Editors:
- Latest results in data mining
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 9)
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Table of contents (20 chapters)
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Front Matter
About this book
Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. Currently, application oriented engineers are only concerned with their immediate problems, which results in an ad hoc method of problem solving. Researchers, on the other hand, lack an understanding of the practical issues of data-mining for real-world problems and often concentrate on issues that are of no significance to the practitioners. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research. A set of well respected data mining theoreticians were invited to present their views on the fundamental science of data mining. We have also called on researchers with practical data mining experiences to present new important data-mining topics.
Bibliographic Information
Book Title: Foundations and Novel Approaches in Data Mining
Editors: Tsau Young Lin, Setsuo Ohsuga, Churn-Jung Liau, Xiaohua Hu
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/11539827
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2006
Hardcover ISBN: 978-3-540-28315-7Published: 03 November 2005
Softcover ISBN: 978-3-642-06650-4Published: 20 November 2010
eBook ISBN: 978-3-540-31229-1Published: 23 November 2005
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 378
Topics: Mathematical and Computational Engineering, Artificial Intelligence