Abstract
This paper proposes the use of description logics as a representational framework for learning composite concepts. Description logics are restricted variants of first-order logic providing a form of logical bias that dates back to semantic networks. Some recent work investigates concept learning in the context of these formalisms. Also, having recognized the importance of part-whole hierarchies in commonsense reasoning, researchers have started to incorporate part-of reasoning into description logics. In our approach we represent composite concepts in such a formalism. On one hand we have a relatively rich representation language with an infinite space of possible concepts. On the other hand we have special constructs for handling part-of relations that can be used in the learning algorithm to reduce the overall search space.
The authors would like to thank Nada Lavrač for useful comments on a previous draft. The first author is supported by grant 95-176 from the Swedish Research Council for Engineering Sciences (TFR).
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© 1996 Springer-Verlag Berlin Heidelberg
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Lambrix, P., Maleki, J. (1996). Learning composite concepts in description logics: A first step. In: Raś, Z.W., Michalewicz, M. (eds) Foundations of Intelligent Systems. ISMIS 1996. Lecture Notes in Computer Science, vol 1079. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61286-6_132
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DOI: https://doi.org/10.1007/3-540-61286-6_132
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