Entropy-Based Measure for Influence Maximization in Temporal Networks
The challenge of influence maximization in social networks is tackled in many settings and scenarios. However, the most explored variant is looking at how to choose a seed set of a given size, that maximizes the number of activated nodes for selected mode
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Valeria V. Krzhizhanovskaya · Gábor Závodszky · Michael H. Lees · Jack J. Dongarra · Peter M. A. Sloot · Sérgio Brissos · João Teixeira (Eds.)
Computational Science – ICCS 2020 20th International Conference Amsterdam, The Netherlands, June 3–5, 2020 Proceedings, Part IV
Lecture Notes in Computer Science Founding Editors Gerhard Goos Karlsruhe Institute of Technology, Karlsruhe, Germany Juris Hartmanis Cornell University, Ithaca, NY, USA
Editorial Board Members Elisa Bertino Purdue University, West Lafayette, IN, USA Wen Gao Peking University, Beijing, China Bernhard Steffen TU Dortmund University, Dortmund, Germany Gerhard Woeginger RWTH Aachen, Aachen, Germany Moti Yung Columbia University, New York, NY, USA
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More information about this series at http://www.springer.com/series/7407
Valeria V. Krzhizhanovskaya Gábor Závodszky Michael H. Lees Jack J. Dongarra Peter M. A. Sloot Sérgio Brissos João Teixeira (Eds.) •
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Computational Science – ICCS 2020 20th International Conference Amsterdam, The Netherlands, June 3–5, 2020 Proceedings, Part IV
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Editors Valeria V. Krzhizhanovskaya University of Amsterdam Amsterdam, The Netherlands
Gábor Závodszky University of Amsterdam Amsterdam, The Netherlands
Michael H. Lees University of Amsterdam Amsterdam, The Netherlands
Jack J. Dongarra University of Tennessee Knoxville, TN, USA
Peter M. A. Sloot University of Amsterdam Amsterdam, The Netherlands
Sérgio Brissos Intellegibilis Setúbal, Portugal
ITMO University Saint Petersburg, Russia Nanyang Technological University Singapore, Singapore João Teixeira Intellegibilis Setúbal, Portugal
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-50422-9 ISBN 978-3-030-50423-6 (eBook) https://doi.org/10.1007/978-3-030-50423-6 LNCS Sublibrary: SL1 – Theoretical Computer Science and General Issues © Springer Nature Switzerland AG 2020 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, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard
