Document Detail


Biclique communities.
MedLine Citation:
PMID:  18764021     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
We present a method for detecting communities in bipartite networks. Based on an extension of the k -clique community detection algorithm, we demonstrate how modular structure in bipartite networks presents itself as overlapping bicliques. If bipartite information is available, the biclique community detection algorithm retains all of the advantages of the k -clique algorithm, but avoids discarding important structural information when performing a one-mode projection of the network. Further, the biclique community detection algorithm provides a level of flexibility by incorporating independent clique thresholds for each of the nonoverlapping node sets in the bipartite network.
Authors:
Sune Lehmann; Martin Schwartz; Lars Kai Hansen
Publication Detail:
Type:  Journal Article     Date:  2008-07-21
Journal Detail:
Title:  Physical review. E, Statistical, nonlinear, and soft matter physics     Volume:  78     ISSN:  1539-3755     ISO Abbreviation:  Phys Rev E Stat Nonlin Soft Matter Phys     Publication Date:  2008 Jul 
Date Detail:
Created Date:  2008-09-03     Completed Date:  2008-09-15     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101136452     Medline TA:  Phys Rev E Stat Nonlin Soft Matter Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  016108     Citation Subset:  -    
Affiliation:
Center for Complex Network Research and Department of Physics, Northeastern University, Boston, Massachusetts 02115, USA.
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