Increasing the scalability of the fitting of generalised block models for social networks

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2011, Pages 1218-1224

  Chan, Jeffrey ^a   Lam, Samantha ^a   Hayes, Conor ^a  

^a NATIONAL UNIVERSITY OF IRELAND   (Ireland)

Author keywords

[No Author keywords available]

Indexed keywords

BLOCK MODELS; NEW APPROACHES; ORDERS OF MAGNITUDE; REAL DATA SETS;

ARTIFICIAL INTELLIGENCE; SIMULATED ANNEALING; SOCIAL NETWORKING (ONLINE);

ALGORITHMS;

EID: 84881059227     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5591/978-1-57735-516-8/IJCAI11-207     Document Type: Conference Paper

References (17)

1. E. Airoldi, D. Blei, S. Fienberg, and E. Xing. Mixed membership stochastic blockmodels.Journal of Machine Learning Research, 9:1981-2014, 2008.
2. S. Borgatti and M. Everett. Notions of position in social network analysis. Sociological Methodology, 22:1-35, 1992.
3. R. Brendel and H. Krawczyk. Extended generalized blockmodeling for compound communities and external actors. In Proceedings of CASoN, pages 32-39, 2009.
4. T.N. Bui and B.R. Moon. Genetic algorithm and graph partitioning. Computers, IEEE Transactions on, 45(7):841-855, 2002.
5. A. Clauset, M. Newman, and C. Moore. Finding community structure in very large networks. Phys. Rev. E, 70(6):066111, Dec 2004.
6. J. Diesner, T. Frantz, and K. Carley. Communication Networks from the Enron Email Corpus It's Always About the People. Enron is no Different. Computational & Mathematical Organization Theory, 11(3):201-228, 2005. (Pubitemid 43118967)
7. P. Doreian, V. Batagelj, and A. Ferligoj. Generalized blockmodeling. Cambridge University Press, 2005.
8. T James. Grouping genetic algorithm for the blockmodel problem. IEEE Transactions on Evolutionary Computing, 14(1):103-111, 2010.
9. D. Johnson, C. Aragon, L. Mcgeoch, and C. Schevon. Annealing : An Experimental by Simulated Optimization Part 11, Graph Coloring and Evaluation; Number Partitioning. Operations Research, 39(3):378-406, 1991.
10. B. Kernighan and S. Lin. An efficient heuristic procedure for partitioning graphs. Bell System Technical Journal, 49(2):291-307, 1970.
11. A. Lancichinetti, S. Fortunato, and F. Radicchi. Benchmark graphs for testing community detection algorithms. Phy. Rev. E, 78(4):46110, 2008.
12. J. Lerner. Role assignments. In Network Analysis, pages 216-252, 2004.
13. M. Meila. Comparing clusterings by the variation of information. In Proceedings of the COLT/Kernel, pages 173-187. Springer Verlag, 2003.
14. Z. Michalewicz. Genetic algorithms + data structures = evolution programs (3rd ed.). Springer-Verlag, London, UK, 1996.
15. K. Nowicki and T. Snijders. Estimation and prediction for stochastic blockstructures. Journal of American Statistical Association, 96(455):1077-1087, 2001.
16. M Rosvall and C T Bergstrom. Maps of random walks on complex networks reveal community structure. PNAS, 105:1118-1123, 2008. (Pubitemid 351397014)
17. S. Wasserman and K. Faust. Social Network Analysis: Methods and Applications. Cambridge University Press, 1 edition, 1994.