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• W2964261708 startingPage "121949" @default.
• W2964261708 abstract "Clustering nodes of a network into communities is a basic tool for identifying structure in complex system. We extend spectral clustering to multiplex structures and discuss some of the difficulties that arise in defining natural generalizations of the single layer case. To analyze the effectiveness of our approaches, we construct three simple families of synthetic multiplex networks and compare the performance of two different versions of multiplex spectral clustering. Our two clustering models – one based on the diagonal supra-Laplacian and the other based on a different diffusive model – perform differently on our tests. The first essentially interpolates between splitting the layers of the networks into different clusters and finding the layer clusters while the second interpolates between the layer clusterings, often finding clusters that span the different layers which reflect multiplex characteristics of the network." @default.
• W2964261708 created "2019-07-30" @default.
• W2964261708 creator A5019973061 @default.
• W2964261708 creator A5078170104 @default.
• W2964261708 date "2019-11-01" @default.
• W2964261708 modified "2023-10-01" @default.
• W2964261708 title "Spectral clustering methods for multiplex networks" @default.
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• W2964261708 doi "https://doi.org/10.1016/j.physa.2019.121949" @default.
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