A triclustering approach for time evolving graphs

Proceedings - 12th IEEE International Conference on Data Mining Workshops, ICDMW 2012

Volumn , Issue , 2012, Pages 115-122

  Guigourès, Romain ^a,b   Boullé, Marc ^a   Rossi, Fabrice ^b  

^a ORANGE LABS   (France)

^b Université Paris 1 Panthéon Sorbonne   (France)

Author keywords

Blockmodeling; Coclustering; Graph mining; Model selection

Indexed keywords

BLOCKMODELING; BUILD TIME; CO-CLUSTERING; DATA SETS; DISCRETIZATIONS; EDGE DISTRIBUTION; EVOLVING GRAPHS; EXPLORATORY DATA ANALYSIS; GRAPH MINING; MODEL SELECTION; NOVEL TECHNIQUES; TIME SEGMENTS; TRACK STRUCTURE;

DATA MINING;

EID: 84873153756     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2012.61     Document Type: Conference Paper

References (25)

1. E. Bott, Family and Social Network. Tavistock, 1957.
2. S. F. Nadel, The Theory of Social Structure. Cohen & West, 1957.
3. F. Lorrain and H. White, "Structural equivalence of individuals in social networks," Journal of Mathematical Sociology, vol. 1, no. 49-80, 1971.
4. D. R. White and K. P. Reitz, "Graph and semigroup homo-morphisms on networks of relations," Social Networks, vol. 5, no. 2, 1983.
5. P. Doreian, V. Batagelj, and A. Ferligoj, "Generalized block-modeling of two-mode network data," 2004.
6. H. White, S. Boorman, and R. Breiger, "Social structure from multiple networks: I. blockmodels of roles and positions," Am. J. of Sociology, vol. 81, no. 4, pp. 730-80, 1976.
7. J. Reichardt and D. R. White, "Role models for complex networks," The European Physical Journal B, vol. 60, 2007.
8. S. Wasserman and K. Faust, Social Network Analysis: Methods and Applications, ser. Structural analysis in the social sciences. Cambridge Univ. Press, 1994.
9. K. Nowicki and T. Snijders, "Estimation and prediction for stochastic blockstructures," Journal of the American Statistical Association, vol. 96, pp. 1077-1087, 2001.
10. C. Kemp and J. Tenenbaum, "Learning systems of concepts with an infinite relational model," in AAAI'06, 2006.
11. E. Airoldi, D. M. Blei, S. E. Fienberg, and E. P. Xing, "Mixed Membership Stochastic Blockmodels," JMLR, vol. 9, pp. 1981-2014, 2008.
12. J. Hopcroft, O. Khan, B. Kulis, and B. Selman, "Tracking evolving communities in large linked networks," PNAS, vol. 101, pp. 5249-5253, 2004.
13. E. P. Xing, W. Fu, and L. Song, "A state-space mixed membership blockmodel for dynamic network tomography," Annals of Applied Statistics, vol. 4, no. 2, pp. 535-566, 2010.
14. J. Sun, C. Faloutsos, S. Papadimitriou, and P. S. Yu, "Graphscope: parameter-free mining of large time-evolving graphs," ser. KDD '07, 2007, pp. 687-696.
15. P. Grünwald, The Minimum Description Length Principle. Mit Press, 2007.
16. K. J. Lang, "Information theoretic comparison of stochastic graph models: Some experiments," in WAW, 2009, pp. 1-12.
17. M. Boullé, Data grid models for preparation and modeling in supervised learning. Microtome, 2010.
18. E. Jaynes, Probability Theory: The Logic of Science. Cambridge Univ. Press, 2003.
19. S. P. Borgatti, "A comment on doreian's regular equivalence in symmetric structures," Social Networks, vol. 10, 1988.
20. C. E. Shannon, "A mathematical theory of communication," Bell system technical journal, vol. 27, 1948.
21. P. Hansen and N. Mladenovic, "Variable neighborhood search: Principles and applications," European Journal of Operational Research, vol. 130, no. 3, pp. 449-467, 2001.
22. J. Lin, "Divergence measures based on the shannon entropy," IEEE Transactions on Information theory, vol. 37, pp. 145-151, 1991.
23. I. S. Dhillon, S. Mallela, and D. Modha, "Information-theoretic co-clustering," in KDD '03, 2003, pp. 89-98.
24. T. M. Cover and J. A. Thomas, Elements of information theory (2. ed.). Wiley, 2006.
25. C. Robardet, "Constraint-based pattern mining in dynamic graphs," in ICDM'09, 2009, pp. 950-955.