Abstract
Despite the undisputed success of ontologies, they are not appropriate to represent and reason with vague knowledge. WordNet, a widely used ontology for general/natural language tasks, presents some of these problems when it is applied to specialized discourse. In this paper, we propose to use fuzzy ontologies, which combine Fuzzy Logic theory and Description Logics, to represent the imprecise notions of prototypicality and representativeness inside a synonym set, semantic similarity, and hyponymic degree in WordNet. We show that this approach is particularly appropiate to combine WordNet with other specific terminological resources, such as the environmental knowledge base EcoLexicon.
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Bobillo, F., Gómez-Romero, J., León Araúz, P. (2012). Fuzzy Ontologies for Specialized Knowledge Representation in WordNet. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances on Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31709-5_44
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DOI: https://doi.org/10.1007/978-3-642-31709-5_44
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