Semantic information retrieval based on fuzzy ontology for intelligent transportation systems

Abstract

Information retrieval is the important work for traffic information service in Intelligent Transportation Systems (ITS). Ontology-based semantic information retrieval is a hotspot of current research. In order to achieve fuzzy semantic retrieval, this paper applies a fuzzy ontology framework to information retrieval system for ITS. The framework includes three parts: concepts, properties of concepts and values of properties, in which property's value can be either standard data type or linguistic values (i.e. fuzzy concepts). The semantic query expansion is constructed by order relation, equivalence relation, inclusion relation and complement relation between fuzzy concepts defined in fuzzy linguistic variable ontologies. The application to retrieve traffic accident information shows that the framework can overcome the localization of other fuzzy ontology models, and this research facilitates the semantic retrieval of traffic information through fuzzy concepts in ITS on the Semantic Web.