We show how to convert OWL Class Expressions to SPARQL queries where the instances of that concept are with a specific ABox equal to the SPARQL query result. Furthermore, we implement and integrate our converter into the CELOE algorithm (Class Expression Learning for Ontology Engineering), where it replaces the position of a traditional OWL reasoner. This will foster the application of structured machine learning to the Semantic Web, since most data is readily available in triple stores. We provide experimental evidence for the usefulness of the bridge. In particular, we show that we can improve the run time of machine learning approaches by several orders of magnitude
The paper presents an approach for optimizing the evaluation of SPARQL queries over OWL ontologies ...
Lightweight ontologies in the formof RDF vocabularies such as SIOC, FOAF, vCard, etc. are increasing...
Abstract. The paper presents an approach for optimizing query answering algo-rithms that are based o...
Abstract. The vision of the Semantic Web is to make use of semantic representations on the largest p...
Abstract. The vision of the Semantic Web is to make use of semantic representations on the largest p...
Linked Open Data community is constantly producing new repositories that store information from dif...
Exploiting the complex structure of relational data enables to build better models by taking into ac...
While the number of knowledge bases in the Semantic Web increases, the main-tenance and creation of ...
We extend the Semantic Web query language SPARQL by defining the semantics of SPARQL queries under t...
Abstract. We extend the Semantic Web query language SPARQL by defining the semantics of SPARQL queri...
Exploiting the complex structure of relational data enables to build better models by taking into ac...
In this article the authors discuss the challenges of performing reasoning on large scale RDF datase...
We present LSQ, an algorithm learning SPARQL queries from a subset of expected results. The algorith...
In this article the authors discuss the challenges of performing reasoning on large scale RDF datase...
Solving problems raised by heterogeneous ontologies can be achieved by matching the ontologies and...
The paper presents an approach for optimizing the evaluation of SPARQL queries over OWL ontologies ...
Lightweight ontologies in the formof RDF vocabularies such as SIOC, FOAF, vCard, etc. are increasing...
Abstract. The paper presents an approach for optimizing query answering algo-rithms that are based o...
Abstract. The vision of the Semantic Web is to make use of semantic representations on the largest p...
Abstract. The vision of the Semantic Web is to make use of semantic representations on the largest p...
Linked Open Data community is constantly producing new repositories that store information from dif...
Exploiting the complex structure of relational data enables to build better models by taking into ac...
While the number of knowledge bases in the Semantic Web increases, the main-tenance and creation of ...
We extend the Semantic Web query language SPARQL by defining the semantics of SPARQL queries under t...
Abstract. We extend the Semantic Web query language SPARQL by defining the semantics of SPARQL queri...
Exploiting the complex structure of relational data enables to build better models by taking into ac...
In this article the authors discuss the challenges of performing reasoning on large scale RDF datase...
We present LSQ, an algorithm learning SPARQL queries from a subset of expected results. The algorith...
In this article the authors discuss the challenges of performing reasoning on large scale RDF datase...
Solving problems raised by heterogeneous ontologies can be achieved by matching the ontologies and...
The paper presents an approach for optimizing the evaluation of SPARQL queries over OWL ontologies ...
Lightweight ontologies in the formof RDF vocabularies such as SIOC, FOAF, vCard, etc. are increasing...
Abstract. The paper presents an approach for optimizing query answering algo-rithms that are based o...