Data Mining: Foundations and Intelligent Paradigms

Volume 1: Clustering, Association and Classification

  • Dawn E. Holmes
  • Lakhmi C. Jain

Part of the Intelligent Systems Reference Library book series (ISRL, volume 23)

Table of contents

  1. Front Matter
  2. Dawn E. Holmes, Jeffrey Tweedale, Lakhmi C. Jain
    Pages 1-6
  3. R. Avros, O. Granichin, D. Shalymov, Z. Volkovich, G. -W. Weber
    Pages 131-155
  4. Marek Wojciechowski, Maciej Zakrzewicz, Pawel Boinski
    Pages 223-266
  5. Tru H. Cao, Thao M. Tang, Cuong K. Chau
    Pages 267-287
  6. Wei Ding, Christoph F. Eick
    Pages 289-313
  7. Troy Raeder, George Forman, Nitesh V. Chawla
    Pages 315-331
  8. Back Matter

About this book

Introduction

Data mining is one of the most rapidly growing research areas in computer science and statistics. In Volume 1of this three volume series, we have brought together contributions from some of the most prestigious researchers in the fundamental data mining tasks of clustering, association and classification. Each of the chapters is self contained. Theoreticians and applied scientists/ engineers will find this volume valuable. Additionally, it provides a sourcebook for graduate students interested in the current direction of research in these aspects of data mining.

Keywords

Computational Intelligence Data Mining Intelligent Paradigms

Editors and affiliations

  • Dawn E. Holmes
    • 1
  • Lakhmi C. Jain
    • 2
  1. 1.Department of Statistics and Applied Probability University of CaliforniaSanta BarbaraUSA
  2. 2.Knowledge-Based Engineering University of South AustraliaAdelaide, Mawson LakesAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-23166-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-23165-0
  • Online ISBN 978-3-642-23166-7
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • About this book