The increasing amount of information to be managed in knowledge-based systems has promoted, on one hand, the exploitation of machine learning for the automated acquisition of knowledge and, on the other hand, the adoption of object-oriented representation models for easing the maintenance. In this context, adopting tech- niques for structuring knowledge representation in ma- chine learning seems particularly appealing. Inductive Logic Programming (ILP) is a promising ap- proach for the automated discovery of rules in knowl- edge based systems. We propose an object-oriented ex- tension of ILP employing multi-theory logic programs as the representation language. We dene a new learn- ing problem and propose the corresponding learning algorithm. Our approach enables ILP to benet of object-oriented domain modelling in the learning pro- cess, such as allowing structured domains to be directly mapped onto program constructs, or easing the man- agement of large knowledge bases.

Adopting an object-oriented data model in Inductive Logic Programming

MILANO, Michela;RIGUZZI, Fabrizio
1999

Abstract

The increasing amount of information to be managed in knowledge-based systems has promoted, on one hand, the exploitation of machine learning for the automated acquisition of knowledge and, on the other hand, the adoption of object-oriented representation models for easing the maintenance. In this context, adopting tech- niques for structuring knowledge representation in ma- chine learning seems particularly appealing. Inductive Logic Programming (ILP) is a promising ap- proach for the automated discovery of rules in knowl- edge based systems. We propose an object-oriented ex- tension of ILP employing multi-theory logic programs as the representation language. We dene a new learn- ing problem and propose the corresponding learning algorithm. Our approach enables ILP to benet of object-oriented domain modelling in the learning pro- cess, such as allowing structured domains to be directly mapped onto program constructs, or easing the man- agement of large knowledge bases.
1999
Logic Programming; Inductive Logic Programming; Multi-theory Logic Programming
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/1195311
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact