Data Science and Big Data: An Environment of Computational Intelligence
This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and pract
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Witold Pedrycz Shyi-Ming Chen Editors
Data Science and Big Data: An Environment of Computational Intelligence
Studies in Big Data Volume 24
Series editor Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland e-mail: [email protected]
About this Series The series “Studies in Big Data” (SBD) publishes new developments and advances in the various areas of Big Data- quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economics and life sciences. The books of the series refer to the analysis and understanding of large, complex, and/or distributed data sets generated from recent digital sources coming from sensors or other physical instruments as well as simulations, crowd sourcing, social networks or other internet transactions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence incl. neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence, data mining, modern statistics and Operations research, as well as self-organizing systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.
More information about this series at http://www.springer.com/series/11970
Witold Pedrycz ⋅ Shyi-Ming Chen Editors
Data Science and Big Data: An Environment of Computational Intelligence
123
Editors Witold Pedrycz Department of Electrical and Computer Engineering University of Alberta Edmonton, AB Canada
ISSN 2197-6503 Studies in Big Data ISBN 978-3-319-53473-2 DOI 10.1007/978-3-319-53474-9
Shyi-Ming Chen Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan
ISSN 2197-6511
(electronic)
ISBN 978-3-319-53474-9
(eBook)
Library of Congress Control Number: 2017931524 © Springer International Publishing AG 2017 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. 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of
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