Studies in Computational Intelligence

Mining Complex Data

Editors: Zighed, D.A., Tsumoto, S., Ras, Z.W., Hacid, H. (Eds.)

  • First publication focusing specifically on mining complex data

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eBook $199.00
price for USA in USD (gross)
  • ISBN 978-3-540-88067-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $259.00
price for USA in USD
  • ISBN 978-3-540-88066-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $259.00
price for USA in USD
  • ISBN 978-3-642-09980-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. The whole knowledge discovery process being involved, our goal is to provide researchers dealing with each step of this process by key entries. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g. structuring and organizing) to the visualization and interpretation (e.g. sorting or filtering) of the results, via the data mining methods themselves (e.g. classification, clustering, frequent patterns extraction, etc.). The papers presented here are selected from the workshop papers held yearly since 2006.

The book is composed of four parts and a total of sixteen chapters. Part I gives a general view of complex data mining by illustrating some situations and the related complexity. It contains five chapters. Chapter 1 illustrates the problem of analyzing the scientific literature. The chapter gives some background to the various techniques in this area, explains the necessary pre-processing steps involved, and presents two case studies, one from image mining and one from table identification.

Table of contents (16 chapters)

  • Using Layout Data for the Analysis of Scientific Literature

    Mathiak, Brigitte (et al.)

    Pages 3-22

  • Extracting a Fuzzy System by Using Genetic Algorithms for Imbalanced Datasets Classification: Application on Down’s Syndrome Detection

    Soler, Vicenç (et al.)

    Pages 23-39

  • A Hybrid Approach of Boosting Against Noisy Data

    Bahri, Emna (et al.)

    Pages 41-54

  • Dealing with Missing Values in a Probabilistic Decision Tree during Classification

    Hawarah, Lamis (et al.)

    Pages 55-74

  • Kernel-Based Algorithms and Visualization for Interval Data Mining

    Do, Thanh-Nghi (et al.)

    Pages 75-91

Buy this book

eBook $199.00
price for USA in USD (gross)
  • ISBN 978-3-540-88067-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $259.00
price for USA in USD
  • ISBN 978-3-540-88066-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $259.00
price for USA in USD
  • ISBN 978-3-642-09980-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Mining Complex Data
Editors
  • Djamel A. Zighed
  • Shusaku Tsumoto
  • Zbigniew W Ras
  • Hakim Hacid
Series Title
Studies in Computational Intelligence
Series Volume
165
Copyright
2009
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-88067-7
DOI
10.1007/978-3-540-88067-7
Hardcover ISBN
978-3-540-88066-0
Softcover ISBN
978-3-642-09980-9
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XII, 302
Number of Illustrations and Tables
114 b/w illustrations
Topics