A MODEL FOR REPRESENTING VAGUE LINGUISTIC TERMS AND FUZZY RULES FOR CLASSIFICATION IN ONTOLOGIES
Cristiane A. Yaguinuma, Vinícius Ramos Toledo Ferraz, Marilde Terezinha Prado Santos, Heloisa A. Camargo, Tatiane Marques Nogueira · 2010
Ontologies have been successfully employed in applications that require semantic information processing. However, traditional ontologies are not able to express fuzzy or vague information, which often occurs in human vocabulary as well as in several application domains. In order to deal with such restriction, concepts of fuzzy set theory should be incorporated into ontologies so that it is possible to represent and reason over fuzzy or vague knowledge. In this context, this paper proposes a model for representing fuzzy ontologies covering fuzzy properties and fuzzy rules, and we also implement fuzzy reasoning methods such as classical and general fuzzy reasoning, aiming to support classification of new instances based on fuzzy rules.