Analysing Indexability of Intrinsically High-Dimensional Data Using TriGen
The TriGen algorithm is a general approach to transform distance spaces in order to provide both exact and approximate similarity search in metric and non-metric spaces. This paper focuses on the reduction of intrinsic dimensionality using TriGen. Besides
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Shin'ichi Satoh · Lucia Vadicamo · Arthur Zimek · Fabio Carrara · Ilaria Bartolini · Martin Aumüller · Björn Þór Jónsson · Rasmus Pagh (Eds.)
Similarity Search and Applications 13th International Conference, SISAP 2020 Copenhagen, Denmark, September 30 – October 2, 2020 Proceedings
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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Shin’ichi Satoh Lucia Vadicamo Arthur Zimek Fabio Carrara Ilaria Bartolini Martin Aumüller Björn Þór Jónsson Rasmus Pagh (Eds.) •
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Similarity Search and Applications 13th International Conference, SISAP 2020 Copenhagen, Denmark, September 30 – October 2, 2020 Proceedings
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Editors Shin’ichi Satoh National Institute of Informatics Tokyo, Japan
Lucia Vadicamo ISTI-CNR Pisa, Italy
Arthur Zimek University of Southern Denmark Odense M, Denmark
Fabio Carrara ISTI-CNR Pisa, Italy
Ilaria Bartolini University of Bologna Bologna, Italy
Martin Aumüller IT University of Copenhagen Copenhagen, Denmark
Björn Þór Jónsson IT University of Copenhagen Copenhagen, Denmark
Rasmus Pagh IT University of Copenhagen Copenhagen, Denmark
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-60935-1 ISBN 978-3-030-60936-8 (eBook) https://doi.org/10.1007/978-3-030-60936-8 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
