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• W2028365946 abstract "The paper proposes a new approach to detect shared community structure in multidimensional networks based on the combination of multiobjective genetic algorithms, local search, and the concept of temporal smoothness, coming from evolutionary clustering. A multidimensional network is clustered by running on each slice a multiobjective genetic algorithm that maximizes the modularity on such a slice and, at the same time, minimizes the difference between the community structure obtained for the current layer and that found on the already considered dimensions. Experiments on synthetic and real-world datasets show the ability of the approach in discovering latent shared clustering of objects." @default.
• W2028365946 created "2016-06-24" @default.
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• W2028365946 date "2014-11-01" @default.
• W2028365946 modified "2023-09-25" @default.
• W2028365946 title "Community Detection in Multidimensional Networks" @default.
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• W2028365946 doi "https://doi.org/10.1109/ictai.2014.60" @default.
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