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Rettet Nærhedscentralitet×Directed PageRank×
FagområdeNetværksanalyseNetværksanalyse
FamilieMachine learningMachine learning
Oprindelsesår1979–19941998
OphavspersonFreeman, L. C.; Wasserman, S. & Faust, K.Brin, S. & Page, L.
TypeCentrality measureIterative authority-scoring algorithm
Oprindelig kildeWasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38269-4Brin, 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 ↗
Aliasserdirected closeness, in-closeness centrality, out-closeness centrality, directional closenessPageRank, PR, Google PageRank, directed link analysis
Relaterede55
ResuméDirected closeness centrality extends the classical closeness measure to directed networks by separately quantifying how quickly a node can be reached by others (in-closeness) and how quickly it can reach all others (out-closeness). It is a foundational node-level metric in social network analysis and graph theory, used wherever link direction conveys meaningful asymmetry such as citation flows, information cascades, or authority hierarchies.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: Directed Closeness Centrality · Directed PageRank. Hentet 2026-06-18 fra https://scholargate.app/da/compare