrix factorization as local search module (MOIA-Net) is proposed to uncover overlapping communities in networks. The proposed algorithm simultaneously optimizes two criteria, negative ratio association and ratio cut, to achieve a preferable soft-partition in networks. It adopts a nonnegative matrix factorization strategy as local search procedure to enhance the search ability. Experiments on synthetic networks show the efficiency of the proposed algorithm." @default.
- W2569392167 created "2017-01-13" @default.
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- W2569392167 date "2016-01-01" @default.
- W2569392167 modified "2023-09-22" @default.
- W2569392167 title "Multi-objective Optimization with Nonnegative Matrix Factorization for Identifying Overlapping Communities in Networks" @default.
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- W2569392167 doi "https://doi.org/10.1007/978-981-10-3614-9_40" @default.
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