Data Mining and Knowledge Discovery for Big Data Methodologies, Chal
The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineerin
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Wesley W. Chu Editor
Data Mining and Knowledge Discovery for Big Data Methodologies, Challenge and Opportunities
Studies in Big Data Volume 1
Series Editor Janusz Kacprzyk, Warsaw, Poland
For further volumes: http://www.springer.com/series/11970
Wesley W. Chu Editor
Data Mining and Knowledge Discovery for Big Data Methodologies, Challenge and Opportunities
ABC
Editor Wesley W. Chu Department of Computer Science University of California Los Angeles USA
ISSN 2197-6503 ISBN 978-3-642-40836-6 DOI 10.1007/978-3-642-40837-3
ISSN 2197-6511 (electronic) ISBN 978-3-642-40837-3 (eBook)
Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2013947706 c Springer-Verlag Berlin Heidelberg 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein.
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Preface
The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. This transdisciplinary aspect of data mining addresses the rapidly expanding areas of science and engineering which demand
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