The Blind Leading the Blind: Network-Based Location Estimation Under Uncertainty

We propose a probabilistic method for inferring the geographical locations of linked objects, such as users in a social network. Unlike existing methods, our model does not assume that the exact locations of any subset of the linked objects, like neighbor

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Annalisa Appice · Pedro Pereira Rodrigues Vitor Santos Costa · Carlos Soares João Gama · Alípio Jorge (Eds.)

Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2015 Porto, Portugal, September 7–11, 2015 Proceedings, Part II

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Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science

LNAI Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany

LNAI Founding Series Editor Joerg Siekmann DFKI and Saarland University, Saarbrücken, Germany

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More information about this series at http://www.springer.com/series/1244

Annalisa Appice Pedro Pereira Rodrigues Vitor Santos Costa João Gama Alípio Jorge Carlos Soares (Eds.) •





Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2015 Porto, Portugal, September 7–11, 2015 Proceedings, Part II

123

Editors Annalisa Appice University of Bari Aldo Moro Bari Italy

João Gama University of Porto - INESC TEC Porto Portugal

Pedro Pereira Rodrigues University of Porto Porto Portugal

Alípio Jorge University of Porto - INESC TEC Porto Portugal

Vitor Santos Costa University of Porto - CRACS/INESC TEC Porto Portugal

Carlos Soares University of Porto - INESC TEC Porto Portugal

ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-319-23524-0 ISBN 978-3-319-23525-7 (eBook) DOI 10.1007/978-3-319-23525-7 Library of Congress Control Number: 2015947118 LNCS Sublibrary: SL7 – Artificial Intelligence Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2015 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, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)

Preface

We are delighted to introduce the proceedings of the 2015 edition of the Europe