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Foundations of Computational Intelligence

Volume 6: Data Mining

  • Book
  • © 2009

Overview

  • Sixth volume of a Reference work on the foundations of Computational Intelligence
  • Devoted to Data Mining

Part of the book series: Studies in Computational Intelligence (SCI, volume 206)

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Table of contents (16 chapters)

  1. Data Click Streams and Temporal Data Mining

  2. Text and Rule Mining

  3. Data Mining Applications

Keywords

About this book

Foundations of Computational Intelligence Volume 6: Data Mining: Theoretical Foundations and Applications Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; arti- cial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are - plied to Data Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated. This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Int- ligence techniques for Data Mining. The book is divided into 3 parts: Part-I: Data Click Streams and Temporal Data Mining Part-II: Text and Rule Mining Part-III: Applications Part I on Data Click Streams and Temporal Data Mining contains four chapters that describe several approaches in Data Click Streams and Temporal Data Mining.

Editors and Affiliations

  • Machine Intelligence Research Labs, (MIR Labs), Scientific Network for Innovation and Research Excellence, Washington, USA

    Ajith Abraham

  • College of Business Administration, Quantitative and Information System Department, Kuwait University, Safat, Kuwait

    Aboul-Ella Hassanien

  • Department of Computer Science, University of São Paulo, Sao Carlos, Brazil

    André Ponce Leon F. de Carvalho

  • Dept. Computer Science, Technical University Ostrava, Ostrava, Czech Republic

    Václav Snášel

Bibliographic Information

  • Book Title: Foundations of Computational Intelligence

  • Book Subtitle: Volume 6: Data Mining

  • Editors: Ajith Abraham, Aboul-Ella Hassanien, André Ponce Leon F. de Carvalho, Václav Snášel

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-01091-0

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2009

  • Hardcover ISBN: 978-3-642-01090-3Published: 27 April 2009

  • Softcover ISBN: 978-3-642-10167-0Published: 28 October 2010

  • eBook ISBN: 978-3-642-01091-0Published: 01 May 2009

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: X, 400

  • Topics: Mathematical and Computational Engineering, Artificial Intelligence

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