Compression, clustering, and pattern discovery in very high-dimensional discrete-attribute data sets

IEEE Transactions on Knowledge and Data Engineering

Volumn 17, Issue 4, 2005, Pages 447-461

  Koyutürk, Mehmet ^a   Grama, Ananth ^a   Ramakrishnan, Naren ^b  

^a Purdue University   (United States)

^b VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

Author keywords

Association rules; Classification; Clustering; Data mining; Singular value decomposition; Sparse; Structured and very large systems

Indexed keywords

ASSOCIATION RULES; CLASSIFICATION; CLUSTERING; SINGULAR VALUE DECOMPOSITION; SPARSE; STRUCTURED AND VERY LARGE SYSTEMS;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATA COMPRESSION; DATA MINING; DATA REDUCTION; LARGE SCALE SYSTEMS; PARAMETER ESTIMATION; PATTERN MATCHING; SEMANTICS;

DATA STRUCTURES;

EID: 17044371964     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2005.55     Document Type: Article

References (29)

1. R. Agrawal and R. Srikant, "Fast Algorithms for Mining Association Rules," Proc. 20th Int'l Conf. Very Large Data Bases (VLDB '94), pp. 487-499, 1994.
2. G.H. John and P. Langley, "Static versus Dynamic Sampling for Data Mining," Proc. Second Int'l Conf. Knowledge Discovery and Data Mining (KDD '96), pp. 367-370, 1996.
3. F.J. Provost, D. Jensen, and T. Gates, "Efficient Progressive Sampling," Knowledge Discovery and Data Mining, pp. 23-32, 1999.
4. F.J. Provost and V. Kolluri, "A Survey of Methods for Scaling Up Inductive Algorithms," Data Mining and Knowledge Discovery, vol. 3, no. 2, pp. 131-169, 1999.
5. H. Toivonen, "Sampling Large Databases for Association Rules," Proc. 22th Int'l Conf. Very Large Databases (VLDB '96), pp. 134-145, 1996.
6. M.J. Zaki, S. Parthasarathy, W. Li, and M. Ogihara, "Evaluation of Sampling for Data Mining of Association Rules," Proc. Seventh Int'l Workshop Research Issues Data Eng. (RIDE '97), p. 42, 1997.
7. M.W. Berry, S.T. Dumais, and G.W. O'Brien, "Using Linear Algebra for Intelligent Information Retrieval," SIAM Rev., vol. 37, no. 4, pp. 573-595, 1995.
8. T.G. Kolda and D.P. O'Leary, "Computation and Uses of the Semidiscrete Matrix Decomposition," ACM Trans. Information Processing, 1999.
9. M.T. Chu and R.E. Funderlic, "The Centroid Decomposition: Relationships between Discrete Variational Decompositions and SVDs," SIAM J. Matrix Analysis and Applications, vol. 23, no. 4, pp. 1025-1044, 2002.
10. D. Boley, "Principal Direction Divisive Partitioning," Data Mining and Knowledge Discovery, vol. 2, no. 4, pp. 325-344, 1998.
11. I.T Joliffe, Principal Component Analysis. Springer-Verlag, 1986.
12. H.H. Harman, Modern Factor Analysis. Univ. of Chicago Press, 1967.
13. T. Hofmann, "Probabilistic Latent Semantic Analysis," Proc. 15th Conf. Uncertainty in Artificial Intelligence (UAI '99), 1999.
14. A.P. Dempster, N.M. Laird, and D.B. Rubin, "Maximum Likelihood from Incomplete Data via the EM Algorithm," J. Royal Statistical Soc. Series B (Methodological), vol. 39, no. 1, pp. 1-38, 1977.
15. A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis. John Wiley & Sons, 2001.
16. R.M. Gray, "Vector Quantization," IEEE ASSP Magazine, vol. 1, no. 2, pp. 4-29, 1984.
17. J. MacQueen, "Some Methods for Classification and Analysis of Multivariate Observations," Proc. Fifth Berkeley Symp., vol. 1, pp. 281-297, 1967.
18. Z. Huang, "A Fast Clustering Algorithm to Cluster Very Large Categorical Data Sets in Data Mining," Proc. SIGMOD Workshop Research Issues Data Mining and Knowledge Discovery, 1997.
19. D. Gibson, J. Kleingberg, and P. Raghavan, "Clustering Categorical Data: An Approach Based on Dynamical Systems," The VLDB J., vol. 8, nos. 3-4, pp. 222-236, 2000.
20. S. Guha, R. Rastogi, and K. Shim, "ROCK: A Robust Clustering Algorithm for Categorical Attributes," Information Systems, vol. 25, no. 5, pp. 345-366, 2000.
21. E.H. Han, G. Karypis, V. Kumar, and B. Mobasher, "Hypergraph-Based Clustering in High-Dimensional Data Sets: A Summary of Results," Bull. IEE Technical Comm. Data Eng., vol. 21, no. 1, pp. 15-22, 1998.
22. M. Özdal and C. Aykanat, "Hypergraph Models and Algorithms for Data-Pattern Based Clustering," Data Mining and Knowledge Discovery, vol. 9, no. 1, pp. 29-57, 2004.
23. M. Koyutürk, A. Grama, and N. Ramakrishnan, "Algebraic Techniques for Analysis of Large Discrete-Valued Data Sets," Proc. Sixth European Conf. Principles of Data Mining and Knowledge Discovery (PKDD '02), pp. 311-324, 2002.
24. C. Bron and J. Kerbosch, "Finding All Cliques in an Undirected Graph," Comm. ACM, vol. 16, pp. 575-577, 1973.
25. R. Peeters, "The Maximum Edge Biclique Problem is NP-Complete," Discrete Applied Math., vol. 131, no. 3, pp. 651-654, 2003.
26. G. Karypis and V. Kumar, "A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs," SIAM J. Scientific Computing, vol. 20, no. 1, pp. 359-392, 1998.
27. J. Chi, M. Koyutürk, and A. Grama, "Conquest: A Distributed Tool for Constructing Summaries of High-Dimensional Discrete-Attributed Data Sets," Proc. Fourth SIAM Int'l Conf. Data Mining (SDM '04), pp. 154-165, 2004.
28. C. Borgelt and R. Kruse, "Induction of Association Rules: Apriori Implementation," Proc. 15th Conf. Computational Statistics, 2002.
29. M. Koyutürk and A. Grama, "Proximus: A Framework for Analyzing Very High Dimensional Discrete-Attributed Data Sets," Proc. Ninth ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD '03), pp. 147-156, 2003.