OWL ontologies are nowadays a quite popular way to describe structured knowledge in terms of classes, relations among classes and class instances. In this paper, given an OWL target class T, we address the problem of inducing EL(D) concept descriptions that describe sufficient conditions for being an individual instance of T. To do so, we use a FOIL-based method with a probabilistic candidate ensemble estimation. We illustrate its effectiveness by means of an experimentation.

pFOIL-DL: Learning (Fuzzy) EL Concept Descriptions from Crisp OWL Data Using a Probabilistic Ensemble Estimation.

Straccia U;
2015

Abstract

OWL ontologies are nowadays a quite popular way to describe structured knowledge in terms of classes, relations among classes and class instances. In this paper, given an OWL target class T, we address the problem of inducing EL(D) concept descriptions that describe sufficient conditions for being an individual instance of T. To do so, we use a FOIL-based method with a probabilistic candidate ensemble estimation. We illustrate its effectiveness by means of an experimentation.
2015
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-1-4503-3196-8
Semantic Web
Fuzzy logic
OWL 2
Learning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/295994
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