Abstract
Computing least common subsumers in description logics is an important reasoning service useful for a number of applications. As shown in the literature, it can, for instance, be used for similarity-based information retrieval where information retrieval is performed on the basis of the similarities of user-specified examples. In this article, we first show that, for crisp DLs, in certain cases the set of retrieved information items can be too large. Then we propose a probabilistic least common subsumer operation based on a probabilistic extension of the description logic language ALN. We show that by this operator the amount of retrieved data can be reduced avoiding information flood.
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© 1999 Springer-Verlag Berlin Heidelberg
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Mantay, T., Möller, R., Kaplunova, A. (1999). Computing Probabilistic Least Common Subsumers in Description Logics. In: Burgard, W., Cremers, A.B., Cristaller, T. (eds) KI-99: Advances in Artificial Intelligence. KI 1999. Lecture Notes in Computer Science(), vol 1701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48238-5_7
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DOI: https://doi.org/10.1007/3-540-48238-5_7
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