Big Data Analytics in the Social and Ubiquitous Context 5th Internat
The 9 papers presented in this book are revised and significantly extended versions of papers submitted to three related workshops: The 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and the First International Worksho
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Martin Atzmueller · Alvin Chin Frederik Janssen · Immanuel Schweizer Christoph Trattner (Eds.)
Big Data Analytics in the Social and Ubiquitous Context 5th International Workshop on Modeling Social Media, MSM 2014 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014 and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers
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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
Martin Atzmueller Alvin Chin Frederik Janssen Immanuel Schweizer Christoph Trattner (Eds.) •
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Big Data Analytics in the Social and Ubiquitous Context 5th International Workshop on Modeling Social Media, MSM 2014 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014 and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014 Revised Selected Papers
123
Editors Martin Atzmueller University of Kassel Kassel, Hessen Germany
Immanuel Schweizer TU Darmstadt Darmstadt Germany
Alvin Chin BMW Technology Group Chicago, IL USA
Christoph Trattner Graz University of Technology Graz Austria
Frederik Janssen Knowledge Engineering Technische Universität Darmstadt Darmstadt, Hessen Germany
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-319-29008-9 ISBN 978-3-319-29009-6 (eBook) DOI 10.1007/978-3-319-29009-6 Library of Congress Control Number: 2015960407 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 pa
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