Graph nodes clustering based on the commute-time kernel

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4426 LNAI, Issue , 2007, Pages 1037-1045

  Yen, Luh ^a   Fouss, Francois ^a   Decaestecker, Christine ^b   Francq, Pascal ^b   Saerens, Marco ^a  

^a UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^b UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

FUZZY CLUSTERING; GRAPH THEORY; MATRIX ALGEBRA; PROBLEM SOLVING;

GRAPH NODES; KERNEL CLUSTERING;

CLUSTERING ALGORITHMS;

EID: 38049162603     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71701-0_117     Document Type: Conference Paper

References (23)

1. M. W. Berry, editor. Survey of Text Mining. Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2003.
2. I. S. Dhillon, Y. Guan, and B. Kulis. Kernel k-means, spectral clustering and normalized cuts. In Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining, pages 551-556. ACM Press, 2004.
3. I. S. Dhillon and D. S. Modha. Concept decompositions for large sparse text data using clustering. Machine Learning, 42(1):143-175, 2001.
4. C. Ding and X. He. Linearized cluster assignment via spectral ordering. In ICML '04'- Proceedings of the twenty-first international conference on Machine learning, page 30, New York, NY, USA, 2004. ACM Press.
5. P. Drineas, A. Frieze, R. Kannan, S. Vempala, and V. Vinay. Clustering large graphs via the singular value decomposition. Machine Learning, 56(1-3):9-33, 2004.
6. B. S. Everitt, S. Landau, and M. Leese. Cluster Analysis. Arnold Publishers, 2001.
7. G. W. Flake, R. E. Tarjan, and K. Tsioutsiouliklis. Graph clustering and minimum cut trees. Internet Math, 1(4):385-408, 2003.
8. F. Fouss, A. Pirotte, J.-M. Renders, and M. Saerens. Random-walk computation of similarities between nodes of a graph, with application to collaborative recommendation. IEEE Transactions on Knowledge and Data Engineering, 19(3):355-369. 2007.
9. M. Girolami. Mercer kernel-based clustering in feature space. IEEE Transactions on Neural Networks, 13(3):780-784, May 2002.
10. D.-W. Kim, K. Y. Lee, D. Lee, and K. H. Lee. Evaluation of the performance of clustering algorithms in kernel-induced feature space. Pattern Recognition, 38(4):607-611, 2005.
11. M. Newman. Detecting community structure in networks. The European Physical Journal B, 38:321-330, 2004.
12. A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In T. Dietterich, S. Becker, and Z. Ghahramani, editors, Advances in Neural Information Processiong Systems, volume 14, pages 849-856, Vancouver, Canada, 2001. MIT Press.
13. M. F. Porter. An algorithm for suffix stripping. Program, 14(3):130-137, 1980.
14. M. Saerens, F. Fouss, L. Yen, and P. Dupont. The principal components analysis of a graph, and its relationships to spectral clustering. Proceedings of the 15th European Conference on Machine Learning (ECML 2004). Lecture Notes in Artificial Intelligence, Vol. 3201, Springer-Verlag, Berlin, pages 371-383, 2004.
15. B. Scholkopf and A. Smola. Learning with kernels. The MIT Press, 2002.
16. J. Shawe-Taylor and N. Cristianini. Kernel Methods for Pattern Analysis. Cambridge University Press, 2004.
17. S. van Dongen. Graph Clustering by Flow Simulation. PhD thesis, University of Utrecht, 2000.
18. S. Weiss, N, Indurkhya, T. Zhang, and F. Damerau. Text Mining: Predictive Methods for Analyzing Unstructured Information. Springer, 2004.
19. S. White and P. Smyth. A spectral clustering approach to finding communities in graph. In SDM, 2005.
20. Z.-D. Wu, W.-X. Xie, and J.-P. Yu. Fuzzy c-means clustering algorithm based on kernel method. In ICCIMA '03: Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications, page 49, Washington, DC, USA, 2003. IEEE Computer Society.
21. H. Zha, X. He, C. H. Q. Ding, M. Gu, and H. D. Simon. Bipartite graph partitioning and data clustering. In Proc. of ACM 10th Int'l Conf. Information and Knowledge Management (CIKM 2001), pages 25-32, 2001.
22. D.-Q. Zhang and S.-C. Chen. Fuzzy clustering using kernel method. In Proceedings of the 2002 International Conference on Control and Automation, 2002. ICCA, pages 162-163, 2002.
23. D.-Q. Zhang and S.-C. Chen. A novel kernelized fuzzy c-means algorithm with application in medical image segmentation. Artificial Intelligence in Medicine, 32(1):37-50, 2004.