Graph Structures for Knowledge Representation and Reasoning
5th International Workshop, GKR 2017, Melbourne, VIC, Australia, August 21, 2017, Revised Selected Papers
Published on 21. March 2018
Book
Paperback/Softback
VII, 139 pages
978-3-319-78101-3 (ISBN)
Description
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.
More details
Series
Edition
1st ed. 2018
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
VII, 139 p.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
238 gr
ISBN-13
978-3-319-78101-3 (9783319781013)
DOI
10.1007/978-3-319-78102-0
Schweitzer Classification
Other editions
Additional editions
Madalina Croitoru | Pierre Marquis | Sebastian Rudolph
Graph Structures for Knowledge Representation and Reasoning
5th International Workshop, GKR 2017, Melbourne, VIC, Australia, August 21, 2017, Revised Selected Papers
E-Book
03/2018
Springer
€42.79
Available for download
Content
Exploring, Reasoning With and Validating Directed Graphs by Applying Formal Concept Analysis to Conceptual Graphs.- Subjective Bayesian Networks and Human-in-the-Loop Situational Understanding.- Counting and Conjunctive Queries in the Lifted Junction Tree Algorithm.- Representing and Reasoning about Logical Network Topologies.- From Enterprise Concepts to Formal Concepts: A University Case Study.- Visualizing ALC Using Concept Diagrams.- Graph Theoretical Properties of Logic Based Argumentation Frameworks: Proofs and General Results.