Abstract
Ontology is the basis of sharing and reusing knowledge on the Semantic Web, and ontology-based semantic retrieval is a hotspot of current research. Fuzzy ontology is an extension of domain ontology for solving the uncertainty problems. To represent fuzzy knowledge more effectively, this paper presents fuzzy ontology models of linguistic variable, considering semantic relationships of fuzzy concepts, including set relation, order relation, equivalence relation and semantic association relation etc. To achieve fuzzy semantic retrieval, the semantic query expansion in SPARQL query language is constructed by semantic relations between fuzzy concepts defined in linguistic variable fuzzy ontology. The application shows that the extended query can return all results which satisfy research requirement at semantic level without upgrading current main search algorithm, and this research facilitates the semantic retrieval through fuzzy concepts on the Semantic Web.
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Zhai, J., Li, M., Zhou, K. (2010). Linguistic Variable Ontology and Its Application to Fuzzy Semantic Retrieval. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Communications in Computer and Information Science, vol 106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16339-5_25
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DOI: https://doi.org/10.1007/978-3-642-16339-5_25
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