Salīdzināt metodes

	Daudzslāņu stohastiskais bloku modelis	Daudzslāņu kopienu noteikšana
Nozare	Tīklu analīze	Tīklu analīze
Saime	Machine learning	Machine learning
Izcelsmes gads	2015-2017	2010–2014
Autors	Peixoto, T. P.; De Bacco, C. and colleagues	Mucha, P. J. et al.; Kivela, M. et al.
Tips	Generative probabilistic model	Community detection algorithm for multilayer networks
Pirmavots	Peixoto, T. P. (2015). Inferring the mesoscale structure of layered, edge-valued, and time-varying networks. Physical Review E, 92(4), 042807.	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.
Citi nosaukumi	ML-SBM, multilayer SBM, multi-layer stochastic block model, multiplex stochastic block model	multilayer clustering, multiplex community detection, cross-layer community detection, MCD
Saistītās	4	5
Kopsavilkums	The Multilayer Stochastic Block Model (ML-SBM) is a generative probabilistic framework that extends the classical stochastic block model to networks with multiple relation types or layers. It simultaneously infers community structure and block-to-block connection probabilities across all layers, capturing how communities cohere differently depending on context or relationship type.	Multilayer community detection identifies groups of nodes that are densely connected across multiple types of relationships simultaneously. By coupling layers of a network — such as friendship, advice, and collaboration ties — it finds communities that are coherent not just within one relation type but across all of them, revealing structure that single-layer analysis would miss.