In different situations, information coming from different sources are often affected with uncertainty and imprecision. Representing such information generally gives rise to a prioritized (i.e. stratified) knowledge base. To reason with such prioritized knowledge in a principled way, we propose an extension of εL description logics within possibility theory, which provides a very natural framework to deal with ordinal, qualitative uncertainty, preferences and priorities. We first introduce the syntax and semantics of possibilistic εL, and then provide the main related reasoning tasks. We show in particular that these tasks remain tractable in possibilistic εL.
CITATION STYLE
Mohamed, R., Loukil, Z., & Bouraoui, Z. (2018). Qualitative-based possibilistic εL ontology. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11224 LNAI, pp. 552–559). Springer Verlag. https://doi.org/10.1007/978-3-030-03098-8_41
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