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پیج‌رنک جهت‌دار×مرکزیت بردار ویژه×
حوزهتحلیل شبکهتحلیل شبکه
خانوادهMachine learningMachine learning
سال پیدایش19981972
پدیدآورBrin, S. & Page, L.Bonacich, P.
نوعIterative authority-scoring algorithmCentrality measure
منبع بنیادینBrin, 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 ↗Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113–120. DOI ↗
نام‌های دیگرPageRank, PR, Google PageRank, directed link analysiseigenvector centrality, EC, Bonacich centrality, power centrality
مرتبط56
خلاصهDirected 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.Eigenvector centrality, introduced by Bonacich in 1972, measures a node's influence by considering not just how many neighbors it has, but how influential those neighbors are. A node scores highly if it is connected to other high-scoring nodes, making it a recursive, globally-aware measure of structural importance in a network.
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ScholarGateمقایسهٔ روش‌ها: Directed PageRank · Eigenvector Centrality. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare