Abstract
Clearly, ontology components are distinguished depending on features of inexactitudes and uncertainties. Such shortcomings are mostly the outcome an indistinct inaccurate semantic lingual representation, supplied by professionals. So as to tackle this lack of exactness issue, the notion of ”fuzziness” has to be considered. In this respect, fuzzy ontologies have been shown to be useful tools to represent specific knowledge (crisp and fuzzy) and reasoning over it. Thus, an advanced fuzzy ontology called the COVID-19 Fuzzy Ontology (CFO) is exhibited in this work. The latter licenses a semantically meaningful representation of fuzzy crusty medical data particulars related to the diagnosis of COVID-19. The CFO also takes into account the imprecise aspects associated to the induced knowledge of this disease. The CFO is grounded from a domain ontology about COVID-19. The evaluation of the CFO ontology shows that it is accurate, consistent, and that it covers COVID-19 terminologies.
Published Version
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