4.7 Article

Overlapping community detection using Bayesian non-negative matrix factorization

Journal

PHYSICAL REVIEW E
Volume 83, Issue 6, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.83.066114

Keywords

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Funding

  1. UK Research Council [EP/I011587/1]
  2. Microsoft Research
  3. EPSRC [EP/I011587/1] Funding Source: UKRI
  4. Engineering and Physical Sciences Research Council [EP/I011587/1] Funding Source: researchfish

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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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