Fuzzy Ontology Representation using OWL 2
By Fernando Bobillo, Umberto Straccia. International Journal of Approximate Reasoning, 2010
330 citations recorded by the source corpus.
The need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We may address this issue by either extending current Semantic Web languages to cope with vagueness, or by providing a procedure to represent such information within current standard languages and tools. In this work, we follow the latter approach, by identifying the syntactic differences that a fuzzy ontology language has to cope with, and by proposing a concrete methodology to represent fuzzy ontologies using OWL 2 annotation properties. We also report on some prototypical implementations: a plug-in to edit fuzzy ontologies using OWL 2 annotations and some parsers that translate fuzzy ontologies represented using our methodology into the languages supported by some reasoners.
Subfields: Artificial Intelligence, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/0c8ecc5c06c4ec25c5ae400b71dacc82b01bef0f
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Citations in the corpus
- Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies (2017, methodology): “Two approaches have been proposed for dealing with vagueness in ontologies: the development of fuzzy extensions to OWL based on new DLs [54], and the use of the current OWL standard using specific procedures ( e.g. using annotations to specify fuzziness) [55].”