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→基于推论统计学的社团检测算法
| arxiv = 1310.4377
| arxiv = 1310.4377
| bibcode = 2014PhRvX...4a1047P
| bibcode = 2014PhRvX...4a1047P
}}</ref>。 模型选择可以使用一些有原则的算法，例如最小描述长度(或贝叶斯模型选择<ref>{{cite arxiv|last=P. Peixoto|first=T.|date=2017|title=Bayesian stochastic blockmodeling|eprint=1705.10225|class=stat.ML}}</ref>)和似然比检定<ref>
}}</ref>。 模型选择可以使用一些有原则的算法，例如最小描述长度<ref>{{cite journal
|author1=Martin Rosvall |author2=Carl T. Bergstrom | year = 2007
| title = An information-theoretic framework for resolving community structure in complex networks
| journal = Proceedings of the National Academy of Sciences of the United States of America
| volume = 104
| issue = 18
| pages = 7327–7331
| doi = 10.1073/pnas.0611034104
| pmid=17452639
| pmc=1855072
| arxiv=physics/0612035| bibcode=2007PNAS..104.7327R}}</ref><ref>{{Cite journal|last=P. Peixoto|first=T.|date=2013|title=Parsimonious Module Inference in Large Networks|journal=Phys. Rev. Lett. |volume=110 |issue=14|page=148701|doi=10.1103/PhysRevLett.110.148701|pmid=25167049|bibcode=2013PhRvL.110n8701P|arxiv=1212.4794}}</ref>
(或贝叶斯模型选择<ref>{{cite arxiv|last=P. Peixoto|first=T.|date=2017|title=Bayesian stochastic blockmodeling|eprint=1705.10225|class=stat.ML}}</ref>)和似然比检定<ref>
{{cite journal
{{cite journal
| last = Yan
| last = Yan
}}
}}
</ref>
</ref>
===基于团结构的社团检测算法===
===基于团结构的社团检测算法===