Efficiently inferring community structure in bipartite networks
نویسندگان
چکیده
منابع مشابه
Efficiently inferring community structure in bipartite networks
Bipartite networks are a common type of network data in which there are two types of vertices, and only vertices of different types can be connected. While bipartite networks exhibit community structure like their unipartite counterparts, existing approaches to bipartite community detection have drawbacks, including implicit parameter choices, loss of information through one-mode projections, a...
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Bipartite networks are an important category of complex networks in human social activities. Newman and Girvan proposed a measurement called modularity to evaluate community structure in unipartite networks called modularity. Due to the success of modularity in unipartite networks, bipartite modularity is developed according to different understandings of community in bipartite networks which a...
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ژورنال
عنوان ژورنال: Physical Review E
سال: 2014
ISSN: 1539-3755,1550-2376
DOI: 10.1103/physreve.90.012805