Modeling Local and Global Flow Aggregation for Traffic Flow Forecasting
Traffic flow forecasting is significant to traffic management and public safety. However, it is a challenging problem, because of complex spatial and temporal dependencies. Many existing approaches adopt Graph Convolution Networks (GCN) to model spatial d
- PDF / 41,519,927 Bytes
- 584 Pages / 439.37 x 666.142 pts Page_size
- 23 Downloads / 268 Views
Zhisheng Huang · Wouter Beek · Hua Wang · Rui Zhou · Yanchun Zhang (Eds.)
Web Information Systems Engineering – WISE 2020 21st International Conference Amsterdam, The Netherlands, October 20–24, 2020 Proceedings, Part I
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
12342
More information about this series at http://www.springer.com/series/7409
Zhisheng Huang Wouter Beek Hua Wang Rui Zhou Yanchun Zhang (Eds.) •
•
•
•
Web Information Systems Engineering – WISE 2020 21st International Conference Amsterdam, The Netherlands, October 20–24, 2020 Proceedings, Part I
123
Editors Zhisheng Huang VU Amsterdam Amsterdam, The Netherlands
Wouter Beek VU Amsterdam Amsterdam, The Netherlands
Hua Wang Victoria University Melbourne, VIC, Australia
Rui Zhou Swinburne University of Technology Hawthorn, VIC, Australia
Yanchun Zhang Victoria University Melbourne, VIC, Australia
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-62004-2 ISBN 978-3-030-62005-9 (eBook) https://doi.org/10.1007/978-3-030-62005-9 LNCS Sublibrary: SL3 – Information Systems and Applications, incl. Internet/Web, and HCI © 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 to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Welcome to the proceedings of the 21st International Conference on Web Inf
