Developing a fuzzy OWL ontology for obesity related cancer domain. (2017)

• Record Type: Journal Article
• Authors: Elhefny, Mohammad Abdelrahman; Elmogy, Mohammed; Elfetouh, Ahmed A.; Badria, Farid A.
• Is Part Of: International journal of medical engineering and informatics. Volume 9:Number 2(2017)
• Page Start: 162
• Page End: 187
• Publication Date: 2017
• Subjects: fuzzy ontology -- obesity related cancer -- ORC domain knowledge -- Web Ontology Language 2 -- OWL2 -- knowledge representation -- disease ontology -- fuzzy logic; 610.2805
• Languages: English
• ISSNs: 1755-0653

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.