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Fuzzy Ontologies: State of the Art Revisited

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Fuzzy Information Processing (NAFIPS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 831))

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Abstract

Although ontologies have become the standard for representing knowledge on the Semantic Web, they have a primary limitation, the inability to represent vague and imprecise knowledge. Much research has been undertaken to extend ontologies with the means to overcome this and has resulted in numerous extensions from crisp ontologies to fuzzy ontologies. The original web ontology language, and tools were not designed to handle fuzzy information; therefore, additional research has focused on modifications to extend them. A review of the fuzzy extensions to allow fuzziness in ontologies, web languages, and tools as well as several very current examples of fuzzy ontologies in real-world applications is presented.

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Authors and Affiliations

  1. Computer Science and Software Engineering, Miami University, Oxford, OH, 45056, USA

    Valerie Cross & Shangye Chen

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  1. Valerie Cross
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  2. Shangye Chen
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Correspondence to Valerie Cross .

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Editors and Affiliations

  1. Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Guilherme A. Barreto

  2. Department of Statistics & Applied Mathematics, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Ricardo Coelho

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Cross, V., Chen, S. (2018). Fuzzy Ontologies: State of the Art Revisited. In: Barreto, G., Coelho, R. (eds) Fuzzy Information Processing. NAFIPS 2018. Communications in Computer and Information Science, vol 831. Springer, Cham. https://doi.org/10.1007/978-3-319-95312-0_20

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  • DOI: https://doi.org/10.1007/978-3-319-95312-0_20

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