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Graph Structures for Knowledge Representation and Reasoning

Third International Workshop, GKR 2013, Beijing, China, August 3, 2013. Revised Selected Papers

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Madalina Croitoru

    1. LIRMM, Montpellier Cedex 5, France

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  2. Sebastian Rudolph

    1. Fakultät Informatik, Technische Universität Dresden, Dresden, Germany

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  3. Stefan Woltran

    1. Institute of Information Systems, Vienna University of Technology, Austria

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  4. Christophe Gonzales

    1. Laboratoire d’Informatique de Paris 6 (LIP6/UPMC), Université Pierre et Marie Curie, Paris, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8323)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Table of contents (12 papers)

  1. Front Matter

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  2. Implementation of a Knowledge Representation and Reasoning Tool Using Default Rules for a Decision Support System in Agronomy Applications

    • Patrice Buche, Virginie Cucheval, Awa Diattara, Jérôme Fortin, Alain Gutierrez
    Pages 1-12

  3. Information Revelation Strategies in Abstract Argument Frameworks Using Graph Based Reasoning

    • Madalina Croitoru, Nir Oren
    Pages 13-20

  4. Different Classes of Graphs to Represent Microstructures for CSPs

    • Achref El Mouelhi, Philippe Jégou, Cyril Terrioux
    Pages 21-38

  5. Finding Maximal Common Sub-parse Thickets for Multi-sentence Search

    • Boris A. Galitsky, Dmitry Ilvovsky, Sergei O. Kuznetsov, Fedor Strok
    Pages 39-57

  6. Intrusion Detection with Hypergraph-Based Attack Models

    • Antonella Guzzo, Andrea Pugliese, Antonino Rullo, Domenico Saccà
    Pages 58-73

  7. Structural Consistency: A New Filtering Approach for Constraint Networks

    • Philippe Jégou, Cyril Terrioux
    Pages 74-91

  8. Inductive Triple Graphs: A Purely Functional Approach to Represent RDF

    • Jose Emilio Labra Gayo, Johan Jeuring, Jose María Álvarez Rodríguez
    Pages 92-110

  9. A Depth-First Branch and Bound Algorithm for Learning Optimal Bayesian Networks

    • Brandon Malone, Changhe Yuan
    Pages 111-122

  10. Learning Bayes Nets for Relational Data with Link Uncertainty

    • Zhensong Qian, Oliver Schulte
    Pages 123-137

  11. Concurrent Reasoning with Inference Graphs

    • Daniel R. Schlegel, Stuart C. Shapiro
    Pages 138-164

  12. Formal Concept Analysis over Graphs and Hypergraphs

    • John G. Stell
    Pages 165-179

  13. Automatic Strengthening of Graph-Structured Knowledge Bases

    • Vinay Chaudhri, Nikhil Dinesh, Stijn Heymans, Michael Wessel
    Pages 180-210

  14. Back Matter

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Keywords

About this book

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2013, held in Beijing, China, in August 2013, associated with IJCAI 2013, the 23rd International Joint Conference on Artificial Intelligence. The 12 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers feature current research involved in the development and application of graph-based knowledge representation formalisms and reasoning techniques. They address the following topics: representations of constraint satisfaction problems; formal concept analysis; conceptual graphs; and argumentation frameworks.

Editors and Affiliations

  • LIRMM, Montpellier Cedex 5, France

    Madalina Croitoru

  • Fakultät Informatik, Technische Universität Dresden, Dresden, Germany

    Sebastian Rudolph

  • Institute of Information Systems, Vienna University of Technology, Austria

    Stefan Woltran

  • Laboratoire d’Informatique de Paris 6 (LIP6/UPMC), Université Pierre et Marie Curie, Paris, France

    Christophe Gonzales

Bibliographic Information

  • Book Title: Graph Structures for Knowledge Representation and Reasoning

  • Book Subtitle: Third International Workshop, GKR 2013, Beijing, China, August 3, 2013. Revised Selected Papers

  • Editors: Madalina Croitoru, Sebastian Rudolph, Stefan Woltran, Christophe Gonzales

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-319-04534-4

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing Switzerland 2014

  • Softcover ISBN: 978-3-319-04533-7Published: 29 January 2014

  • eBook ISBN: 978-3-319-04534-4Published: 21 January 2014

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 211

  • Number of Illustrations: 64 b/w illustrations

  • Topics: Artificial Intelligence, Mathematical Logic and Formal Languages, Discrete Mathematics in Computer Science

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