Low-entropy set selection

Society for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics

Volumn 2, Issue , 2009, Pages 565-576

  Heikinheimo, Hannes ^a   Siebes, Arno ^b   Vreeken, Jilles ^b   Mannila, Heikki ^c  

^a HELSINKI INSTITUTE FOR INFORMATION TECHNOLOGY   (Finland)

^b UTRECHT UNIVERSITY   (Netherlands)

^c UNIVERSITY OF HELSINKI   (Finland)

Author keywords

Dense data; Low entropy sets; Maximum likelihood principle; MDL; Pattern subset selection

Indexed keywords

DATA DESCRIPTION; DATA MINING; ENTROPY; MAXIMUM LIKELIHOOD;

DENSE DATUM; HIGH COMPRESSION RATIO; INFORMATIVE PATTERNS; LOW ENTROPY; MAXIMUM LIKELIHOOD PRINCIPLE; PATTERN DISCOVERY; STRONG INTERACTION; SUBSET SELECTION;

DATA COMPRESSION RATIO;

EID: 72749095588     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. I. Verkamo. Fast discovery of association rules. In Advances in Knowledge Discovery and Data Mining, pages 307-328. AAAI, 1996.
2. R. J. Bayardo. Efficiently mining long patterns from databases. In ACM SlGMOD Conference on Management of Data, pages 85-93, 1998.
3. B. Bringmann and A. Zimmermann. The chosen few: On identifying valuable patterns. In IEEE International Conference on Data Mining, pages 63-72, 2007.
4. T. Calders and B. Goethals. Mining all non-derivable frequent itemsets. In Proceedings of the 6th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, pages 74-85, 2002.
5. F. Coenen. The LUCS-KDD discretised/normalised ARM and CARM data library. 2003.
6. C. Faloutsos and V. Megalooikonomou. On data mining, compression and kolmogorov complexity. In Data Mining and Knowledge Discovery, volume 15, pages 3-20. Springer, 2007.
7. M. R. Garey and D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman, 1979.
8. A. Gionis, H. Mannila, T. Mielikäinen, and P. Tsaparas. Assessing data mining results via swap randomization. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 167-176, 2006.
9. P. D. Grünwald. Minimum description length tutorial. In P. Grünwald and I. Myung, editors, Advances in Minimum Description Length. MIT Press, 2005.
10. H. Heikinheimo, E. Hinkkanen, H. Mannila, T. Mielikäinen, and J. K. Seppänen. Finding low-entropy sets and trees from binary data. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 350-359, 2007.
11. Y. Ke, J. Cheng, and W. Ng. Mining quantitative correlated patterns using an information-theoretic approach. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 227-236, 2006.
12. A. J. Knobbe and E. K. Y. Ho. Maximally informative k-itemsets and their efficient discovery. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 237-244, 2006.
13. A. J. Knobbe and E. K. Y. Ho. Pattern teams. In European Conference on Principles and Practice of Knowledge Discovery in Databases, pages 577-584, 2006.
14. J. MacQueen. Some methods for classification and analysis of multivariate observations. In Proceedings of the 5th Symposium on Mathematical Statistics and Probability, 1967.
15. T. Mielikäinen and H. Mannila. The pattern ordering problem. In European Conference on Principles and Practice of Knowledge Discovery in Databases, pages 327-338, 2003.
16. A. J. Mitchell-Jones, G. Amori, W. Bogdanowicz, B. Krystufek, P. J. H. Reijnders, F. Spitzenberger, M. Stubbe, J. B. M. Thissen, V. Vohralik, and J. Zima. The Atlas of European Mammals. Academic Press, 1999.
17. S. Morishita and J. Sese. Traversing itemset lattice with statistical metric pruning. In PODS, pages 226-236, 2000.
18. N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal. Discovering frequent closed itemsets for association rules. Lecture Notes in Computer Science, 1540:398-416, 1999.
19. A. Siebes, J. Vreeken, and M. van Leeuwen. Item sets that compress. In SIAM Conference on Data Mining, pages 393-404, 2006.
20. X. Yan, H. Cheng, J. Han, and D. Xin. Summarizing itemset patterns: A profile-based approach. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 314-323, 2005.