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Data Mining and Knowledge Discovery Handbook (Hardback)

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ISBN 10: 0387098224 / ISBN 13: 9780387098227
Edité par Springer-Verlag New York Inc., United States, 2010
Neuf(s) Etat : New Couverture rigide
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A propos de cet article

Language: English . Brand New Book. This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries. N° de réf. du libraire SPR9780387098227

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Détails bibliographiques

Titre : Data Mining and Knowledge Discovery Handbook...

Éditeur : Springer-Verlag New York Inc., United States

Date d'édition : 2010

Reliure : Hardback

Etat du livre :New

Edition : 2nd ed. 2010.

A propos de ce titre

Synopsis :

This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

From the Back Cover:

Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data.

Data Mining and Knowledge Discovery Handbook, Second Edition organizes the most current concepts, theories, standards, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This handbook first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security.

Data Mining and Knowledge Discovery Handbook, Second Edition is designed for research scientists, libraries and advanced-level students in computer science and engineering as a reference. This handbook is also suitable for professionals in industry, for computing applications, information systems management, and strategic research management.

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