Graph Structures for Knowledge Representation and Reasoning Seco
This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2011, held in Barcelona, Spain, in July 2011 as satellite event of IJCAI 201
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LNAI Founding Series Editor Joerg Siekmann DFKI and Saarland University, Saarbrücken, Germany
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Madalina Croitoru Sebastian Rudolph Nic Wilson John Howse Olivier Corby (Eds.)
Graph Structures for Knowledge Representation and Reasoning Second International Workshop, GKR 2011 Barcelona, Spain, July 16, 2011 Revised Selected Papers
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Series Editors Randy Goebel, University of Alberta, Edmonton, Canada Jörg Siekmann, University of Saarland, Saarbrücken, Germany Wolfgang Wahlster, DFKI and University of Saarland, Saarbrücken, Germany Volume Editors Madalina Croitoru University Montpellier II, France E-mail: [email protected] Sebastian Rudolph Karlsruher Institut für Technologie, Germany E-mail: [email protected] Nic Wilson University College Cork, Ireland E-mail: [email protected] John Howse University of Brighton, UK E-mail: [email protected] Olivier Corby INRIA, Sophia Antipolis, France E-mail: [email protected] ISSN 0302-9743 e-ISSN 1611-3349 ISBN 978-3-642-29448-8 e-ISBN 978-3-642-29449-5 DOI 10.1007/978-3-642-29449-5 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2012934971 CR Subject Classification (1998): I.2, F.4.1, F.1, H.3, F.2, F.3 LNCS Sublibrary: SL 7 – Artificial Intelligence © Springer-Verlag Berlin Heidelberg 2012 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, 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. Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
The development of effective techniques for knowledge representation and reasoning (KRR) is a crucial aspect of successful intelligent systems. Different representation paradigms, as well as their use in dedicated reasoning systems, have been extensively studied in the past. Nevertheless, new challenges, problems, and issues have emerged in the context of knowledge representation in artificial intelligence, involving the logical manipulation of increasingly large information sets (as, for example, in the Semantic Web, bioinformatics, and various other areas). Improvements in storage capacity and performance of computing infrastructure have also affected the nature of KRR systems, shiftin
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