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Transactions on Large-Scale Data- and Knowledge-Centered Systems XXVII

Special Issue on Big Data for Complex Urban Systems

  • Abdelkader Hameurlain
  • Josef Küng
  • Roland Wagner
  • Amin Anjomshoaa
  • Patrick C. K.  Hung
  • Dominik Kalisch
  • Stanislav Sobolevsky

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9860)

Also part of the Transactions on Large-Scale Data- and Knowledge-Centered Systems book sub series (TLDKS, volume 9860)

Table of contents

  1. Front Matter
    Pages I-XII
  2. Cássia de Souza Carvalho, Fabrício Olivetti de França, Denise Hideko Goya, Claudio Luis de Camargo Penteado
    Pages 1-18
  3. Teruyuki Iijima, Takahiro Kawamura, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
    Pages 19-30
  4. Dominik Kalisch, Steffen Braun, Alanus von Radecki
    Pages 31-47
  5. Shawyun Sariri, Volker Schwarzer, Dominik P. H. Kalisch, Michael Angelo, Reza Ghorbani
    Pages 48-63
  6. Judie Attard, Fabrizio Orlandi, Sören Auer
    Pages 84-110
  7. Gisele S. Craveiro, Jose P. Alcazar, Andres M. R. Martano
    Pages 111-128
  8. Shusaku Egami, Takahiro Kawamura, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
    Pages 129-141
  9. Konstantinos Maraslis, Peter Cooper, Theo Tryfonas, George Oikonomou
    Pages 142-158
  10. Yuji Yoshimura, Alexander Amini, Stanislav Sobolevsky, Josep Blat, Carlo Ratti
    Pages 177-189
  11. Kun Xie, Kaan Ozbay, Yuan Zhu, Hong Yang
    Pages 190-207
  12. Back Matter
    Pages 209-209

About this book

Introduction

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments.

This, the 27th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of 12 papers presented at the Big Data and Technology for Complex Urban Systems symposium, held in Kauai, HI, USA in January 2016. The papers explore the use of big data in complex urban systems in the areas of politics, society, commerce, tax, and emergency management.

Keywords

big data complex systems e-government smart cities urban studies clustering algorithms consumer behaviors emergency management/planning evacuation modeling geo-spatial data government human behavior human mobility open government data optimization publishing supervised learning algorithms transaction data urban science value creation

Editors and affiliations

  • Abdelkader Hameurlain
    • 1
  • Josef Küng
    • 2
  • Roland Wagner
    • 3
  • Amin Anjomshoaa
    • 4
  • Patrick C. K.  Hung
    • 5
  • Dominik Kalisch
    • 6
  • Stanislav Sobolevsky
    • 7
  1. 1.IRITPaul Sabatier UniversityToulouseFrance
  2. 2.FAWUniversity of LinzLinzAustria
  3. 3.FAWUniversity of LinzLinzAustria
  4. 4.MIT SENSEable City LabCambridgeUSA
  5. 5.Faculty of Business and Information TechnologyUniversity of Ontario Institute of Technology (UOIT)OshawaCanada
  6. 6.Trinity UniversityPlainviewUSA
  7. 7.New York UniversityBrooklynUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-53416-8
  • Copyright Information Springer-Verlag GmbH Germany 2016
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-662-53415-1
  • Online ISBN 978-3-662-53416-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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