Fuzzy Probabilistic Ontology Approach: A Hybrid Model for Handling Uncertain Knowledge in Ontologies

Ishak Riali, Messaouda Fareh and Hafida Bouarfa
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Ishak Riali: LRDSI Laboratory, Faculty of Science, University Blida 1, Soumaa BP 270, Blida, Algeria
Messaouda Fareh: LRDSI Laboratory, Faculty of Science, University Blida 1, Soumaa BP 270, Blida, Algeria
Hafida Bouarfa: LRDSI Laboratory, Faculty of Science, University Blida 1, Soumaa BP 270, Blida, Algeria

International Journal on Semantic Web and Information Systems (IJSWIS), 2019, vol. 15, issue 4, 1-20

Abstract: In spite of the undeniable success of the ontologies, where they have been widely applied successfully to represent the knowledge in lots of real-world problems, they cannot represent and reason with uncertain knowledge which inherently appears in most domains. To cope with this issue, this article presents a new approach for dealing with rich-uncertainty domains. In fact, it is mainly based on integrating hybrid models which combine both fuzzy logic and Bayesian networks. On the other hand, the Fuzzy multi-entity Bayesian network (FzMEBN) proposed as a hybrid model which enhances the classical multi-entity Bayesian network using fuzzy logic, it can be used to represent and reason with probabilistic and vague knowledge simultaneously. Thus, as a language belongs to the proposed approach, this study proposes a promising solution to overcome the weakness of the Probabilistic Ontology Web Language (PR-OWL) based on FzMEBN to allow dealing with vague and probabilistic knowledge in ontologies. The proposed extension is evaluated with a case study in the medical field (diabetes diseases).

Date: 2019
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