Graph Structures for Knowledge Representation and Reasoning Third International Workshop, GKR 2013, Beijing, China, August 3, 2013. Revised Selected Papers

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 Artif...

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Published inGraph Structures for Knowledge Representation and Reasoning Third International Workshop, GKR 2013, Beijing, China, August 3, 2013. Revised Selected Papers Vol. 8323; pp. 1 - 211
Main Authors GKR, Croitoru, Madalina
Format eBook Book Conference Proceeding
LanguageEnglish
Published Cham Springer Nature 2014
Springer
Springer International Publishing AG
Springer International Publishing
Edition1
SeriesLecture Notes in Computer Science
Subjects
Artificial Intelligence
Computer Science
Data structures (Computer science)-Congresses
Discrete Mathematics in Computer Science
GKR
Graph structures
Graph theory
Graph theory > Congresses
Knowledge representation (Information theory)
Knowledge representation (Information theory) > Congresses
Logic in Computer Science
Mathematical Logic and Formal Languages
Reasoning
Reasoning > Congresses
Special computer methods
Discrete Mathematics in Computer Science
Artificial Intelligence
Mathematical Logic and Formal Languages
Online AccessGet full text
ISBN9783319045344
3319045342
9783319045337
3319045334
ISSN0302-9743
1611-3349
DOI10.1007/978-3-319-04534-4

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Abstract 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.
AbstractList Versatile and effective techniques for knowledge representation and reasoning (KRR) are essential for the development of successful intelligent systems. Many representatives of next generation KRR systems are based on graph-based knowledge representation formalisms and leverage graph-theoretical notions and results. The goal of the workshop series on Graph Structures for Knowledge Representation and Reasoning (GKR) is to bring together the researchers involved in the development and application of graph-based knowledge representation formalisms and reasoning techniques. This volume contains revised selected papers of the third edition of GKR, which took place in Beijing, China on August 3, 2013. Like the previous editions, held in Pasadena, USA (2009), and in Barcelona, Spain (2011), the workshop was associated with IJCAI (the International Joint Conference on Artificial Intelligence), thus providing the perfect venue for a rich and valuable exchange. The scientific program of this workshop included many topics related to graph-based knowledge representation and reasoning such as representations of constraint satisfaction problems, formal concept analysis, conceptual graphs, argumentation frameworks and many more. All in all, the third edition of the GKR workshop was very successful. The papers coming from diverse fields all addressed various issues for knowledge representation and reasoning and the common graph-theoretic background allowed to bridge the gap between the different communities. This made it possible for the participants to gain new insights and inspiration. We are grateful for the support of IJCAI and we would also like to thank the Program Committee of the workshop for their hard work in reviewing papers and providing valuable guidance to the contributors. But, of course, GKR 2013 would not have been possible without the dedicated involvement of the contributing authors and participants.
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.
Author GKR
Croitoru, Madalina
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Croitoru, Madalina
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Mathematical Logic and Formal Languages
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PublicationTitle Graph Structures for Knowledge Representation and Reasoning Third International Workshop, GKR 2013, Beijing, China, August 3, 2013. Revised Selected Papers
PublicationYear 2014
2013
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Springer International Publishing AG
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Snippet This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Graph Structures for Knowledge Representation...
Versatile and effective techniques for knowledge representation and reasoning (KRR) are essential for the development of successful intelligent systems. Many...
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StartPage 1
SubjectTerms Artificial Intelligence
Computer Science
Data structures (Computer science)-Congresses
Discrete Mathematics in Computer Science
GKR
Graph structures
Graph theory
Graph theory -- Congresses
Knowledge representation (Information theory)
Knowledge representation (Information theory) -- Congresses
Logic in Computer Science
Mathematical Logic and Formal Languages
Reasoning
Reasoning -- Congresses
Special computer methods
Subtitle Third International Workshop, GKR 2013, Beijing, China, August 3, 2013. Revised Selected Papers
TableOfContents Intro -- Preface -- Organization -- Table of Contents -- Implementation of a Knowledge Representation and Reasoning Tool Using Default Rules for a Decision Support System in Agronomy Applications -- 1 Introduction -- 2 Structuring CFTC Knowledge Using Freeplane -- 3 Structuring Knowledge of CTFC with CoGui -- 3.1 The Conceptual Graph Formalism -- 4 End-User Application -- 5 Conclusion -- References -- Information Revelation Strategies in Abstract Argument Frameworks Using Graph Based Reasoning -- 1 Introduction -- 2 Bonds -- 3 Identifying Bonds -- 4 Discussion and Conclusions -- References -- Different Classes of Graphs to Represent Microstructures for CSPs -- 1 Preliminaries -- 2 Microstructures for Non Binary CSPs -- 2.1 Microstructure Based on Dual Representation -- 2.2 Microstructure Based on Hidden Variable -- 2.3 Microstructure Based on Mixed Encoding -- 2.4 Comparisons between Microstructures -- 3 Some Results Deduced from Microstructures -- 3.1 Microstructures and Number of Cliques -- 3.2 Microstructures and BTP -- 3.3 Microstructures and "0-1-all" Constraints -- 4 Conclusion -- References -- Finding Maximal Common Sub-parse Thickets for Multi-sentence Search -- 1 Introduction -- 2 Parse Thickets and Their Graph Representation -- 2.1 Introducing Parse Thickets -- 2.2 Finding Similarity between Two Paragraphs of Text -- 2.3 Arcs of Parse Thicket Based on Theories of Discourse -- 2.4 Phrase-Level Generalization -- 2.5 Forming Thicket Phrases for Generalization -- 2.6 Sentence-Level Generalization Algorithm -- 3 Computing Maximal Common Sub-PTs -- 4 Architecture of PT Processing System -- 5 Algorithms and Scalability of the Approach -- 6 Evaluation of Multi-sentence Search -- 7 Conclusions -- References -- Intrusion Detection with Hypergraph-Based Attack Models -- 1 Introduction -- 2 Modeling Attack Processes
2.1 Tracking Attack Trajectories -- 3 Consistency of Attack Models -- 4 The Intrusion Detection Problem -- 4.1 Scaling Intrusion Detection -- 5 Type Hierarchies -- 6 Related Work -- 7 Conclusions and Future Work -- References -- Structural Consistency: A New Filtering Approach for Constraint Networks -- 1 Introduction -- 2 Preliminaries -- 3 Structural Consistency -- 3.1 w-SC Consistency -- 3.2 Filtering -- 4 Relations with Other Consistencies -- 5 Experiments -- 5.1 Experimental Protocol -- 5.2 AC/SAC vs w-SC -- 5.3 Complementarity and Combinations of AC/SAC and w-SC -- 6 Discussion and Conclusion -- References -- Inductive Triple Graphs: A Purely Functional Approach to Represent RDF -- 1 Introduction -- 2 Inductive Graphs -- 2.1 General Inductive Graphs -- 2.2 Inductive Triple Graphs -- 2.3 Representing Graphs at Triple Graphs -- 2.4 Algebra of Graphs -- 3 The RDF Model -- 4 Functional Representation of RDF Graphs -- 5 Implementation -- 5.1 Implementation in Haskell -- 5.2 Implementation in Scala -- 6 Related Work -- 7 Conclusions -- References -- A Depth-First Branch and Bound Algorithm for Learning Optimal Bayesian Networks -- 1 Introduction -- 2 Background -- 2.1 Learning Bayesian Network Structures -- 2.2 Shortest-Path Perspective -- 2.3 Finding Optimal Parents -- 2.4 Finding the Shortest Path -- 3 A Depth-First Branch and Bound Algorithm -- 3.1 Reverse Order Graph -- 3.2 Branch and Bound -- 3.3 Duplicate Detection and Repair -- 3.4 Depth-First Search -- 4 Experiments -- 4.1 Comparison of Anytime Behavior -- 4.2 Comparison of Running Time -- 5 Conclusion -- 6 Appendix -- References -- Learning Bayes Nets for Relational Data with Link Uncertainty -- 1 Introduction -- 2 Related Work -- 3 Background and Notation -- 3.1 Bayes Nets for Relational Data -- 3.2 Databases and Table Joins -- 4 Bayes Net Learning With Link Correlation Analysis
4.1 Flat Search -- 4.2 Hierarchical Search -- 5 Evaluation -- 5.1 Results -- 6 Computing Data Join Tables -- 7 Conclusion -- References -- Concurrent Reasoning with Inference Graphs -- 1 Introduction -- 2 Propositional Graphs -- 3 Inference Graphs -- 3.1 Messages -- 3.2 Rule Node Inference -- 3.3 Inference Segments -- 4 Concurrent Reasoning -- 4.1 Scheduling Heuristics -- 5 An Illustrative Example -- 6 Evaluation -- 6.1 Backward Inference -- 6.2 Forward Inference -- 7 Conclusions -- References -- Formal Concept Analysis over Graphs and Hypergraphs -- 1 General Introduction -- 1.1 Formal Concept Analysis -- 1.2 Importance of Graphs and Hypergraphs -- 2 Theoretical Background -- 2.1 Graphs and Hypergraphs -- 2.2 Mathematical Morphology on Sets -- 2.3 The Algebra of Graphs and Hypergraphs -- 3 Contexts and Concepts for Pre-orders -- 3.1 Relations between Preorders -- 3.2 Defining Formal Concepts -- 4 Application Domains -- 5 Conclusions and Further Work -- References -- Automatic Strengthening of Graph-Structured Knowledge Bases -- 1 Introduction -- 2 Graph Structured Knowledge Bases - The Logical Perspective -- 2.1 Definitions -- 2.2 Constructing a Strengthened GSKB -- 3 Graph Structured Knowledge Bases - The Graph-Based Perspective -- 3.1 Definitions -- 3.2 Concept Graph Morphisms and Inherited Atoms -- 3.3 Concept Patchworks and Coverings -- 3.4 Computation of a Covering -- 3.5 The Implementation -- 4 Evaluation -- 5 Related Work -- 6 Conclusions and Outlook -- References -- Author Index
Title Graph Structures for Knowledge Representation and Reasoning
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