Tell me what I need to know: Succinctly summarizing data with itemsets

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2011, Pages 573-581

  Mampaey, Michael ^a   Tatti, Nikolaj ^a   Vreeken, Jilles ^a  

^a UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

Algorithms; Experimentation; Theory

Indexed keywords

DATA MINING;

BAYESIAN INFORMATION CRITERION; CURRENT MODELING; EXPERIMENTATION; ITEMSET; ITERATIVE PROCESS; MAXIMUM ENTROPY MODELS; NON-REDUNDANT; PROBABILISTICS; SYNTHETIC DATA; THEORY;

ITERATIVE METHODS;

EID: 80052675183     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2020408.2020499     Document Type: Conference Paper

References (33)

1. C. C. Aggarwal and P. S. Yu. A new framework for itemset generation. In Proc. PODS'98, pages 18-24, 1998.
2. S. Brin, R. Motwani, and C. Silverstein. Beyond market baskets: Generalizing association rules to correlations. In Proc. ACM SIGMOD'97, pages 265-276, 1997. (Pubitemid 127456791)
3. T. Calders and B. Goethals. Non-derivable itemset mining. Data Min. Knowl. Disc., 14(1):171-206, 2007. (Pubitemid 46345359)
4. I. Csiszár. I-divergence geometry of probability distributions and minimization problems. The Annals of Probability, 3(1):146-158, Feb. 1975.
5. J. Darroch and D. Ratcliff. Generalized iterative scaling for log-linear models. The Annals of Mathematical Statistics, 43(5):1470-1480, 1972.
6. A. Frank and A. Asuncion. UCI machine learning repository. http://archive.ics.uci.edu/ml, 2010.
7. A. Gallo, N. Cristianini, and T. De Bie. MINI: Mining informative non-redundant itemsets. In Proc. PKDD'07, pages 438-445, 2007.
8. G. C. Garriga, E. Junttila, and H. Mannila. Banded structure in binary matrices. In Proc. ACM SIGKDD'08, pages 292-300, 2008.
9. F. Geerts, B. Goethals, and T. Mielikäinen. Tiling databases. In Proc. DS'04, pages 278-289, 2004. (Pubitemid 39745469)
10. A. Gionis, H. Mannila, T. Mielikäinen, and P. Tsaparas. Assessing data mining results via swap randomization. Trans. Knowl. Disc. Data, 1(3), 2007.
11. B. Goethals and M. Zaki. Frequent itemset mining dataset repository. http://fimi.ua.ac.be/.
12. P. D. Grünwald. The Minimum Description Length Principle. MIT Press, 2007.
13. S. Hanhijärvi, M. Ojala, N. Vuokko, K. Puolamäki, N. Tatti, and H. Mannila. Tell me something I don't know: randomization strategies for iterative data mining. In Proc. ACM SIGKDD'09, pages 379-388, 2009.
14. S. Jaroszewicz and D. A. Simovici. Interestingness of frequent itemsets using bayesian networks as background knowledge. In Proc. ACM SIGKDD'04, pages 178-186, 2004. (Pubitemid 40114927)
15. K.-N. Kontonasios and T. De Bie. An information-theoretic approach to finding noisy tiles in binary databases. In Proc. SDM'10, pages 153-164, 2010.
16. M. Mampaey and J. Vreeken. Summarising data by clustering items. In Proc. ECML PKDD'10, pages 321-336, 2010.
17. A. Mitchell-Jones, G. Amori, W. Bogdanowicz, B. Krystufek, P. H. Reijnders, F. Spitzenberger, M. Stubbe, J. Thissen, V. Vohralik, and J. Zima. The Atlas of European Mammals. Academic Press, 1999.
18. T. Mitchell-Jones. Societas europaea mammalogica. http://www.european- mammals.org.
19. S. Myllykangas, J. Himberg, T. Böhling, B. Nagy, J. Hollmén, and S. Knuutila. DNA copy number amplification profiling of human neoplasms. Oncogene, 25(55):7324-7332, 2006. (Pubitemid 44809098)
20. S. Nijssen, T. Guns, and L. De Raedt. Correlated itemset mining in ROC space: a constraint programming approach. In Proc. ACM SIGKDD'09, pages 647-656, 2009.
21. N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal. Discovering frequent closed itemsets for association rules. In Proc. ICDT'99, pages 398-416, 1999.
22. G. Schwarz. Estimating the dimension of a model. Annals of Statistics, 6(2):461-464, 1978.
23. A. Siebes, J. Vreeken, and M. van Leeuwen. Item sets that compress. In Proc. SDM'06, pages 393-404, 2006.
24. P. Tan, V. Kumar, and J. Srivastava. Selecting the right interestingness measure for association patterns. In Proc. ACM SIGKDD'02, pages 32-41. ACM, 2002.
25. N. Tatti. Computational complexity of queries based on itemsets. Inf. Proc. Letters, pages 183-187, 2006.
26. N. Tatti. Maximum entropy based significance of itemsets. Knowl. Inf. Sys., 17(1):57-77, 2008.
27. N. Tatti. Probably the best itemsets. In Proc. ACM SIGKDD'10, pages 293-302. ACM, 2010.
28. N. Tatti and H. Heikinheimo. Decomposable families of itemsets. In Proc. ECMLPKDD'08, pages 472-487, 2008.
29. N. Tatti and M. Mampaey. Using background knowledge to rank itemsets. Data Min. Knowl. Disc., 21(2):293-309, 2010.
30. C. Wang and S. Parthasarathy. Summarizing itemset patterns using probabilistic models. In Proc. ACM SIGKDD'06, pages 730-735, 2006. (Pubitemid 44535582)
31. G. I. Webb. Self-sufficient itemsets: An approach to screening potentially interesting associations between items. Trans. Knowl. Disc. Data, 4(1), 2010.
32. X. Yan, H. Cheng, J. Han, and D. Xin. Summarizing itemset patterns: a profile-based approach. In Proc. ACM SIGKDD'05, pages 314-323, 2005. (Pubitemid 43218293)
33. M. J. Zaki and N. Ramakrishnan. Reasoning about sets using redescription mining. In Proc. ACM SIGKDD'05, pages 364-373, New York, NY, USA, 2005. ACM Press. (Pubitemid 43218298)