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مركزية المتجه الذاتي الموجه×PageRank الموجه×
المجالتحليل الشبكاتتحليل الشبكات
العائلةMachine learningMachine learning
سنة النشأة1972–19871998
صاحب الطريقةBonacich, P.Brin, S. & Page, L.
النوعCentrality measure (eigenvector-based, directed)Iterative authority-scoring algorithm
المصدر التأسيسيBonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92(5), 1170–1182. 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 ↗
الأسماء البديلةdirected EC, asymmetric eigenvector centrality, right eigenvector centrality, left eigenvector centralityPageRank, PR, Google PageRank, directed link analysis
ذات صلة55
الملخصDirected eigenvector centrality extends the classic eigenvector centrality to directed graphs by scoring each node according to the centrality of the nodes that point to it (in-direction) or that it points to (out-direction). A node earns a high score not merely by having many connections but by being connected to other highly central nodes, capturing asymmetric influence in citation networks, social hierarchies, and information flows.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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ScholarGateقارن الطرق: Directed Eigenvector Centrality · Directed PageRank. استُرجع بتاريخ 2026-06-15 من https://scholargate.app/ar/compare