Community detection in scientific collaborative network with bayesian matrix learning

1. Newman M E J. Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences, 2004, 101(suppl 1): 5200–5205

   Google Scholar 

2. Danon L, Díaz-Guilera A, Arenas A. The effect of size heterogeneity on community identification in complex networks. Journal of Statistical Mechanics: Theory and Experiment, 2006, 2006(11): P11010

   Book  Google Scholar 

3. Lu H T, Fu Z Y, Shu X. Non-negative and sparse spectral clustering. Pattern Recognition, 2014, 47(1): 418–426

   Article  MATH  Google Scholar 

4. Blondel V D, Guillaume J L, Lambiotte R, Lefebvre, E. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008, 2008(10): P10008

   Book  Google Scholar 

5. Le Martelot E, Hankin C. Fast multi-scale detection of relevant communities in large-scale networks. The Computer Journal, 2013, 56(9): 1136–1150

   Article  Google Scholar 

6. Lee D D, Seung H S. Algorithms for non-negative matrix factorization. Advances in Neural Information Processing Systems, 2001, 13: 556–562

   Google Scholar 

7. Wang F, Li T, Wang X, Chris D. Community discovery using nonnegative matrix factorization. Data Mining and Knowledge Discovery, 2011, 22(3): 493–521

   Article  MathSciNet  MATH  Google Scholar 

8. Cemgil A T. Bayesian inference for nonnegative matrix factorisation models. Computational Intelligence and Neuroscience, 2009, 2009: 1–17

   Article  Google Scholar 

Download references