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dc.contributor.authorBeckett, Stephen J.en_US
dc.date.accessioned2018-10-30T07:00:44Z
dc.date.available2018-10-30T07:00:44Z
dc.date.issued2016
dc.identifier.otherHPU4160522en_US
dc.identifier.urihttp://lib.pyu.edu.vn/handle/123456789/1930
dc.description.abstractReal world complex networks are composed of non random quantitative interactions. Identifying communities of nodes that tend to interact more with each other than the network as a whole is a key research focus across multiple disciplines, yet many community detection algorithms only use information about the presence or absence of interactions between nodes. Weighted modularity is a potential method for evaluating the quality of community partitions in quantitative networks.en_US
dc.language.isoenen_US
dc.subjectBiologyen_US
dc.subjectGraph theoryen_US
dc.subjectComputational biologyen_US
dc.subjectEcologyen_US
dc.subjectModular structureen_US
dc.subjectNetwork ecologyen_US
dc.subjectBipartite networksen_US
dc.subjectModulesen_US
dc.titleImproved community detection inweighted bipartite networksen_US
dc.typeArticleen_US
dc.size736KBen_US
dc.departmentEducationen_US


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