Graph Structures for Knowledge Representation and Reasoning

1. Front Matter

   Pages I-VII

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2. Extended Workshop Papers

   1. Front Matter

      Pages 1-1

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   2. Exploring, Reasoning with and Validating Directed Graphs by Applying Formal Concept Analysis to Conceptual Graphs

      • Simon Andrews, Simon Polovina

      Pages 3-28

   3. Subjective Bayesian Networks and Human-in-the-Loop Situational Understanding

      • Dave Braines, Anna Thomas, Lance Kaplan, Murat Şensoy, Jonathan Z. Bakdash, Magdalena Ivanovska et al.

      Pages 29-53

   4. Counting and Conjunctive Queries in the Lifted Junction Tree Algorithm

      • Tanya Braun, Ralf Möller

      Pages 54-72

   5. Representing and Reasoning About Logical Network Topologies

      • Shaun Voigt, Catherine Howard, Dean Philp, Christopher Penny

      Pages 73-83

   6. From Enterprise Concepts to Formal Concepts: A University Case Study

      • Jamie Caine, Simon Polovina

      Pages 84-96

3. Invited Contributions

   1. Front Matter

      Pages 97-97

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   2. Visualizing \(\mathcal {ALC}\) Using Concept Diagrams

      • Gem Stapleton, Aidan Delaney, Michael Compton, Peter Chapman

      Pages 99-117

   3. Graph Theoretical Properties of Logic Based Argumentation Frameworks: Proofs and General Results

      • Bruno Yun, Madalina Croitoru, Srdjan Vesic, Pierre Bisquert

      Pages 118-138

4. Back Matter

   Pages 139-139

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This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2017, held in Melbourne, VIC, Australia, in August 2017, associated with IJCAI 2017, the 26th International Joint Conference on Artificial Intelligence. The 7 revised full papers presented were reviewed and selected from 9 submissions. The contributions  address various issues for knowledge representation and reasoning and the common graph-theoretic background allows to bridge the gap between the different communities.

• Knowledge representation and reasoning
• Graph theory
• Reasoning about belief and knowledge
• Probabilistic reasoning
• Ontology engineering
• Theorem proving and SAT solving
• Decision support systems
• Probability and statistics
• Probabilistic representations
• Bayesian networks
• Hypergraphs
• Recommender systems
• Semantic web description languages
• Web Ontology Language (OWL)
• Multi-agent learning
• Knowledge based systems
• formal logic
• Semantics

• LIRMM, Montpellier Cedex 5, France

  Madalina Croitoru

• CRIL-CNRS and Université d’Artois, Lens, France

  Pierre Marquis

• Technische Universität Dresden, Dresden, Germany

  Sebastian Rudolph

• University of Brighton, Brighton, United Kingdom

  Gem Stapleton

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