Improving queries and representing heterogeneous information in fuzzy ontologies using multi-granular fuzzy linguistic modelling methods

Abstract

The appearance of Fuzzy Ontologies has improved the way that crisp ontologies use to represent information. Thanks to them, it is possible to represent information in an imprecise and linguistic way using linguistic modelling and fuzzy sets. Nevertheless, there are still several restrictions that must be overcome. For instance, ontology queries must be performed using a linguistic label set with an specific granularity value. In environments where several people have to deal with the same ontology, this can be an inconvenient since the chosen representation does not have to be suitable for all of them. In this paper, multi-granular fuzzy linguistic modelling methods have been used in order to deal with heterogeneous information coming from different sources and to allow experts to choose the linguistic label set that better fits their needs.