Learning Composite Concepts

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Learning Composite Concepts
This paper proposes a framework to learn concepts from di erent kinds of observations. We de ne a language to describe meta-concepts, that represent the sets of possible concepts that can be the result of learning given a set of observations. The kinds of observations that we havestudied are subsumption,membershipand part-of. We exemplify the framework by showing how composite concepts can be learned in a speci c description logic and we show that previous machine learning approaches in description logics can be reformulated in our framework.
Patrick Lambrix, Pierpaolo Larocchia
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 1998
Where DLOG
Authors Patrick Lambrix, Pierpaolo Larocchia
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