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| Multilayer PageRank× | Gerichtetes PageRank× | |
|---|---|---|
| Fachgebiet | Netzwerkanalyse | Netzwerkanalyse |
| Familie | Machine learning | Machine learning |
| Entstehungsjahr≠ | 2015 | 1998 |
| Urheber≠ | De Domenico, M.; Sole-Ribalta, A.; Arenas, A. et al. | Brin, S. & Page, L. |
| Typ≠ | Centrality measure (random-walk-based) | Iterative authority-scoring algorithm |
| Wegweisende Quelle≠ | De Domenico, M., Sole-Ribalta, A., Omodei, E., Gomez, S., & Arenas, A. (2015). Ranking in interconnected multilayer networks reveals versatile nodes. Nature Communications, 6, 6868. 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 ↗ |
| Aliasnamen | multiplex PageRank, layer-coupled PageRank, multilayer random walk centrality, MuxRank | PageRank, PR, Google PageRank, directed link analysis |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | Multilayer PageRank extends the classic PageRank random-walk centrality to networks that contain multiple interconnected layers — such as a social network where people are connected simultaneously via friendship, professional ties, and online platforms. By allowing a virtual walker to jump both within and across layers, the algorithm identifies nodes that are influential across the entire multilayer structure, not just within any single layer. | 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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