On Learning and Exploiting Time Domain Traffic Patterns in Cellular Radio Access Networks
This paper presents a vision of how the different management procedures of future Fifth Generation (5G) wireless networks can be built upon the pillar of artificial intelligence concepts. After a general description of a cellular network and its managemen
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Petra Perner (Ed.)
Machine Learning and Data Mining in Pattern Recognition 12th International Conference, MLDM 2016 New York, NY, USA, July 16–21, 2016 Proceedings
123
Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science
LNAI Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany
LNAI Founding Series Editor Joerg Siekmann DFKI and Saarland University, Saarbrücken, Germany
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More information about this series at http://www.springer.com/series/1244
Petra Perner (Ed.)
Machine Learning and Data Mining in Pattern Recognition 12th International Conference, MLDM 2016 New York, NY, USA, July 16–21, 2016 Proceedings
123
Editor Petra Perner Institute of Computer Vision and applied Computer Sciences, IBaI Leipzig, Saxony Germany
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-319-41919-0 ISBN 978-3-319-41920-6 (eBook) DOI 10.1007/978-3-319-41920-6 Library of Congress Control Number: 2016943411 LNCS Sublibrary: SL7 – Artificial Intelligence © Springer International Publishing Switzerland 2016 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 publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
Preface
The 12th event of the International Conference on Machine Learning and Data Mining MLDM 2016 was held in New York (www.mldm.de) running under the umbrella of the World Congress “The Frontiers in Intelligent Data and Signal Analysis, DSA2016” (www.worldcongressdsa.com). For this edition the Program Committee received 169 submissions. After the peer-review process, we accepted 56 high-quality papers for oral presentation. The topics range from theoretical topics for classification, clustering, association rule, and pattern mining to specific data-mining methods for the
