Mapping Crisp Structural Semantic Similarity Measures to Fuzzy Context: A Generic Approach

ntology-based similarity measures have received much importance in recent years. In many real-world cases, the domain considered in the ontological similarity assessment consists of uncertainty or incomplete information. Such vagueness has led to the successful implementation of fuzzy ontology (FO)-based similarity measures. Despite various applications of FO-based similarity measures, limited methods have so far been proposed for this purpose. Accordingly, this paper presents a generic model for semantic similarity assessment based on a fuzzy ontology. The proposed approach relies on the broad literature of Crisp Ontology-based Structural Semantic Similarity Measures (CO-SSSM). It provides an approach for mapping CO-SSSMs to fuzzy context. Consequently, the proposed generic model can be applied to various CO-SSSMs to develop their corresponding FO-SSSMs. In this regard, as an empirical investigation, four of the common CO-SSSMs were selected, their equivalent FO-SSSMs were developed by means of the proposed approach, and the accuracy of their similarity assessment was compared with each other. The results show the power of FO-SSSMs in describing the relations between concepts and their superiority over CO-SSSMs.