Fuzzy ontologies for handling uncertainties and inconsistencies in domain knowledge description

Ontologies represent a method of formally expressing a shared understanding of information, and have paved the way for sharing concepts across applications in an unambiguous way. However, these ontologies are assumed to be hand-crafted, pre-defined structures with crisp concept descriptions and inter-concept relations. Crisp definitions however are not sufficient for real-world applications like ontology-based information extraction from unstructured text. In this paper we propose an enhancement of the ontology structure to a fuzzy ontology, which provides a mechanism to store imprecise concept definitions. The proposed fuzzy ontology framework can also help in ascertaining similarities and dissimilarities of concept definitions across distributed ontologies representing the same domain. Our design of fuzzy ontology is motivated by fuzzy set theoretic representation and reasoning, and is entirely different from other fuzzy ontology designs, which use only co-occurrence of concepts to determine their closeness. We have cited examples from various domains to show the necessity and capability of the structure in representing real-world knowledge.