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• W2019965116 abstract "Community detection in weighted networks is an important challenge. In this paper, we introduce a local weight ratio scheme for identifying the community structures of weighted networks within the context of the Kuramoto model by taking into account weights of links. The proposed scheme takes full advantage of the information of the link density among vertices and the closeness of relations between each vertex and its neighbors. By means of this scheme, we explore the connection between community structures and dynamic time scales of synchronization. Moreover, we can also unravel the hierarchical structures of weighted networks with a well-defined connectivity pattern by the synchronization process. The performance of the proposed method is evaluated on both computer-generated benchmark graphs and real-world networks." @default.
• W2019965116 created "2016-06-24" @default.
• W2019965116 creator A5050096545 @default.
• W2019965116 creator A5078854904 @default.
• W2019965116 date "2011-11-07" @default.
• W2019965116 modified "2023-09-27" @default.
• W2019965116 title "Finding communities in weighted networks through synchronization" @default.
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• W2019965116 doi "https://doi.org/10.1063/1.3655371" @default.
• W2019965116 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/22225353" @default.
• W2019965116 hasPublicationYear "2011" @default.
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