Relational Data Mining

  • Sašo Džeroski
  • Nada Lavrač

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Introduction

    1. Front Matter
      Pages 1-1
    2. Sašo Džeroski
      Pages 3-27
    3. Sašo Džeroski, Nada Lavrač
      Pages 48-73
  3. Techniques

    1. Front Matter
      Pages 103-103
    2. Luc De Raedt, Hendrik Blockeel, Luc Dehaspe, Wim Van Laer
      Pages 105-139
    3. Stefan Kramer, Gerhard Widmer
      Pages 140-159
    4. Stephen Muggleton, John Firth
      Pages 160-188
    5. Luc Dehaspe, Hannu Toivonen
      Pages 189-212
    6. Mathias Kirsten, Stefan Wrobel, Tamás Horváth
      Pages 213-232
  4. From Propositional to Relational Data Mining

    1. Front Matter
      Pages 233-233
    2. Stefan Kramer, Nada Lavrač, Peter Flach
      Pages 262-291
    3. Ross Quinlan
      Pages 292-306
    4. Lise Getoor, Nir Friedman, Daphne Koller, Avi Pfeffer
      Pages 307-335
  5. Applications and Web Resources

    1. Front Matter
      Pages 337-337
    2. Sašo Džeroski
      Pages 339-364
    3. Ljupčo Todorovski, Irene Weber, Nada Lavrač, Olga Stěpánkova, Sašo Džeroski, Dimitar Kazakov et al.
      Pages 375-388
  6. Back Matter
    Pages 389-398

About this book


As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area.
The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining.
This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.


Algorithmic Learning Data Analysis Data Mining Inductive Logic Programming Knowledge Discovery Knowledge Processing Machine Learning Multi-Relational Data classification database knowledge learning logic logic programming programming

Editors and affiliations

  • Sašo Džeroski
    • 1
  • Nada Lavrač
    • 1
  1. 1.Jožef Stefan InstituteLjubljanaSlovenia

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2001
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-07604-6
  • Online ISBN 978-3-662-04599-2
  • Buy this book on publisher's site