Mining non-derivable association rules

Proceedings of the 2005 SIAM International Conference on Data Mining, SDM 2005

Volumn , Issue , 2005, Pages 239-249

  Goethals, Bart ^a,b   Muhonen, Juho ^a   Toivonen, Hannu ^a  

^a UNIVERSITY OF HELSINKI   (Finland)

^b UNIVERSITY OF ANTWERP   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULES;

ABSOLUTE BOUNDS; BOUNDED CONFIDENCES; INFERENCE SYSTEMS; LOWER AND UPPER BOUNDS; PERCENTAGE POINTS; POINT ESTIMATE; PRUNING STRATEGY; REDUNDANT RULES;

DATA MINING;

EID: 84880091428     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972757.22     Document Type: Conference Paper

References (14)

1. Rakesh Agrawal, Tomasz Imielinski, and Arun Swami. Database mining: A performance perspective. IEEE Transactions on Knowledge and Data Engineering, 5(6):914 - 925, December 1993. Special Issue on Learning and Discovery in Knowledge-Based Databases.
2. J-F. Boulicaut, A. Bykowski, and C. Rigotti. Approximation of frequency queries by means of free-sets. In The Fourth European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'00), pages 75-85, Lyon, France, 2000. Springer.
3. Yves Bastide, Nicolas Pasquier, Rafik Taouil, Gerd Stumme, and Lotfi Lakhal. Mining minimal non-redundant association rules using frequent closed itemsets. In Computational Logic - CL 2000: First International Conference, pages 972 - 986, London, UK, 2000.
4. T. Calders and B. Goethals. Mining all non-derivable frequent itemsets. In T. Elomaa, H. Mannila, and H. Toivo-nen, editors, Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery, volume 2431 of Lecture Notes in Computer Science, pages 74-85. Springer, 2002.
5. J. Galambos and I. Simonelli. Bonferroni-type Inequalities with Applications. Springer, 2000.
6. B. Goethals and J. Van den Bussche. On supporting interactive association rule mining. In Y. Kambayashi, M.K. Mohania, and A.M. Tjoa, editors, Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery, volume 1874 of Lecture Notes in Computer Science, pages 307-316. Springer, 2000.
7. S. Jaroszewicz and D. A. Simovici. Pruning redundant association rules using maximum entropy principle. In Advances in Knowledge Discovery and Data Mining, 6th Pacific-Asia Conference, PAKDD'02, pages 135-147, Taipei, Taiwan, May 2002.
8. Mika Klemettinen, Heikki Mannila, Pirjo Ronkainen, Hannu Toivonen, and A. Inkeri Verkamo. Finding interesting rules from large sets of discovered association rules. In Proceedings of the Third International Conference on Information and Knowledge Management (CIKM'94), pages 401 - 407, Gaithersburg, MD, USA, November 1994. ACM.
9. Guichong Li and Howard J. Hamilton. Basic association rules. In Fourth SIAM International Conference on Data Mining, Florida, USA, 2004.
10. Heikki Mannila, Dmitry Pavlov, and Padhraic Smyth. Prediction with local patterns using cross-entropy. In Proceedings of the ACM SIGKDD, pages 357-361. ACM Press, 1999.
11. R.T. Ng, L.V.S. Lakshmanan, J. Han, and A. Pang. Exploratory mining and pruning optimizations of constrained association rules. In L.M. Haas and A. Tiwary, editors, Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data, volume 27(2) of SIGMOD Record, pages 13-24. ACM Press, 1998.
12. N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal. Discovering frequent closed itemsets for association rules. In Proceedings of the 7th International Conference on Database Theory, volume 1540 of Lecture Notes in Computer Science, pages 398-416. Springer, 1999.
13. Mohammed J. Zaki. Generating non-redundant association rules. In Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 34 - 43, Boston, MA, USA, 2000.
14. Mohammed Zaki and Benjarath Phoophakdee. MIRAGE: A framework for mining, exploring and visualizing minimal association rules. Technical Report RPI CS Dept Technical Report 03-04, Department of Computer Science, Rensselaer Polytechnic Institute, Troy, New York, July 2003.