Machine learningNetwork science

Dinamički stohastički blok model

Dinamički stohastički blok model (DSBM) je generativni probabilistički okvir koji proširuje statički stohastički blok model na mreže promatrane u više vremenskih točaka. Zajednički modelira pripadnost zajednicama i evoluciju zajednica, omogućujući istraživačima da otkriju i prate latentne skupine i njihove strukturne promjene tijekom vremena u longitudinalnim podacima mreže.

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Izvori

  1. Yang, T., Chi, Y., Zhu, S., Gong, Y., & Jin, R. (2011). Detecting communities and their evolutions in dynamic social networks — a Bayesian approach. Machine Learning, 82(2), 157–189. DOI: 10.1007/s10994-010-5214-7
  2. Matias, C., & Miele, V. (2017). Statistical clustering of temporal networks through a dynamic stochastic block model. Journal of the Royal Statistical Society: Series B, 79(4), 1119–1141. DOI: 10.1111/rssb.12200

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Dynamic Stochastic Block Model (Temporal Community Detection). ScholarGate. https://scholargate.app/hr/network-analysis/dynamic-stochastic-block-model

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ScholarGateDynamic Stochastic Block Model (Dynamic Stochastic Block Model (Temporal Community Detection)). Preuzeto 2026-06-15 s https://scholargate.app/hr/network-analysis/dynamic-stochastic-block-model · Skup podataka: https://doi.org/10.5281/zenodo.20539026