Constraint-based discovery and inductive queries: Application to association rule mining

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2447, Issue , 2002, Pages 110-124

  Jeudy, Baptiste ^a   Boulicaut, Jean François ^a  

^a UNIVERSITÉ DE LYON   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULES; QUERY LANGUAGES;

CLOSED ITEMSETS; CONDENSED REPRESENTATIONS; CONSTRAINT-BASED; DESCRIPTIVE RULES; EVALUATION SCHEME; INDUCTIVE DATABASE; POST PROCESSING; PRELIMINARY APPROACH;

PATTERN RECOGNITION;

EID: 84937690392     PISSN: 03029743     EISSN: 16113349     Source Type: Journal    
DOI: 10.1007/3-540-45728-3_9     Document Type: Article

References (31)

1. R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In Proceedings SIGMOD'93, pages 207-216, Washington, USA, 1993. ACM Press.
2. 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 Press, 1996.
3. Y. Bastide, N. Pasquier, R. Taouil, G. Stumme, and L. Lakhal. Mining minimal non-redundant association rules using frequent closed itemsets. In Proceedings CL 2000, volume 1861 of LNCS, pages 972-986, London, UK, 2000. Springer-Verlag.
4. Y. Bastide, R. Taouil, N. Pasquier, G. Stumme, and L. Lakhal. Mining frequent patterns with counting inference. SIGKDD Explorations, 2(2):66-75, Dec. 2000.
5. M. Botta, J.-F. Boulicaut, C. Masson, and R. Meo. A comparison between query languages for the extraction of association rules. In Proceedings DaWaK'02, Aix en Provence, F, 2002. Springer-Verlag. To appear.
6. J.-F. Boulicaut and A. Bykowski. Frequent closures as a concise representation for binary data mining. In Proceedings PAKDD'00, volume 1805 of LNAI, pages 62-73, Kyoto, JP, 2000. Springer-Verlag.
7. J.-F. Boulicaut, A. Bykowski, and B. Jeudy. Towards the tractable discovery of association rules with negations. In Proceedings FQAS'00, Advances in Soft Computing series, pages 425-434, Warsaw, PL, Oct. 2000. Springer-Verlag.
8. J.-F. Boulicaut, A. Bykowski, and C. Rigotti. Approximation of frequency queries by means of free-sets. In Proceedings PKDD'00, volume 1910 of LNAI, pages 75-85, Lyon, F, 2000. Springer-Verlag.
9. J.-F. Boulicaut and B. Jeudy. Using constraint for itemset mining: should we prune or not? In Proceedings BDA'00, pages 221-237, Blois, F, 2000.
10. J.-F. Boulicaut, M. Klemettinen, and H. Mannila. Modeling KDD processes within the inductive database framework. In Proceedings DaWaK'99, volume 1676 of LNCS, pages 293-302, Florence, I, 1999. Springer-Verlag.
11. A. Bykowski and C. Rigotti. A condensed representation to find frequent patterns. In Proceedings PODS'01, pages 267-273, Santa Barbara, USA, 2001. ACM Press.
12. M. M. Garofalakis, R. Rastogi, and K. Shim. SPIRIT: Sequential pattern mining with regular expression constraints. In Proceedings VLDB'99, pages 223-234, Edinburgh, UK, 1999. Morgan Kaufmann.
13. B. Goethals and J. van den Bussche. On implementing interactive association rule mining. In Proceedings of the ACM SIGMOD Workshop DMKD'99, Philadelphia, USA, 1999.
14. J. Han and M. Kamber. Data Mining: Concepts and techniques. Morgan Kaufmann Publishers, San Francisco, USA, 2000. 533 pages.
15. T. Imielinski and H. Mannila. A database perspective on knowledge discovery. Communications of the ACM, 39(11):58-64, 1996.
16. T. Imielinski and A. Virmani. MSQL: A query language for database mining. Data Mining and Knowledge Discovery, 3(4):373-408, 1999.
17. B. Jeudy and J.-F. Boulicaut. Optimization of association rule mining queries. Intelligent Data Analysis, 6(5), 2002. To appear.
18. B. Jeudy and J.-F. Boulicaut. Using condensed representations for interactive association rule mining. In Proceedings PKDD'02, Helsinki, FIN, 2002. Springer- Verlag. To appear.
19. M. Kryszkiewicz. Concise representations of association rules. In Proceedings of the ESF Exploratory Workshop on Pattern Detection and Discovery, London, UK, 2002. Springer-Verlag. To appear in this volume.
20. H. Mannila and P. Smyth. Approximate query answering with frequent sets and maximum entropy. In Proceedings ICDE'00, page 309, San Diego, USA, 2000. IEEE Computer Press.
21. H. Mannila and H. Toivonen. Multiple uses of frequent sets and condensed representations. In Proceedings KDD'96, pages 189-194, Portland, USA, 1996. AAAI Press.
22. H. Mannila and H. Toivonen. Levelwise search and borders of theories in knowledge discovery. Data Mining and Knowledge Discovery, 1(3):241-258, 1997.
23. R. Meo, G. Psaila, and S. Ceri. An extension to SQL for mining association rules. Data Mining and Knowledge Discovery, 2(2):195-224, 1998.
24. P. Moen. Attribute, Event Sequence, and Event Type Similarity Notions for Data Mining. PhD thesis, Department of Computer Science, P.O. Box 26, FIN-00014 University of Helsinki, Jan. 2000.
25. B. Nag, P. M. Deshpande, and D. J. DeWitt. Using a knowledge cache for interactive discovery of association rules. In Proceedings SIGKDD'99, pages 244-253. ACM Press, 1999.
26. R. Ng, L. V. Lakshmanan, J. Han, and A. Pang. Exploratory mining and pruning optimizations of constrained associations rules. In Proceedings SIGMOD'98, pages 13-24, Seattle, USA, 1998. ACM Press.
27. N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal. Efficient mining of association rules using closed itemset lattices. Information Systems, 24(1):25-46, 1999.
28. J. Pei, J. Han, and R. Mao. CLOSET an efficient algorithm for mining frequent closed itemsets. In Proceedings of the ACM SIGMOD Workshop DMKD'00, pages 21-30, Dallas, USA, 2000.
29. P. Smyth and R. M. Goodman. An information theoretic approach to rule induction from databases. IEEE Transactions on Knowledge and Data Engineering, 4(4):301- 316, 1992.
30. R. Srikant, Q. Vu, and R. Agrawal. Mining association rules with item constraints. In Proceedings KDD'97, pages 67-73, Newport Beach, USA, 1997. AAAI Press.
31. M. J. Zaki. Generating non-redundant association rules. In Proceedings ACM SIGKDD'00, pages 34-43, Boston, USA, 2000. ACM Press.