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Bayesian PageRank×Rettet PageRank×
FagfeltNettverksanalyseNettverksanalyse
FamilieMachine learningMachine learning
Opprinnelsesår1999 (PageRank); 2000s (Bayesian extension)1998
OpphavspersonPage, L. & Brin, S. (PageRank); Bayesian extension by multiple authorsBrin, S. & Page, L.
TypeProbabilistic centrality measureIterative authority-scoring algorithm
Opprinnelig kildePage, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank citation ranking: Bringing order to the web. Stanford InfoLab Technical Report. link ↗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 ↗
AliasBayesian PR, probabilistic PageRank, uncertainty-aware PageRank, stochastic PageRankPageRank, PR, Google PageRank, directed link analysis
Relaterte65
SammendragBayesian PageRank extends the classic PageRank algorithm by embedding it within a Bayesian probabilistic framework. Instead of returning a single deterministic rank score for each node, it quantifies uncertainty over rank estimates — particularly valuable when the network is incomplete, noisy, or observed with error. It is used in web analysis, citation networks, and social network research where rank uncertainty matters.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: Bayesian PageRank · Directed PageRank. Hentet 2026-06-17 fra https://scholargate.app/no/compare