Understanding and improving ontology reasoning efficiency through learning and ranking
Ontologies are the fundamental building blocks of the Semantic Web and Linked Data.
Reasoning is critical to ensure the logical consistency of ontologies, and to compute inferred …
Reasoning is critical to ensure the logical consistency of ontologies, and to compute inferred …
A machine learning approach for optimizing heuristic decision‐making in Web Ontology Language reasoners
Abstract Description logics (DLs) are formalisms for representing knowledge bases of
application domains. The Web Ontology Language (OWL) is a syntactic variant of a very …
application domains. The Web Ontology Language (OWL) is a syntactic variant of a very …
RakSOR: Ranking of ontology reasoners based on predicted performances
N Alaya, SB Yahia, M Lamolle - 2016 IEEE 28th International …, 2016 - ieeexplore.ieee.org
Over the last decade, several ontology reasoners have been proposed to overcome the
computational complexity of inference tasks on expressive ontology languages …
computational complexity of inference tasks on expressive ontology languages …
Multi-label based learning for better multi-criteria ranking of ontology reasoners
N Alaya, M Lamolle, S Ben Yahia - The Semantic Web–ISWC 2017: 16th …, 2017 - Springer
A growing number of highly optimized reasoning algorithms have been developed to allow
inference tasks on expressive ontology languages such as OWL (DL). Nevertheless, there is …
inference tasks on expressive ontology languages such as OWL (DL). Nevertheless, there is …
Ranking with Ties of OWL Ontology Reasoners Based on Learned Performances
N Alaya, SB Yahia, M Lamolle - … 2015, Lisbon, Portugal, November 12-14 …, 2016 - Springer
Over the last decade, several ontology reasoners have been proposed to overcome the
computational complexity of inference tasks on expressive ontology languages such as …
computational complexity of inference tasks on expressive ontology languages such as …
[PDF][PDF] Efficient Reasoner Performance Prediction using Multi-label learning.
A Makwana - ISIC, 2021 - ceur-ws.org
The reasoner is the mechanism for interpreting the semantics of web ontology language.
This paper focuses on reasoner performance study and predicting it by use of machine …
This paper focuses on reasoner performance study and predicting it by use of machine …
[PDF][PDF] Optimisation of tableau-based reasoning systems for expressive description logics
A Steigmiller - 2016 - oparu.uni-ulm.de
Logic-based knowledge representation formalisms, such as Description Logics, constitute
the basis of well-known ontology languages, eg, the Web Ontology Language, and, thus, are …
the basis of well-known ontology languages, eg, the Web Ontology Language, and, thus, are …
Uncertainties associated with restoring natural alignment to previously straightened streams
K Agazi, PA Johnson, TM Heil - Proceedings of 3rd …, 1995 - ieeexplore.ieee.org
Three models are currently used by the Maryland State Highway Administration for
designing meanders on stream restoration projects. The first model is based on the …
designing meanders on stream restoration projects. The first model is based on the …
A Machine Learning Approach for Optimizing Heuristic Decision-making in OWL Reasoners
R Mehri-Dehnavi - 2019 - spectrum.library.concordia.ca
Description Logics (DLs) are formalisms for representing knowledge bases of application
domains. TheWeb Ontology Language (OWL) is a syntactic variant of a very expressive …
domains. TheWeb Ontology Language (OWL) is a syntactic variant of a very expressive …