Knowledge Graphs and Big Data Processing
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many i
- PDF / 12,005,944 Bytes
- 212 Pages / 439.37 x 666.142 pts Page_size
- 58 Downloads / 219 Views
State-of-the-Art Survey
Valentina Janev Damien Graux Hajira Jabeen Emanuel Sallinger (Eds.)
Knowledge Graphs and Big Data Processing
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
12072
More information about this series at http://www.springer.com/series/7409
Valentina Janev Damien Graux Hajira Jabeen Emanuel Sallinger (Eds.) •
•
•
Knowledge Graphs and Big Data Processing
123
Editors Valentina Janev Institute Mihajlo Pupin University of Belgrade Belgrade, Serbia Hajira Jabeen CEPLAS, Botanical Institute University of Cologne Cologne, Germany
Damien Graux ADAPT SFI Centre, O’Reilly Institute Trinity College Dublin Dublin, Ireland Emanuel Sallinger Institute of Logic and Computation Faculty of Informatics TU Wien Wien, Austria University of Oxford Oxford, UK
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-53198-0 ISBN 978-3-030-53199-7 (eBook) https://doi.org/10.1007/978-3-030-53199-7 LNCS Sublibrary: SL3 – Information Systems and Applications, incl. Internet/Web, and HCI The Editor(s) (if applicable) and The Author(s) 2020. This book is an open access publication. Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. 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 clai
Data Loading...
