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• W2372964457 abstract "Aiming at the matter that the current level classification community algorithms are difficult to select the appropriate initial nodes lead to poor result for community structure divided, this paper proposes a layer partition algorithm based on hierarchical level to select core nodes. Algorithm screens the cores by evaluation criteria of degree and closeness. In order to overcome the shortage that dissimilarity index measures the similarity of nodes within a community, introducing node dissimilarity to evaluate the similarity between initial cores and the initial node set with higher node similarity. By adopting strategy of global optimization modularity and realizing community division in complex network, when applied in standard datasets, experimental results show that, compared with GN algorithm, FN algorithm, the proposed algorithm has a better classification effect and lower time complexity." @default.
• W2372964457 created "2016-06-24" @default.
• W2372964457 creator A5027721616 @default.
• W2372964457 date "2014-01-01" @default.
• W2372964457 modified "2023-09-24" @default.
• W2372964457 title "A Hierarchical Division Algorithm for Community Based on Node Dissimilarity" @default.
• W2372964457 hasPublicationYear "2014" @default.
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