Journal
PHYSICAL REVIEW E
Volume 83, Issue 6, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.83.066114
Keywords
-
Categories
Funding
- UK Research Council [EP/I011587/1]
- Microsoft Research
- EPSRC [EP/I011587/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/I011587/1] Funding Source: researchfish
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available