Add to ORKGWe propose a novel approach to performance prediction of OWL reasoners that selects suitable, small ontology subsets, and then extrapolates to the whole ontology. Our second contribution concerns ontology features: we report their high intercorrelation using PCA: the ontolo-gies basically differ in one or two features
Materialized knowledge bases perform inferencing when data is loaded into them, so that answering qu...
Within the context of ontology learning, we consider the problem of selecting candidate axioms throu...
In this article the authors discuss the challenges of performing reasoning on large scale RDF datase...
Abstract. We propose a novel approach for performance prediction of OWL reasoners. It selects suitab...
We propose a novel approach to performance prediction of OWL reasoners. The existing strategies take...
Abstract. A key issue in semantic reasoning is the computational com-plexity of inference tasks on e...
For expressive ontology languages such as OWL 2 DL, classification is a computationally expensive ta...
In this article, the authors introduce the notion of ABox intensity in the context of predicting rea...
Ontology classification - the computation of subsumption hierarchies for classes and properties - is...
This paper provides a survey to and a comparison of state-of-the-art Semantic Web reasoners that suc...
International audienceWe address the problem of predicting a score for candidate axioms within the c...
This paper provides a survey to and a comparison of state-of-the-art Semantic Web reasoners that suc...
HermiT is the only reasoner we know of that fully supports the OWL 2 standard, and that correctly re...
Abstract. Predicting the performance of a tableau reasoner for an OWL ontology is generally hard. It...
AbstractSeveral techniques and applications have been proposed to aid the decision taking process in...
Materialized knowledge bases perform inferencing when data is loaded into them, so that answering qu...
Within the context of ontology learning, we consider the problem of selecting candidate axioms throu...
In this article the authors discuss the challenges of performing reasoning on large scale RDF datase...
Abstract. We propose a novel approach for performance prediction of OWL reasoners. It selects suitab...
We propose a novel approach to performance prediction of OWL reasoners. The existing strategies take...
Abstract. A key issue in semantic reasoning is the computational com-plexity of inference tasks on e...
For expressive ontology languages such as OWL 2 DL, classification is a computationally expensive ta...
In this article, the authors introduce the notion of ABox intensity in the context of predicting rea...
Ontology classification - the computation of subsumption hierarchies for classes and properties - is...
This paper provides a survey to and a comparison of state-of-the-art Semantic Web reasoners that suc...
International audienceWe address the problem of predicting a score for candidate axioms within the c...
This paper provides a survey to and a comparison of state-of-the-art Semantic Web reasoners that suc...
HermiT is the only reasoner we know of that fully supports the OWL 2 standard, and that correctly re...
Abstract. Predicting the performance of a tableau reasoner for an OWL ontology is generally hard. It...
AbstractSeveral techniques and applications have been proposed to aid the decision taking process in...
Materialized knowledge bases perform inferencing when data is loaded into them, so that answering qu...
Within the context of ontology learning, we consider the problem of selecting candidate axioms throu...
In this article the authors discuss the challenges of performing reasoning on large scale RDF datase...