Graph Structures for Knowledge Representation and Reasoning: Lecture Notes in Computer Science, cartea 9501
Editat de Madalina Croitoru, Pierre Marquis, Sebastian Rudolph, Gem Stapletonen Limba Engleză Paperback – 3 feb 2016
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.
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (2) | 315.22 lei 6-8 săpt. | |
| Springer – 3 feb 2016 | 315.22 lei 6-8 săpt. | |
| Springer International Publishing – 21 mar 2018 | 340.18 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783319287010
ISBN-10: 331928701X
Pagini: 164
Ilustrații: VII, 155 p. 48 illus. in color.
Dimensiuni: 155 x 235 x 10 mm
Greutate: 0.26 kg
Ediția:1st edition 2015
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 331928701X
Pagini: 164
Ilustrații: VII, 155 p. 48 illus. in color.
Dimensiuni: 155 x 235 x 10 mm
Greutate: 0.26 kg
Ediția:1st edition 2015
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Public țintă
ResearchCuprins
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.
Caracteristici
Includes supplementary material: sn.pub/extras