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Multilagsdeteksjon av fellesskap×Stochastic Block Model×
FagfeltNettverksanalyseNettverksanalyse
FamilieMachine learningProcess / pipeline
Opprinnelsesår2010–20141983
OpphavspersonMucha, P. J. et al.; Kivela, M. et al.
TypeCommunity detection algorithm for multilayer networksProbabilistic generative graph model
Opprinnelig kildeKivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271. DOI ↗Holland, P.W., Laskey, K.B. & Leinhardt, S. (1983). Stochastic Blockmodels: First Steps. Social Networks, 5(2), 109-137. DOI ↗
Aliasmultilayer clustering, multiplex community detection, cross-layer community detection, MCDSBM, degree-corrected SBM, DCSBM, Stokastik Blok Modeli (SBM)
Relaterte57
SammendragMultilayer 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.The Stochastic Block Model (SBM), introduced by Holland, Laskey and Leinhardt (1983), is a probabilistic generative model for graphs that assigns nodes to latent blocks and parametrically estimates the connection probabilities between blocks. It is the foundational approach for community detection, core-periphery identification, and hierarchical structure discovery in network analysis.
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ScholarGateSammenlign metoder: Multilayer Community Detection · Stochastic Block Model. Hentet 2026-06-18 fra https://scholargate.app/no/compare