Crisp Representations And Reasoning For Fuzzy Ontologies

Classical ontologies are not suitable to represent imprecise nor uncertain pieces of information. Fuzzy Description Logics were born to represent the former type of knowledge, but they require an appropriate fuzzy language to be agreed on and an important number of available resources to be adapted. This paper faces these problems by presenting a reasoning preserving procedure to obtain a crisp representation for a fuzzy extension of the logic SROIQ(D) which includes fuzzy nominals and trapezoidal membership functions, and uses Godel implication in the semantics of fuzzy concept and role sub-sumption. This reduction makes it possible to reuse a crisp representation language as well as currently available reasoners. Our procedure is optimized with respect to related work, reducing the size of the resulting knowledge base. Finally, we also suggest some further optimizations before applying crisp reasoning.