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Focusing Solutions for Data Mining

Analytical Studies and Experimental Results in Real-World Domains

  • Thomas┬áReinartz

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1623)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 1623)

Table of contents

  1. Front Matter
    Pages I-XV
  2. Pages 1-9
  3. Pages 45-84
  4. Pages 85-158
  5. Pages 159-172
  6. Pages 173-229
  7. Pages 231-238
  8. Back Matter
    Pages 239-309

About this book

Introduction

In the first part, this book analyzes the knowledge discovery process in order to understand the relations between knowledge discovery steps and focusing. The part devoted to the development of focusing solutions opens with an analysis of the state of the art, then introduces the relevant techniques, and finally culminates in implementing a unified approach as a generic sampling algorithm, which is then integrated into a commercial data mining system. The last part evaluates specific focusing solutions in various application domains. The book provides various appendicies enhancing easy accessibility.
The book presents a comprehensive introduction to focusing in the context of data mining and knowledge discovery. It is written for researchers and advanced students, as well as for professionals applying data mining and knowledge discovery techniques in practice.

Keywords

Algorithmic Learning DOM Data Mining Algorithms Intelligent Sampling algorithms data mining databases knowledge discovery

Editors and affiliations

  • Thomas┬áReinartz
    • 1
  1. 1.DaimlerChrysler AGResearch and TechnologyUlmGermany

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-48316-0
  • Copyright Information Springer-Verlag Berlin Heidelberg 1999
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-66429-1
  • Online ISBN 978-3-540-48316-8
  • Series Print ISSN 0302-9743
  • Buy this book on publisher's site
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