Сравнение методов

	Многослойный анализ графов знаний	Анализ диффузии в многослойных сетях
Область	Сетевой анализ	Сетевой анализ
Семейство	Machine learning	Machine learning
Год появления	2014–2016	2013–2014
Автор метода	Kivela, M. et al.; Nickel, M. et al.	Gomez, S. et al.; Boccaletti, S. et al.
Тип	Graph-based analytical framework	Network diffusion model
Основополагающий источник	Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271.	Gomez, S., Diaz-Guilera, A., Gomez-Gardenes, J., Perez-Vicente, C. J., Moreno, Y., & Arenas, A. (2013). Diffusion dynamics on multiplex networks. Physical Review Letters, 110(2), 028701.
Другие названия	multi-relational knowledge graph analysis, multilayer KG analysis, multi-relational graph analysis, multiplex knowledge graph analysis	multiplex diffusion analysis, multilayer spreading analysis, cross-layer contagion analysis, diffusion on multiplex networks
Связанные	5	6
Сводка	Multilayer knowledge graph analysis treats a knowledge base as a stack of relation-specific network layers sharing the same entity set, enabling simultaneous reasoning across relation types. Unlike a flat single-layer graph, it preserves the semantic distinctions between relation types and supports cross-layer link prediction, entity alignment, and community detection grounded in multilayer network theory.	Multilayer Network Diffusion Analysis models how information, disease, or influence spreads across a system composed of multiple, interconnected network layers. By coupling diffusion processes across layers — for instance social ties, transport routes, and online channels simultaneously — it reveals how cross-layer interactions accelerate or dampen spreading and lowers epidemic thresholds compared to single-layer models.