Among the inferences studied in Description Logics (DLs), induction has been paid increasing attention over the last decade. Indeed, useful non-standard reasoning tasks can be based on the inductive inference. Among them, Concept Learning is about the automated induction of a description for a given concept starting from classified instances of the concept. In this paper we present a formal characterization of Concept Learning in DLs which relies on recent results in Knowledge Representation and Machine Learning.
A Formal Characterization of Concept Learning in Description Logics
LISI, Francesca Alessandra
2012-01-01
Abstract
Among the inferences studied in Description Logics (DLs), induction has been paid increasing attention over the last decade. Indeed, useful non-standard reasoning tasks can be based on the inductive inference. Among them, Concept Learning is about the automated induction of a description for a given concept starting from classified instances of the concept. In this paper we present a formal characterization of Concept Learning in DLs which relies on recent results in Knowledge Representation and Machine Learning.File in questo prodotto:
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