Fast online graph clustering via Erdo{combining double acute accent}s-Rényi mixture

Pattern Recognition

Volumn 41, Issue 12, 2008, Pages 3592-3599

  Zanghi, Hugo ^a   Ambroise, Christophe ^b   Miele, Vincent ^b  

^a Exalead   (France)

^b University of Paris 5   (France)

Author keywords

EM algorithm; Graph clustering; Online

Indexed keywords

ALGORITHMS; CLUSTER ANALYSIS; FLOW OF SOLIDS; GRAPH THEORY; MIXTURES; PARAMETER ESTIMATION; RHENIUM; SET THEORY;

BATCH ALGORITHMS; BLOGOSPHERE; COMMUNITY ORGANIZATIONS; COMPUTATIONAL COSTS; DATA SIZE; EM ALGORITHM; GRAPH CLUSTERING; GRAPH NODES; NUMEROUS APPLICATIONS; ON-LINE ALGORITHMS; ON-LINE CLUSTERING; ONLINE; REAL DATA; REAL DATA SETS;

CLUSTERING ALGORITHMS;

EID: 49749086479     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.06.019     Document Type: Article

References (32)

1. Barabasi A.-L. Linked: How Everything is Connected to Everything Else and What it Means for Business, Science, and Everyday Life (2003), Plume Books. http://www.amazon.ca/exec/obidos/redirect?tagciteulike09-20pathASIN/0452 284392 URL 〈http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20{& }path=ASIN/0452284392〉
2. Flake G.W., Lawrence S., Giles C.L., and Coetzee F. Self-organization of the web and identification of communities. J. IEEE Comput. 35 3 (2002) 66-71. http://citeseer.ist.psu.edu/flake02selforganization.html URL 〈citeseer.ist.psu.edu/flake02selforganization.html〉
3. Wasserman S., Faust K., and Iacobucci D. Social Network Analysis (1994), Cambridge University Press, Cambridge, UK. http://www.cambridge.org/catalogue/catalogue.asp?isbn9780521387071 URL 〈http://www.cambridge.org/catalogue/catalogue.asp?isbn=978052138707 1〉
4. Guimera R., and Amaral L.A.N. Functional cartography of complex metabolic networks. Nature 433 (2005) 895. http://www.citebase.org/abstract?idoai:arXiv.org:q-bio/0502035 URL 〈http://www.citebase.org/abstract?id=oai:arXiv.org:q-bio/0502035 〉
5. Newman M. Detecting community structure in networks. Eur. Phys. J. B. 38 2 (2004) 321-330
6. Fiedler M. Algebraic connectivity of graphs. Czech. Math. J. 23 (1973) 298-305
7. Schölkopf B., Knirsch P., Smola A., and Burges C. Fast approximation of support vector kernel expansions, and an interpretation of clustering as approximation in feature spaces. In: Levi P., Schanz M., Ahlers R.-J., and May F. (Eds). Mustererkennung 1998-20. DAGM-Symposium, Informatik aktuell (1998), Springer, Berlin 124-132
8. A. Ng, M. Jordan, Y. Weiss, On spectral clustering: analysis and an algorithm, in: NIPS 14, 2002.
9. Albert R., and Barabasi A.-L. Statistical mechanics of complex networks. Rev. Mod. Phys. 74 (2002) 47. http://www.citebase.org/abstract?idoai:arXiv.org:cond-mat/0106096 URL 〈http://www.citebase.org/abstract?id=oai:arXiv.org:cond-mat/0106096 〉
10. Daudin J.-J., Picard F., and Robin S. A mixture model for random graphs. Statist. Comput. 18 2 (2008) 151-171
11. Dempster A.P., Laird N.M., and Rubin D.B. Maximum-likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. B 39 (1977) 1-39
12. Snijders T.A.B., Pattison P.E., Robins G.L., and Handcock M.S. New specifications for exponential random graph models. Sociol. Methodol. 36 1 (2006) 99-153
13. Robles-Kelly A., and Hancock E. An EM-Like Algorithm for Motion Segmentation via Eigendecomposition. Proceedings of the British Machine Vision Conference (2001) 123-132
14. Snijders T.A.B., and Nowicki K. Estimation and prediction for stochastic block-structures for graphs with latent block structure. J. Classification 14 (1997) 75-100
15. Govaert G., and Nadif M. An EM algorithm for the block mixture model. IEEE Trans. Pattern Anal. Mach. Intell. 27 4 (2005) 643-647
16. Govaert G. Algorithme de classification d'un tableau de contingence. First International Symposium on Data Analysis and Informatics (1977), INRIA, Versailles 487-500
17. G. Govaert, Classification croisée. thèse d'état, université, Ph.D. Thesis, Paris 6, France, 1983.
18. Wasserman S., Faust K., and Iacobucci D. Social Network Analysis: Methods and Applications (Structural Analysis in the Social Sciences) (1994), Cambridge University Press, Cambridge. http://www.amazon.ca/exec/obidos/redirect?tag=citeulike04-20path=ASIN/05 21387078 URL 〈http://www.amazon.ca/exec/obidos/redirect?tag=citeulike04-20{& }path=ASIN/0521387078〉
19. Handcock M., Raftery A., and Tantrum J. Model based clustering for social networks. J. R. Stat. Soc. A. 170 (2007) 301-354
20. Newman M.E.J. Fast algorithm for detecting community structure in networks. Phys. Rev. E 69 (2004) 066133. http://www.citebase.org/abstract?id=oai:arXiv.org:cond-mat/0309508 URL 〈http://www.citebase.org/abstract?id=oai:arXiv.org:cond-mat/0309508 〉
21. A. Clauset, M.E.J. Newman, C. Moore, Finding community structure in very large networks, August 2004. URL 〈http://arxiv.org/abs/cond-mat/0408187〉.
22. Titterington D.M. Recursive parameter estimation using incomplete data. J. R. Stat. Soc. B 46 (1984) 257-267
23. S. Wang, Y. Zhao, Almost sure convergence of Titterington's recursive estimator for finite mixture models, in: IEEE International Symposium on Information Theory IST.
24. Liu Z., Almhana J., Choulakian V., and McGorman R. Online EM algorithm for mixture with application to Internet traffic modeling. Comput. Statist. Data Anal. 50 4 (2006) 1052-1071. http://ideas.repec.org/a/eee/csdana/v50y2006i4p1052-1071.html available at 〈http://ideas.repec.org/a/eee/csdana/v50y2006i4p1052-1071. html〉
25. MacQueen J. Some methods for classification and analysis of multivariate observations. Proceedings of the Fifth Berkeley Symposium on Mathematics, Statistics and Probability vol. 1 (1967) 281-296
26. H.A. Boubacar, S. Lecoeuche, A new kernel-based algorithm for online clustering, in: ICANN, 2005, pp. 583-588.
27. Frank O., and Harary F. Cluster inference by using transitivity indices in empirical graphs. J. Am. Stat. Assoc. 77 380 (1982) 835-840
28. Likas A. A reinforcement learning approach to on-line clustering. Neural Comput. 11 8 (1999) 1915-1932
29. Rosenfeld A., Hummel R., and Zucker S. Scene labeling by relaxation operations. SMC 6 6 (1976) 420-433
30. Hancock E., and Kittler J. Discrete relaxation. Pattern Recognition 23 7 (1990) 711-733
31. Biernacki C., Celeux G., and Govaert G. Assessing a mixture model for clustering with the integrated completed likelihood. IEEE Pattern Anal. Mach. Intell. 22 7 (2000) 719-725
32. Hubert L., and Arabie P. Comparing partitions. J. Classification 2 (1985) 193-218