Enhancing the effectiveness of clustering with spectra analysis

IEEE Transactions on Knowledge and Data Engineering

Volumn 19, Issue 7, 2007, Pages 887-902

  Li, Wenyuan ^b   Ng, Wee Keong ^a,c   Liu, Ying ^a,b   Ong, Kok Leong ^d  

^a IEEE

^b The University of Texas at Dallas   (United States)

^c NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^d DEAKIN UNIVERSITY   (Australia)

Author keywords

Clustering; Eigenvalues; Eigenvectors; Spectral methods

Indexed keywords

CLUSTERING; FUNDAMENTAL QUESTIONS; K-MEANS; SPECTRAL METHODS;

CLUSTERING ALGORITHMS; DATA REDUCTION; EIGENVALUES AND EIGENFUNCTIONS; PARAMETER ESTIMATION; PROBLEM SOLVING; SET THEORY;

SPECTRUM ANALYSIS;

EID: 34249827286     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2007.1066     Document Type: Article

References (43)

1. S. Salvador and P. Chan, "Determining the Number of Clusters/Segments in Hierarchical Clustering/Segmentation Algorithms," Technical Report 2003-18, Florida Inst. of Technology, 2003.
2. R. Tibshirani, G. Walther, and T. Hastie, "Estimating the Number of Clusters in a Dataset via the Gap Statistic," Technical Report 208, Dept. of Statistics, Stanford Univ., 2000.
3. A. Dempster et al. "Maximum Likelihood from Incomplete Data via the EM Algorithm," J. Royal Statistical Soc., vol. 39, pp. 1-38, 1977.
4. F. Evans et al. "Determining the Number of Clusters in a Mixture by Iterative Model Space Refinement with Application to Free-Swimming Fish Detection," Proc. Seventh Int'l Conf. Digital Imaging Computing: Techniques and Applications (DICTA '03), 2003.
5. Y. Yang, X. Guan, and J. You, "CLOPE: A Fast and Effective Clustering Algorithm for Transactional Data," Proc. Eighth ACM S1GKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD '02), pp. 682-687, 2002.
6. M.H. Arshad and P.K. Chan, "Identifying Outliers via Clustering for Anomaly Detection," Technical Report CS-2003-19, Florida Inst. of Technology, 2003.
7. E. Knorr and R. Ng, "Algorithms for Mining Distance-Based Outliers in Large Data set or Data Sets," Proc. 24th Int'l Conf. Very Large Data Bases (VLDB '98), pp. 392-403, 1998.
8. Z. Chen, A. Fu, and J. Tang, "On Complementarity of Cluster and Outlier Detection Schemes," Proc. Fifth Int'l Conf. Data Warehousing and Knowledge Discovery (DaWaK '03), 2003.
9. A.K. Jain, M.N. Murty, and P.J. Flynn, "Data Clustering: A Review," ACM Computing Surveys, vol. 31, no. 13, pp. 264-323, 1999.
10. G. Golub and C.V. Loan, Matrix Computations, third ed. Johns Hopkins Univ. Press, Nov. 1996.
11. F.R.K. Chung, Spectral Graph Theory, CBMS Regional Conf. Series in Math., no. 92. Am. Math. Soc, 1997.
12. S. Deerwester et al. "Indexing by Latent Semantic Analysis," J. Am. Soc. Information Science, vol. 41, no. 6, pp. 391-407, 1990.
13. M.P. Sinka and D.W. Corne, "A Large Benchmark Dataset for Web Document Clustering," Soft Computing Systems: Design, Management, and Applications, pp. 881-890, IOS Press, 2002.
14. A. Gordon, Classification, second ed. Chapman and Hall/CRC, 1999.
15. G. Karypis, "CLUTO: A Clustering Toolkit," Technical Report 02-017, Univ. of Minnesota, 2002.
16. M. Eisen et al. "Cluster Analysis and Display of Genome-Wide Expression Patterns," Proc. Nat'l Academy of Sciences USA, vol. 95, no. 25, pp. 14863-14868, Dec. 1998.
17. R. Sharan, M.-K. Adi, and R. Shamir, "CLICK and EXPANDER: A System for Clustering and Visualizing Gene Expression Data," Bioinformatics, vol. 19, pp. 1787-1799, 2003. [18] D. Ross et al. "Systematic Variation in Gene Expression Patterns in Human Cancer Cell Lines," Nature, vol. 24, pp. 227-235, 2000.
18. G. Karypis, E.-H. Han, and V. Kumar, "CHAMELEON: Hierarchical Clustering Using Dynamic Modeling," Computer, vol. 32, no. 8, pp. 68-75, Aug. 1999.
