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Multilayer PageRank×Detecção de Comunidades Multicamadas×
ÁreaAnálise de redesAnálise de redes
FamíliaMachine learningMachine learning
Ano de origem20152010–2014
Autor originalDe Domenico, M.; Sole-Ribalta, A.; Arenas, A. et al.Mucha, P. J. et al.; Kivela, M. et al.
TipoCentrality measure (random-walk-based)Community detection algorithm for multilayer networks
Fonte seminalDe Domenico, M., Sole-Ribalta, A., Omodei, E., Gomez, S., & Arenas, A. (2015). Ranking in interconnected multilayer networks reveals versatile nodes. Nature Communications, 6, 6868. DOI ↗Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271. DOI ↗
Outros nomesmultiplex PageRank, layer-coupled PageRank, multilayer random walk centrality, MuxRankmultilayer clustering, multiplex community detection, cross-layer community detection, MCD
Relacionados55
ResumoMultilayer PageRank extends the classic PageRank random-walk centrality to networks that contain multiple interconnected layers — such as a social network where people are connected simultaneously via friendship, professional ties, and online platforms. By allowing a virtual walker to jump both within and across layers, the algorithm identifies nodes that are influential across the entire multilayer structure, not just within any single layer.Multilayer community detection identifies groups of nodes that are densely connected across multiple types of relationships simultaneously. By coupling layers of a network — such as friendship, advice, and collaboration ties — it finds communities that are coherent not just within one relation type but across all of them, revealing structure that single-layer analysis would miss.
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ScholarGateComparar métodos: Multilayer PageRank · Multilayer Community Detection. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare