Graph Structures for Knowledge Representation and Reasoning, 1st ed. 2015 4th International Workshop, GKR 2015, Buenos Aires, Argentina, July 25, 2015, Revised Selected Papers Lecture Notes in Artificial Intelligence Series
Coordonnateurs : Croitoru Madalina, Marquis Pierre, Rudolph Sebastian, Stapleton Gem
This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2015, held in Buenos Aires, Argentina, in July 2015, associated with IJCAI 2015, the 24th International Joint Conference on Artificial Intelligence. The 9 revised full papers presented were carefully reviewed and selected from 10 submissions. 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: argumentation; conceptual graphs; RDF; and representations of constraint satisfaction problems.
Designing a Knowledge Representation Tool for Subject Matter Structuring.- Aligning Experientially Grounded Ontologies using Language Games.- An overview of argumentation frameworks for decision support.- Learning Optimal Bayesian Networks with DAG Graphs.- Combinatorial results on directed hypergraphs for the SAT problem.- Conceptual Graphs for Formally Managing and Discovering Complementary Competences.- Subjective Networks: Perspectives and Challenges.- RDF-SQ: Mixing Parallel and Sequential Computation For Top-down OWL RL Inference.- Bring User Interest to Related Entity Recommendation.
Date de parution : 02-2016
Ouvrage de 155 p.
15.5x23.5 cm
Thèmes de Graph Structures for Knowledge Representation and Reasoning :
Mots-clés :
bayesian networks; decision support systems; multi-agent learning; probabilistic reasoning; semantic Web; graph theory; hypergraphs; knowledge reasoning; knowledge representation; ontology engineering; OWL; probabilistic representations; probability; reasoning about belief and knowledge; recommender systems; resource description framework; semantic Web description languages; statistics; theorem proving and sat solving; Web ontology language