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ORCIDDatabase Support for Data Mining Applications 2004
- Rosa Meo, Pier Luca Lanzi, Mika Klemettinen:
Database Support for Data Mining Applications: Discovering Knowledge with Inductive Queries. Lecture Notes in Computer Science 2682, Springer 2004, ISBN 3-540-22479-3 - Jean-François Boulicaut:
Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach. 1-23 - Marco Botta, Jean-François Boulicaut, Cyrille Masson, Rosa Meo:
Query Languages Supporting Descriptive Rule Mining: A Comparative Study. 24-51 - Hasan M. Jamil:
Declarative Data Mining Using SQL3. 52-75 - Fosca Giannotti, Giuseppe Manco
, Franco Turini:
Towards a Logic Query Language for Data Mining. 76-94 - Donato Malerba, Annalisa Appice, Michelangelo Ceci:
A Data Mining Query Language for Knowledge Discovery in a Geographical Information System. 95-116 - Luc De Raedt:
Towards Query Evaluation in Inductive Databases Using Version Spaces. 117-134 - Petr Hájek, Jan Rauch, David Coufal, Thomas Feglar:
The GUHA Method, Data Preprocessing and Mining. 135-153 - Sau Dan Lee, Luc De Raedt:
Constraint Based Mining of First Order Sequences in SeqLog. 154-173 - Matthias Gimbel, Michael Klein, Peter C. Lockemann:
Interactivity, Scalability and Resource Control for Efficient KDD Support in DBMS. 174-193 - Ralf Rantzau:
Frequent Itemset Discovery with SQL Using Universal Quantification. 194-213 - Toon Calders:
Deducing Bounds on the Support of Itemsets. 214-233 - Artur Bykowski, Jouni K. Seppänen, Jaakko Hollmén:
Model-Independent Bounding of the Supports of Boolean Formulae in Binary Data. 234-249 - Arnaud Giacometti, Dominique Laurent, Cheikh Talibouya Diop:
Condensed Representations for Sets of Mining Queries. 250-269 - Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, H. Jaap van den Herik:
One-Sided Instance-Based Boundary Sets. 270-288 - Kimmo Hätönen, Mika Klemettinen:
Domain Structures in Filtering Irrelevant Frequent Patterns. 289-305 - Artur Bykowski, Thomas Daurel, Nicolas Méger, Christophe Rigotti:
Integrity Constraints over Association Rules. 306-323
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