Сравнение методов

	Многослойный PageRank	Directed PageRank
Область	Сетевой анализ	Сетевой анализ
Семейство	Machine learning	Machine learning
Год появления	2015	1998
Автор метода	De Domenico, M.; Sole-Ribalta, A.; Arenas, A. et al.	Brin, S. & Page, L.
Тип	Centrality measure (random-walk-based)	Iterative authority-scoring algorithm
Основополагающий источник	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.	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.
Другие названия	multiplex PageRank, layer-coupled PageRank, multilayer random walk centrality, MuxRank	PageRank, PR, Google PageRank, directed link analysis
Связанные	5	5
Сводка	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.