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Constraint-Based Mining and Inductive Databases

European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers

  • Conference proceedings
  • © 2006

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Overview

Editors:
  1. Jean-François Boulicaut

    1. INSA-Lyon, LIRIS CNRS UMR5205, Villeurbanne, France

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  2. Luc Raedt

    1. Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium

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  3. Heikki Mannila

    1. HIIT, Helsinki University of Technology and, University of Helsinki, Finland

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3848)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Keywords

Table of contents (18 papers)

  1. Front Matter

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  2. The Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery

    • Roberto J. Bayardo
    Pages 1-13
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  3. A Relational Query Primitive for Constraint-Based Pattern Mining

    • Francesco Bonchi, Fosca Giannotti, Dino Pedreschi
    Pages 14-37
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  4. To See the Wood for the Trees: Mining Frequent Tree Patterns

    • Björn Bringmann
    Pages 38-63
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  5. A Survey on Condensed Representations for Frequent Sets

    • Toon Calders, Christophe Rigotti, Jean-François Boulicaut
    Pages 64-80
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  6. Adaptive Strategies for Mining the Positive Border of Interesting Patterns: Application to Inclusion Dependencies in Databases

    • Fabien De Marchi, Frédéric Flouvat, Jean-Marc Petit
    Pages 81-101
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  7. Computation of Mining Queries: An Algebraic Approach

    • Cheikh Talibouya Diop, Arnaud Giacometti, Dominique Laurent, Nicolas Spyratos
    Pages 102-126
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  8. Inductive Queries on Polynomial Equations

    • Sašo Džeroski, Ljupčo Todorovski, Peter Ljubič
    Pages 127-154
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  9. Mining Constrained Graphs: The Case of Workflow Systems

    • Gianluigi Greco, Antonella Guzzo, Giuseppe Manco, Luigi Pontieri, Domenico Saccà
    Pages 155-171
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  10. CrossMine: Efficient Classification Across Multiple Database Relations

    • Xiaoxin Yin, Jiawei Han, Jiong Yang, Philip S. Yu
    Pages 172-195
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  11. Remarks on the Industrial Application of Inductive Database Technologies

    • Kimmo Hätönen, Mika Klemettinen, Markus Miettinen
    Pages 196-215
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  12. How to Quickly Find a Witness

    • Daniel Kifer, Johannes Gehrke, Cristian Bucila, Walker White
    Pages 216-242
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  13. Relevancy in Constraint-Based Subgroup Discovery

    • Nada Lavrač, Dragan Gamberger
    Pages 243-266
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  14. A Novel Incremental Approach to Association Rules Mining in Inductive Databases

    • Rosa Meo, Marco Botta, Roberto Esposito, Arianna Gallo
    Pages 267-294
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  15. Employing Inductive Databases in Concrete Applications

    • Rosa Meo, Pier Luca Lanzi, Maristella Matera, Danilo Careggio, Roberto Esposito
    Pages 295-327
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  16. Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining

    • Ruggero G. Pensa, Jérémy Besson, Céline Robardet, Jean-François Boulicaut
    Pages 328-347
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  17. Boolean Formulas and Frequent Sets

    • Jouni K. Seppänen, Heikki Mannila
    Pages 348-361
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  18. Generic Pattern Mining Via Data Mining Template Library

    • Mohammed J. Zaki, Nilanjana De, Feng Gao, Paolo Palmerini, Nagender Parimi, Jeevan Pathuri et al.
    Pages 362-379
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  19. Inductive Querying for Discovering Subgroups and Clusters

    • Albrecht Zimmermann, Luc De Raedt
    Pages 380-399
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  20. Back Matter

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Editors and Affiliations

  • INSA-Lyon, LIRIS CNRS UMR5205, Villeurbanne, France

    Jean-François Boulicaut

  • Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium

    Luc Raedt

  • HIIT, Helsinki University of Technology and, University of Helsinki, Finland

    Heikki Mannila

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