Fodor / Montali / Calvanese Rules and Reasoning
Erscheinungsjahr 2019
ISBN: 978-3-030-31095-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Third International Joint Conference, RuleML+RR 2019, Bolzano, Italy, September 16–19, 2019, Proceedings
E-Book, Englisch, 207 Seiten
Reihe: Programming and Software Engineering
ISBN: 978-3-030-31095-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book constitutes the proceedings of the International Joint Conference on Rules and Reasoning, RuleML+RR 2019, held in Bolzano, Italy, during September 2019. This is the third conference of a new series, joining the efforts of two existing conference series, namely “RuleML” (International Web Rule Symposium) and “RR” (Web Reasoning and Rule Systems).
The 10 full research papers presented together with 5 short technical communications papers were carefully reviewed and selected from 26 submissions.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Full Papers.- Finding New Diamonds: Temporal Minimal-World Query Answering over Sparse ABoxes.- Reasoning on DL-Lite with Defeasibility in ASP.- ODRL policy modelling and compliance checking.- Aligning, Interoperating, and Co-executing Air Traffic Control Rules Across PSOA RuleML and IDP.- An ASP-based Solution for Operating Room Scheduling with Beds Management.- EASE: Enabling Hardware Assertion Synthesis from English.- Formalizing Object-ontological Mapping Using F-logic.- Alternating Fixpoint Operator for Hybrid MKNF Knowledge Bases as an Approximator of AFT.- Efficient TBox Reasoning with Value Restrictions—Introducing the FLwer Reasoner.- Query Rewriting for DL Ontologies under the ICAR semantics.- Technical Communication Papers.- Complementing Logical Reasoning with Sub-Symbolic Commonsense.- Adding Constraint Tables to the DMN Standard: Preliminary Results.- Detecting "Slippery Slope" and other argumentative stances of opposition using Tree Kernels in monologic discourse.- Fuzzy Logic Programming for Tuning Neural Networks.- Querying Key-Value Stores Under Single-Key Constraints: Rewriting and Parallelization.
