Graph Structures for Knowledge Representation and Reasoning
Springer International Publishing (Verlag)
9783319287010 (ISBN)
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 SubjectMatter Structuring.- Aligning Experientially Grounded Ontologies using LanguageGames.- An overview of argumentation frameworks for decision support.- LearningOptimal Bayesian Networks with DAG Graphs.- Combinatorial results on directedhypergraphs for the SAT problem.- Conceptual Graphs for Formally Managing andDiscovering Complementary Competences.- Subjective Networks: Perspectives andChallenges.- RDF-SQ: Mixing Parallel and Sequential Computation For Top-downOWL RL Inference.- Bring User Interest to Related Entity Recommendation.
| Erscheinungsdatum | 10.02.2016 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | VII, 155 p. 48 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | artificial intelligence (incl. robotics) • Bayesian networks • Computer Science • Decision Support Systems • graph theory • Hypergraphs • knowledge reasoning • Knowledge Representation • Knowledge Representation and Reasoning • Multi-Agent Learning • ontology engineering • OWL • Probabilistic Reasoning • probabilistic representations • Probability • probability and statistics • reasoning about belief and knowledge • Recommender Systems • resource description framework • Resource Description Framework (RDF) • semantic web • semantic web description languages • Statistics • theorem proving and SAT solving • Web Ontology Language • Web Ontology Language (OWL) |
| ISBN-13 | 9783319287010 / 9783319287010 |
| Zustand | Neuware |
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