Сравнение методов

	Многослойный анализ социальных сетей	Анализ графов знаний
Область	Сетевой анализ	Сетевой анализ
Семейство	Machine learning	Machine learning
Год появления	2014	2012–2016
Автор метода	Kivela, M.; Boccaletti, S. et al.	Ehrlinger, L. & Wöß, W.; Google (popularized)
Тип	Structural network analysis framework	Graph-based knowledge representation and analysis
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.	Ehrlinger, L. & Wöß, W. (2016). Towards a Definition of Knowledge Graphs. In Proceedings of the SEMANTICS Posters and Demos Track (SEMANTiCS 2016). CEUR Workshop Proceedings, vol. 1695.
Другие названия	MSNA, multiplex network analysis, multilayer network analysis, interconnected network analysis	KG analysis, semantic graph analysis, knowledge base graph analysis, entity-relation graph analysis
Связанные	6	5
Сводка	Multilayer social network analysis extends classical single-layer network methods to settings where actors are connected through multiple, distinct types of ties — such as friendship, professional collaboration, and online interaction — simultaneously. By modeling each type of relationship as a separate layer and explicitly representing connections across layers, it captures structural complexity that a single aggregated network would hide.	Knowledge Graph Analysis is a framework for representing, storing, and reasoning over structured factual knowledge as a directed graph of entities and typed relations. Entities (nodes) and relationships (edges) are expressed as subject–predicate–object triples, enabling rich querying, inference, and integration of heterogeneous data sources across domains such as biomedical research, e-commerce, and scientific literature.