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Multilayer PageRank×Directed PageRank×
FagområdeNetværksanalyseNetværksanalyse
FamilieMachine learningMachine learning
Oprindelsesår20151998
OphavspersonDe Domenico, M.; Sole-Ribalta, A.; Arenas, A. et al.Brin, S. & Page, L.
TypeCentrality measure (random-walk-based)Iterative authority-scoring algorithm
Oprindelig kildeDe 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 ↗Brin, S. & Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine. Proceedings of the 7th International Conference on World Wide Web (WWW7), 107–117. Elsevier. link ↗
Aliassermultiplex PageRank, layer-coupled PageRank, multilayer random walk centrality, MuxRankPageRank, PR, Google PageRank, directed link analysis
Relaterede55
ResuméMultilayer 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.Directed PageRank is a link-based authority scoring algorithm that assigns importance scores to nodes in a directed graph by iteratively redistributing rank through outgoing edges. Introduced by Brin and Page in 1998 as the backbone of Google Search, it measures not just how many in-links a node has but how authoritative the nodes pointing to it are.
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ScholarGateSammenlign metoder: Multilayer PageRank · Directed PageRank. Hentet 2026-06-17 fra https://scholargate.app/da/compare