Developing a fuzzy OWL ontology for obesity related cancer domain Online publication date: Mon, 20-Mar-2017
by Mohammad Abdelrahman Elhefny; Mohammed Elmogy; Ahmed A. Elfetouh; Farid A. Badria
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 9, No. 2, 2017
Abstract: Obesity is associated with various diseases, particularly cardiovascular diseases, diabetes type 2, obstructive sleep apnea, certain types of cancer, osteoarthritis, and asthma. The knowledge of the obesity related cancer (ORC) domain is highly required to be represented in a structured and formalised shape. In this paper, we develop an ontology to represent ORC domain knowledge with its diseases, symptoms, diagnosis, and treatments. The proposed ontology is based on the Web Ontology Language (OWL 2) integrated with the fuzzy logic. The fuzzy developed ontology handles the overlapping concepts, ingesting more concepts, and copes with the linguistic domain variables, which were not possible using the regular ontologies. It allows the users to query the fuzzy Dl reasoner for element and answer them with the fuzzy ontology. By developing the fuzzy ORC ontology, it is expected to be a good practice for the ontologists and knowledge engineers.
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