Frequent Closures as a Concise Representation for Binary Data Mining-Reference-Cited by-同舟云学术

Frequent Closures as a Concise Representation for Binary Data Mining

Published:2000 Issue: Volume: Page:62-73
ISSN:0302-9743
Container-title:Knowledge Discovery and Data Mining. Current Issues and New Applications
language:
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Author:

Boulicaut Jean-François,Bykowski Artur

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-45571-X_9

Reference13 articles.

1. R. Agrawal, T. Imielinski, and A. Swami. Mining association rules between sets of items in large databases. In: Proc. SIGMOD’93, Washington DC (USA), pages 207–216, May 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, 1996, AAAI Press.

3. R.J. Bayardo. Efficiently mining of long patterns from databases. In: Proc. SIG-MOD’98, Seattle (USA), pages 85–93, June 1998, ACM Press.

4. Lect Notes Comput Sci;J.-F. Boulicaut,1999

5. J-F. Boulicaut, A. Bykowski, and C. Rigotti. Mining almost-closures in highly correlated data. Research Report LISI INSA Lyon, 2000, 20 pages.

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