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Multilager detektion av gemenskaper×Stochastic Block Model×
ÄmnesområdeNätverksanalysNätverksanalys
FamiljMachine learningProcess / pipeline
Ursprungsår2010–20141983
UpphovspersonMucha, P. J. et al.; Kivela, M. et al.
TypCommunity detection algorithm for multilayer networksProbabilistic generative graph model
UrsprungskällaKivela, 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)
Närliggande57
SammanfattningMultilayer 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.
ScholarGateDatamängd
  1. v1
  2. 2 Källor
  3. PUBLISHED
  1. v1
  2. 2 Källor
  3. PUBLISHED

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ScholarGateJämför metoder: Multilayer Community Detection · Stochastic Block Model. Hämtad 2026-06-18 från https://scholargate.app/sv/compare