Foundations and Novel Approaches in Data Mining: 9 Softcover reprint of hardcover 1st ed. 2006 Edition

Foundations and Novel Approaches in Data Mining: 9 Softcover reprint of hardcover 1st ed. 2006 Edition book cover

Foundations and Novel Approaches in Data Mining: 9 Softcover reprint of hardcover 1st ed. 2006 Edition

Author(s): Tsau Young Lin (Editor), Setsuo Ohsuga (Editor), Churn-Jung Liau (Editor), Xiaohua Hu (Editor)

  • Publisher: Springer
  • Publication Date: 20 Nov. 2010
  • Edition: Softcover reprint of hardcover 1st ed. 2006
  • Language: English
  • Print length: 388 pages
  • ISBN-10: 364206650X
  • ISBN-13: 9783642066504

Book Description

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.

Editorial Reviews

From the Back Cover

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 realworld 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.

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