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An efficient semi-supervised community detection framework in social networks
2017
PLoS ONE
Community detection is an important tasks across a number of research fields including social science, biology, and physics. In the real world, topology information alone is often inadequate to accurately find out community structure due to its sparsity and noise. The potential useful prior information such as pairwise constraints which contain must-link and cannot-link constraints can be obtained from domain knowledge in many applications. Thus, combining network topology with prior
doi:10.1371/journal.pone.0178046
pmid:28542520
pmcid:PMC5441628
fatcat:mtqddf5jyrgltnkmm5upskayeq