Database Support for Data Mining Applications

Discovering Knowledge with Inductive Queries

  • Rosa Meo
  • Pier Luca Lanzi
  • Mika Klemettinen

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2682)

Also part of the Lecture Notes in Artificial Intelligence book sub series (volume 2682)

Table of contents

  1. Front Matter
  2. Database Languages and Query Execution

    1. Marco Botta, Jean-François Boulicaut, Cyrille Masson, Rosa Meo
      Pages 24-51
    2. Hasan M. Jamil
      Pages 52-75
    3. Fosca Giannotti, Giuseppe Manco, Franco Turini
      Pages 76-94
    4. Donato Malerba, Annalisa Appice, Michelangelo Ceci
      Pages 95-116
    5. Petr Hájek, Jan Rauch, David Coufal, Tomáš Feglar
      Pages 135-153
    6. Sau Dan Lee, Luc De Raedt
      Pages 154-173
  3. Support for KDD-Process

    1. Matthias Gimbel, Michael Klein, P. C. Lockemann
      Pages 174-193
    2. Toon Calders
      Pages 214-233
    3. Artur Bykowski, Jouni K. Seppänen, Jaakko Hollmén
      Pages 234-249
    4. Arnaud Giacometti, Dominique Laurent, Cheikh Talibouya Diop
      Pages 250-269
    5. Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, H Jaap van den Herik
      Pages 270-288
    6. Kimmo Hätönen, Mika Klemettinen
      Pages 289-305
    7. Artur Bykowski, Thomas Daurel, Nicolas Méger, Christophe Rigotti
      Pages 306-323
  4. Back Matter

About this book

Introduction

Data mining from traditional relational databases as well as from non-traditional ones such as semi-structured data, Web data, and scientific databases housing biological, linguistic, and sensor data has recently become a popular way of discovering hidden knowledge.

This book on database support for data mining is developed to approaches exploiting the available database technology, declarative data mining, intelligent querying, and associated issues, such as optimization, indexing, query processing, languages, and constraints. Attention is also paid to the solution of data preprocessing problems, such as data cleaning, discretization, and sampling.

The 16 reviewed full papers presented were carefully selected from various workshops and conferences to provide complete and competent coverage of the core issues. Some papers were developed within an EC funded project on discovering knowledge with inductive queries.

Keywords

DOM association rules data analysis data mining database management systems database mining database query languages declarative data mining inductive queries information system knowledge discovery knowledge extraction optimization relational databases sql

Editors and affiliations

  • Rosa Meo
    • 1
  • Pier Luca Lanzi
    • 2
  • Mika Klemettinen
    • 3
  1. 1.Dipartimento di InformaticaUniversità di TorinoItaly
  2. 2.Dipartimento di Elettronica e InformazionePolitecnico di MilanoMilanoItaly
  3. 3.Nokia Research CenterNokia GroupFinland

Bibliographic information

  • DOI https://doi.org/10.1007/b99016
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-22479-2
  • Online ISBN 978-3-540-44497-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book
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