| Overlapping community detection using Bayesian non-negative matrix factorization. | |
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MedLine Citation:
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PMID: 21797448 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Identifying overlapping communities in networks is a challenging task. In this work we present a probabilistic approach to community detection that utilizes a Bayesian non-negative matrix factorization model to extract overlapping modules from a network. The scheme has the advantage of soft-partitioning solutions, assignment of node participation scores to modules, and an intuitive foundation. We present the performance of the method against a variety of benchmark problems and compare and contrast it to several other algorithms for community detection. |
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Authors:
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Ioannis Psorakis; Stephen Roberts; Mark Ebden; Ben Sheldon |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-6-22 |
Journal Detail:
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Title: Physical review. E, Statistical, nonlinear, and soft matter physics Volume: 83 ISSN: 1550-2376 ISO Abbreviation: - Publication Date: 2011 Jun |
Date Detail:
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Created Date: 2011-7-29 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101136452 Medline TA: Phys Rev E Stat Nonlin Soft Matter Phys Country: - |
Other Details:
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Languages: ENG Pagination: 066114 Citation Subset: - |
Affiliation:
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Pattern Analysis and Machine Learning Research Group, Department of Engineering Science, University of Oxford, Oxford, United Kingdom. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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