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• W1618319632 abstract "In this paper we present the application of a novel methodology to scientific citation and collaboration networks. This methodology is designed for understanding the governing dynamics of evolving networks and relies on an attachment kernel, a scalar function of node properties, that stochastically drives the addition and deletion of vertices and edges. We illustrate how the kernel function of a given network can be extracted from the history of the network and discuss other possible applications.KeywordsKernel FunctionPhysical ReviewPreferential AttachmentCollaboration NetworkCitation NetworkThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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• W1618319632 date "2010-01-01" @default.
• W1618319632 modified "2023-09-26" @default.
• W1618319632 title "Estimating the dynamics of kernel-based evolving networks" @default.
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• W1618319632 doi "https://doi.org/10.1007/978-3-540-85081-6_12" @default.
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