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Fuzzy Ontologies to Represent Background Knowledge: Some Experimental Results on Modelling Climate Change Knowledge

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 107))

Abstract

Ontologies represent a method of sharing and reusing knowledge on the semantic web. Moreover, fuzzy ontologies, i.e., the combination of fuzzy logic and ontologies, may be an interesting tool for representing domain knowledge with the aim of solving problems where uncertainty is present. This paper presents three fuzzy-based ontology models for knowledge representation. These ontologies have been obtained after the automatic analysis of a collection of relevant documents that are related to a specific subject. Some experiments have been carried out to illustrate the feasibility of these approaches.

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Fdez-Viñas, E., Ferreira-Satler, M., Romero, F.P., Serrano-Guerrero, J., Olivas, J.A., Saavedra, N. (2011). Fuzzy Ontologies to Represent Background Knowledge: Some Experimental Results on Modelling Climate Change Knowledge. In: Melo-Pinto, P., Couto, P., Serôdio, C., Fodor, J., De Baets, B. (eds) Eurofuse 2011. Advances in Intelligent and Soft Computing, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24001-0_18

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  • DOI: https://doi.org/10.1007/978-3-642-24001-0_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24000-3

  • Online ISBN: 978-3-642-24001-0

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