Machine learningNetwork science

Analiza difuzije zasnovana na Bejzijanskim mrežama

Analiza difuzije zasnovana na Bejzijanskim mrežama primenjuje Bejzijansko verovatnosno zaključivanje na proučavanje načina na koji se informacije, bolesti, ponašanja ili inovacije šire kroz mrežu. Postavljanjem apriornih distribucija na parametre difuzije i njihovim ažuriranjem na osnovu opserviranih podataka o kaskadama, kvantifikuju se stope prenosa, identifikuju uticajni širitelji, rekonstruišu latentni putevi širenja i pružaju potpune procene nesigurnosti — sve u okviru principijelnog statističkog okvira.

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Izvori

  1. Gomez Rodriguez, M., Leskovec, J., & Scholkopf, B. (2012). Structure and Dynamics of Information Pathways in Online Media. Proceedings of the 6th ACM International Conference on Web Search and Data Mining (WSDM), 23–32. DOI: 10.1145/2433396.2433402
  2. Kitsak, M., Gallos, L. K., Havlin, S., Liljeros, F., Muchnik, L., Stanley, H. E., & Makse, H. A. (2010). Identification of influential spreaders in complex networks. Nature Physics, 6(11), 888–893. DOI: 10.1038/nphys1746

Kako citirati ovu stranicu

ScholarGate. (2026, June 3). Bayesian Network Diffusion Analysis (Probabilistic Inference on Contagion and Spreading Processes). ScholarGate. https://scholargate.app/sr/network-analysis/bayesian-network-diffusion-analysis

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Citirana u

ScholarGateBayesian Network Diffusion Analysis (Bayesian Network Diffusion Analysis (Probabilistic Inference on Contagion and Spreading Processes)). Preuzeto 2026-06-15 sa https://scholargate.app/sr/network-analysis/bayesian-network-diffusion-analysis · Skup podataka: https://doi.org/10.5281/zenodo.20539026