Data Mining Query Languages

Author:

Boulicaut Jean-Francois,Masson Cyrille

Publisher

Springer-Verlag

Reference25 articles.

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 Press, 1996.

2. Y. Bastide, N. Pasquier, R. Taouil, G. Stumme, and L. Lakhal. Mining minimal non-redundant association rules using frequent closed itemsets. In Proc. CL 2000, volume 1861 of LNCS, pages 972–986. Springer-Verlag, 2000.

3. M. Botta, J.-F. Boulicaut, C. Masson, and R. Meo. Query languages supporting descriptive rule mining: a comparative study. In Database Technologies for Data Mining-Discovering Knowledge with Inductive Queries, volume 2682 of LNCS, pages 27–54. Springer-Verlag, 2004.

4. J.-F. Boulicaut. Inductive databases and multiple uses of frequent itemsets: the clnQ approach. In Database Technologies for Data Mining-Discovering Knowledge with Inductive Queries, volume 2682 of LNCS, pages 3–26. Springer-Verlag, 2004.

5. J.-F. Boulicaut and B. Jeudy. Constraint-based Data Mining. In Data Mining and Knowledge Discovery Handbook. Chapter 18, this volume, Kluwer, 2005.

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