Machine learningNetwork science
时序随机块模型
时序随机块模型（Temporal Stochastic Block Model, TSBM）将经典随机块模型（Stochastic Block Model）扩展到网络快照序列，联合推断潜在社区成员身份以及这些成员身份如何随时间演变。它结合了生成式边概率模型和块分配上的马尔可夫过程，从而能够对随时间变化的社区结构进行有原则的统计检测。
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来源
- 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 ↗
- Xu, K. S. & Hero, A. O. (2014). Dynamic stochastic blockmodels for time-evolving social networks. IEEE Journal of Selected Topics in Signal Processing, 8(4), 552–562. DOI: 10.1109/JSTSP.2014.2310294 ↗
如何引用本页
ScholarGate. (2026, June 3). Temporal Stochastic Block Model (Dynamic Community Detection via SBM). ScholarGate. https://scholargate.app/zh/network-analysis/temporal-stochastic-block-model
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