A Semantic Approach for Handling Probabilistic Knowledge of Fuzzy Ontologies

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.