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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| PageRank Dirigé× | Centralité d'intermédiarité× | |
|---|---|---|
| Domaine | Analyse de réseaux | Analyse de réseaux |
| Famille | Machine learning | Machine learning |
| Année d'origine≠ | 1998 | 1977 |
| Auteur d'origine≠ | Brin, S. & Page, L. | Freeman, L. C. |
| Type≠ | Iterative authority-scoring algorithm | Centrality measure |
| Source fondatrice≠ | 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 ↗ | Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗ |
| Alias | PageRank, PR, Google PageRank, directed link analysis | Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness |
| Apparentées≠ | 5 | 6 |
| Résumé≠ | 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. | Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes. |
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