Authors:
Ishak Riali
;
Messaouda Fareh
and
Hafida Bouarfa
Affiliation:
LRDSI Laboratory, Faculty of Science, University Blida 1, Soumaa BP 270, Blida and Algeria
Keyword(s):
Fuzzy Ontologies, Fuzzy Bayesian Networks, Uncertainty, Vagueness, Semantic Web.
Related
Ontology
Subjects/Areas/Topics:
Advanced Applications of Fuzzy Logic
;
Artificial Intelligence and Decision Support Systems
;
Cloud Computing
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Semantic Web Technologies
;
Services Science
;
Software Agents and Internet Computing
;
Software Engineering
Abstract:
Today, there is a critical need to develop new solutions that enable classical ontologies to deal with uncertain knowledge, which is inherently attached to the most of the real world’s problems. For that need, several solutions have been proposed; one of them is based on fuzzy logic. Fuzzy ontologies were proposed as candidate solutions based on fuzzy logic. Indeed, they propose a formal representation and reason in presence of vague and imprecise knowledge in classical ontologies. Despite their indubitable success, they cannot handle the probabilistic knowledge, which is presented in most of the real world’s applications. To address this problem, this paper proposes a new solution based on fuzzy Bayesian networks, which aims at enhancing the expressivity of the fuzzy ontologies to handle probabilistic knowledge and benefits from the highlights of the fuzzy Bayesian networks to provide a fuzzy probabilistic reasoning based on vague knowledge stored in fuzzy ontologies.