Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 29)
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Table of contents (25 chapters)
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Front Matter
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Introduction to Data Mining and its Applications
Authors: S. Sumathi, S. N. Sivanandam
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-34351-6
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2006
Hardcover ISBN: 978-3-540-34350-9Published: 26 September 2006
Softcover ISBN: 978-3-662-50080-4Published: 23 August 2016
eBook ISBN: 978-3-540-34351-6Published: 12 October 2006
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXII, 828
Topics: Data Mining and Knowledge Discovery, Mathematical and Computational Engineering, Artificial Intelligence