Machine learningNetwork science
时间模块度分析
时间模块度分析将标准的基于模块度的社区检测方法扩展到时变网络，方法是将每个时间切片视为一个网络层，并通过时间层之间的连接来耦合相邻层。这使得研究人员能够识别社区在动态关系数据中如何随时间形成、持续、合并、分裂和消散。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
来源
- Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P. (2010). Community structure in time-dependent, multiscale, and multiplex networks. Science, 328(5980), 876-878. DOI: 10.1126/science.1184819 ↗
- Holme, P., & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97-125. DOI: 10.1016/j.physrep.2012.03.001 ↗
如何引用本页
ScholarGate. (2026, June 3). Temporal Modularity Analysis (Dynamic Community Detection via Modularity Optimization). ScholarGate. https://scholargate.app/zh/network-analysis/temporal-modularity-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
Compare side by side →