HyFOM Reasoner: Hybrid Integration of Fuzzy Ontology and Mamdani Reasoning

Abstract

Some real-world applications require representation and reasoning regarding imprecise or vague information. In this context, the appropriate combination of fuzzy ontologies and Mamdani fuzzy inference systems can provide meaningful inferences involving fuzzy rules and numerical property values. In general, this knowledge is not obtained through typical fuzzy ontology reasoning and can be relevant for some ontology reasoning tasks that depend on numerical property values. To address this issue, this paper proposes the HyFOM reasoner, which provides a hybrid integration of fuzzy ontology and Mamdani reasoning. A real-world case study involving the domain of food safety is presented, including comparative results with a state-of-the-art fuzzy description logic reasoner.