Grasping
发表于 2025-3-28 17:13:22
Ivete Maria Baraldi,Fernanda Malinosky Coelho da Rosa,Vera Lúcia Messias Fialho Capellini,Erica Aparine-learning model on the snapshots and apply this model to the real-word network to find the best BI parameters. We apply these parameters to the sampled real-world network to measure the quality of the sets of initiators found this way. We use various real-world networks to validate our approach a
发芽
发表于 2025-3-28 18:57:14
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强壮
发表于 2025-3-29 00:19:30
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tolerance
发表于 2025-3-29 03:04:32
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OASIS
发表于 2025-3-29 08:05:05
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高脚酒杯
发表于 2025-3-29 13:49:17
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Leisureliness
发表于 2025-3-29 17:12:20
Désirée Laubenstein,Kirsten Guthöhrlein,Christian Lindmeier,David Scheer,Dirk Sponholzore etc.) could be considered as distance. In our analysis, we have primarily used degree centrality to denote the mass of the nodes, while the lengths of shortest paths between them have been used as distances. In this study we compare the proposed link prediction approach to 7 other methods on 4 d
Jubilation
发表于 2025-3-29 19:47:21
Yvonne Blumenthal,Stefan Voß,Simon Sikora,Bodo Hartkes were compared against an existing topological similarity-based link prediction metric. High-performance scores achieved by these dynamic feature, examined in this study, represent them as prospective candidates not only for dynamic link prediction task but also understanding of underlying network
Archipelago
发表于 2025-3-30 01:43:42
Brigitte Lutz-Westphal,Katharina Skutellaore etc.) could be considered as distance. In our analysis, we have primarily used degree centrality to denote the mass of the nodes, while the lengths of shortest paths between them have been used as distances. In this study we compare the proposed link prediction approach to 7 other methods on 4 d
macabre
发表于 2025-3-30 06:46:02
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