The use of background knowledge is one of the distinguishing features of ILP with respect to other approaches to machine learning. Yet the representation formalisms traditionally chosen for the background knowledge in ILP seem to ignore the latest developments in Knowledge Engineering such as standard languages for ontologies. In this paper we present a case study that shows how current ILP systems can be made compliant with these standards in order to fulfill the expressive requirements of emerging application areas like the Semantic Web.
ILP meets Knowledge Engineering: A Case Study
LISI, Francesca Alessandra;ESPOSITO, Floriana
2005-01-01
Abstract
The use of background knowledge is one of the distinguishing features of ILP with respect to other approaches to machine learning. Yet the representation formalisms traditionally chosen for the background knowledge in ILP seem to ignore the latest developments in Knowledge Engineering such as standard languages for ontologies. In this paper we present a case study that shows how current ILP systems can be made compliant with these standards in order to fulfill the expressive requirements of emerging application areas like the Semantic Web.File in questo prodotto:
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