Introduction to Data Mining and its Applications (Studies in Computational Intelligence, 29)

Sumathi, S.; Sivanandam, S.N.

ISBN 10: 3540343504 / ISBN 13: 9783540343509

Verlag: Springer, 2006

Beschreibung

Bestandsnummer des Verkäufers ABLIING23Mar3113020165585

Bibliografische Details

• Titel: Introduction to Data Mining and its Applications (Studies in Computational Intelligence, 29)
• Verlag: Springer
• Erscheinungsjahr: 2006
• Sprache: Englisch
• ISBN-10: 3540343504
• ISBN-13: 9783540343509
• Einband: Hardcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.

Von der hinteren Coverseite

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.