CINECA IRIS Institutional Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishThe 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.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
| Titolo: | ILP meets Knowledge Engineering: A Case Study | |
| Autori: | ||
| Data di pubblicazione: | 2005 | |
| Rivista: | ||
| 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. | |
| Handle: | http://hdl.handle.net/11586/10971 | |
| ISBN: | 978-3-540-28177-1 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
http://hdl.handle.net/11586/10971
Copyright © 2021