Hierarchical taxonomy preparation for text categorization using consistent bipartite spectral graph copartitioning

IEEE Transactions on Knowledge and Data Engineering

Volumn 17, Issue 9, 2005, Pages 1263-1273

  Gao, Bin ^b,c   Liu, Tie Yan ^a,c   Feng, Guang ^b,d   Qin, Tao ^b,d   Cheng, Qian Sheng ^b   Ma, Wei Ying ^a,c  

^a IEEE

^b PEKING UNIVERSITY   (China)

^c MICROSOFT RESEARCH ASIA   (China)

^d TSINGHUA UNIVERSITY   (China)

Author keywords

Clustering; Data mining; Singular value decomposition; Text processing

Indexed keywords

CLUSTER ANALYSIS; DATA MINING; HIERARCHICAL SYSTEMS; SCALABILITY; SINGULAR VALUE DECOMPOSITION; TAXONOMIES;

SPECTRAL GRAPH COPARTITIONING; TAXONOMY PREPARATION; TEXT CATEGORIZATION;

TEXT PROCESSING;

EID: 32344442862     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2005.147     Document Type: Article

References (25)

1. R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. ACM Press, 1999.
2. I.S. Dhillon, "Coclustering Documents and Words Using Bipartite Spectral Graph Partitioning," Proc. SIGKDD '01, 2001.
3. I.S. Dhillon, S. Mallela, and D.S. Modha, "Information-Theoretic Co-Clustering," Proc. SIGKDD '03, pp. 89-98, 2003.
4. C. Ding, X. He, H. Zha, M. Gu, and H. Simon, "A Min-Max Cut Algorithm for Graph Partitioning and Data Clustering," Proc. IEEE Int'l Conf. Data Mining, 2001.
5. R.O. Duda, P.E. Hart, and D.G. Stork, Pattern Classification, second ed. John Wiley & Sons Inc., 2001.
6. S.T. Dumais and H. Chen, "Hierarchical Classification of Web Content," Proc. SIGIR '00, 2000.
7. C. Elkan, "Using the Triangle Inequality to Accelerate k-Means," Proc. Int'l Conf. Machine Learning, 2003.
8. S. Godbole, "Exploiting Confusion Matrices for Automatic Generation of Topic Hierarchies and Scaling Up Multi-Way Classifiers," technical report, IIT Bombay, 2002.
9. S. Godbole, S. Sarawagi, and S. Chakrabarti, "Scaling Multi-Class Support Vector Machines Using Inter-Class Confusion," Proc. SIGKDD '02, 2002.
10. G.H. Golub and C.F.V. Loan, Matrix Computations, third ed. Johns Hopkins Univ. Press, 1996.
11. L. Hagen and A.B. Kahng, "New Spectral Methods for Ratio Cut Partitioning and Clustering," IEEE Trans. Computer Aided Design, vol. 11, pp. 1074-1085, 1992.
12. G. Hamerly and C. Elkan, "Learning the k in k-Means," Proc. Neural Information Processing Systems Conf., 2003.
13. K. Kummamuru, A. Dhawale, and R. Krishnapuram, "Fuzzy Co-Clustering of Documents and Keywords," Proc. IEEE Int'l Conf. Fuzzy Systems, pp. 772-777, 2003.
14. D.D. Lewis, "Evaluating Text Categorization," Proc. Speech and Natural Language Workshop, 1991.
15. D.D Lewis, Y. Yang, T. Rose, and F. Li, "RCV1: A New Benchmark Collection for Text Classification Research," J. Machine Learning Research, vol. 5, pp. 361-397, 2004.
16. T. Liu, Y. Yang, H. Wan, Q. Zhou, B. Gao, H. Zeng, Z. Chen, and W. Ma, "An Experimental Study on Large-Scale Web Categorization," Proc. Int'l World Wide Web Conf., 2005.
17. M. Meila and L. Xu, "Multiway Cuts and Spectral Clustering," http://www.stat.washington.edu/mmp/, 2004.
18. F. Sebastiani, "Machine Learning in Automated Text Categorization," ACM Computing Surveys (CSUR), vol. 34, no. 1, pp. 1-47, 2002.
19. J. Shi and J. Malik, "Normalized Cuts and Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, pp. 888-905, 2000.
20. G.W. Stewart and J.G. Sun, Matrix Perturbation Theory. Academic Press, 1990.
21. V.N. Vapnik, The Nature of Statistical Learning Theory. Springer Verlag, 1995.
22. V. Vural and J.G Dy, "A Hierarchical Method for Multi-Class Support Vector Machines," Proc. Int'l Conf. Machine Learning, 2004.
23. J. Wang, H. Zeng, Z. Chen, H. Lu, L. Tao, and W. Ma, "ReCoM: Reinforcement Clustering of Multi-Type Interrelated Data Objects," Proc. SICIR '03, 2003.
24. Y. Yang, "A Scalability Analysis of Classifiers in Text Classification," Proc. SIGIR. '03, 2003.
25. H. Zha, C. Ding, and M. Gu, "Bipartite Graph Partitioning and Data Clustering," Proc. Conf. Information and Knowledge Management, 2001.