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Table of contents

  1. Front Matter
  2. T. Poggio, S. Smale
    Pages 1-19
  3. B. Liu, Y. Xia, P.S. Yu
    Pages 97-124
  4. W.-G. Teng, M.-S. Chen
    Pages 125-162
  5. B. Choi, Z. Yao
    Pages 221-274
  6. T. Srivastava, P. Desikan, V. Kumar
    Pages 275-307
  7. C. Clifton, M. Kantarcıoğlu, J. Vaidya
    Pages 309-340

About this book

Introduction

With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.

Keywords

Analysis Regression classification construction data mining learning pattern mining web mining

Bibliographic information

  • DOI https://doi.org/10.1007/b104039
  • Copyright Information Springer-Verlag Berlin/Heidelberg 2005
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-25057-9
  • Online ISBN 978-3-540-32393-8
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site
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