19. M. Halkidi et al. "On Clustering Validation Techniques," J. Intelligent Information Systems, vol. 17, nos. 2-3, pp. 107-145, 2001.
20. C. Fraley and A.E. Raftery, "How Many Clusters? Which Clustering Method? Answers via Model-Based Cluster Analysis," Computer J., vol. 41, no. 8, pp. 578-588, 1998.
21. H. Li, K. Zhang, and T. Jiang, "Minimum Entropy Clustering and Applications to Gene Expression Analysis," Proc. IEEE Computational Systems Bioinformatics Conf. (CSB '04), pp. 142-151, 2004.
22. B. Fischer et al. "Clustering with the Connectivity Kernel," Proc. Neural Information Processing Systems Conf. (NIPS '01), Advances in Neural Information Processing Systems, 2003.
23. Z. Füredi and J. Komlós, "The Eigenvalues of Random Symmetric Matrices," Combinatorica, vol. 1, no. 3, pp. 233-241, 1981.
24. R.B. Lehoucq, D.C. Sorensen, and C. Yang, ARPACK User's Guide: Solution of Large-Scale Eigenvalue Problems by Implicitly Restarted Arnoldi Methods. SIAM, 1998.
25. LANSO, Dept. of Computer Science and the Industrial Liaison Office, Univ. of Calif., Berkeley, 2005.
26. P. Berkhin, "Survey of Clustering Data Mining Techniques," technical report, Accrue Software, 2002.
27. N. Alon, "Eigenvalues and Expanders," Combinatorica, vol. 6, no. 2, pp. 83-96, 1986.
28. C. Ding et al. "A Min-Max Cut Algorithm for Graph Partitioning and Data Clustering," Proc. IEEE Int'l Conf. Data Mining (ICDM '01), 2001.
29. J. Shi and J. Malik, "Normalized Cuts and Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 888-905, Aug. 2000.
30. R. Kannan, S. Vempala, and A. Vetta, "On Clusterings: Good, Bad and Spectral," Proc. 41st Symp. Foundations of Computer Science (FOCS '00), pp. 367-377, 2000.
31. P. Smyth, "Clustering Using Monte Carlo Cross-Validation," Proc. Second ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD '96), pp. 126-133, 1996.
32. M. Hansen and B. Yu, "Model Selection and the Principle of Minimum Description Length," J. Am. Statistical Assoc, vol. 96, no. 454, pp. 746-774, 2001.
33. V. Roth, T. Lange, M. Braun, and J. Buhmann, "A Resampling Approach to Cluster Validation," Proc. 15th Symp. Computational Statistics (COMPSTAT '02), 2002.
34. R. Tibshirani, G. Walther, D. Botstein, and P. Brown, "Cluster Validation by Prediction Strength," technical report, Stanford Univ., 2001.
35. Y. Azar, A. Fiat, A. Karlin, F. McSherry, and J. Saia, "Spectral Analysis of Data," Proc. 33rd Ann. ACM Symp. Theory of Computing (STOC '01), pp. 619-626, 2001.
36. J.M. Kleinberg, "Authoritative Sources in a Hyperlinked Environment," J. ACM, vol. 46, no. 5, pp. 604-632, 1999.
37. A. Ng, M. Jordan, and Y. Weiss, "On Spectral Clustering: Analysis and an Algorithm," Proc. Neural Information Processing Systems Conf. (NIPS '01), Advances in Neural Information Processing Systems, pp. 849-856, 2001.
38. M. Belkin and P. Niyogi, "Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering," Proc. Neural Information Processing Systems Conf. (NIPS '01), Advances in Neural Information Processing Systems, 2001.
39. M. Meila and J. Shi, "A Random Walks View of Spectral Segmentation," Proc. Eighth Int'l Workshop Artificial Intelligence and Statistics, 2001.
40. I.S. Dhillon, "Co-Clustering Documents and Words Using Bipartite Spectral Graph Partitioning," Proc. Seventh ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD '01), 2001.
41. D. Boley, "Principal Direction Divisive Partitioning," Data Mining and Knowledge Discovery, vol. 2, no. 4, pp. 325-344, 1998.
42. D. Vukadinovic, P. Huan, and T. Erlebach, "A Spectral Analysis of the Internet Topology," Technical Report ETH TIK-NR 118, 2001.
43. A.J. Seary and W.D. Richards, "Spectral Methods for Analyzing and Visualizing Networks: An Introduction," Dynamic Social Network Modeling and Analysis, pp. 209-228, NatT Academy Press, 2003.