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Foundations of Data Mining and Knowledge Discovery: 6 2005th Edition
Author(s): Tsau Young Lin (Editor), Setsuo Ohsuga (Editor), Churn-Jung Liau (Editor), Xiaohua Hu (Editor), Shusaku Tsumoto (Editor)
- Publisher: Springer
- Publication Date: 16 Nov. 2014
- Edition: 2005th
- Language: English
- Print length: 391 pages
- ISBN-10: 364243228X
- ISBN-13: 9783642432286
Book Description
“Foundations of Data Mining and Knowledge Discovery” contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state of the art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.
Editorial Reviews
From the Back Cover
Foundations of Data Mining and Knowledge Discovery contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state-of-the-art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.
