Machine learningNetwork science
多层 PageRank
多层 PageRank 将经典的 PageRank 随机游走中心性扩展到包含多个相互关联层的网络——例如，一个社交网络，人们同时通过友谊、职业联系和在线平台相互连接。通过允许虚拟行者在层内和层间跳转，该算法可以识别在整个多层结构中具有影响力而不仅仅是在任何单个层中具有影响力的节点。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- 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: 10.1038/ncomms7868 ↗
- Boccaletti, S., Bianconi, G., Criado, R., del Genio, C. I., Gomez-Gardenes, J., Romance, M., Sendina-Nadal, I., Wang, Z., & Zanin, M. (2014). The structure and dynamics of multilayer networks. Physics Reports, 544(1), 1–122. DOI: 10.1016/j.physrep.2014.07.001 ↗
如何引用本页
ScholarGate. (2026, June 3). Multilayer PageRank (Centrality on Multiplex and Multilayer Networks). ScholarGate. https://scholargate.app/zh/network-analysis/multilayer-pagerank
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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