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Fuzzy Ontology Evolution: Classification of a New Individual

Djellal Asma and Boufaida Zizette
LIRE Laboratory, Constantine 2 University, Constantine, Algeria
Abstract—Ontologies help to conceive the real world with its semantic constraints. But this world has several uncertainties and imperfections that we cannot conceive using traditional ontologies. In our work, we are mainly interested in the imprecise knowledge representation problem. We believe that the most appropriate way is to use fuzzy logic in order to build ontologies called "Fuzzy ontologies". Even if there are several researches revolve around handling imprecise knowledge, however, there are still some issues to be further studied; one of them is the evolution problem which is still a tedious field. In this paper, and as a first step in the problem of fuzzy ontology evolution, we are interested in the classification of new individuals; for this reason, we use the classificatory reasoning mechanism to enable the classification of new individuals in a fuzzy hierarchy.

Index Terms—fuzzy logic, fuzzy ontology, classification reasoning, individual classification.  

Cite: Djellal Asma and Boufaida Zizette, "Fuzzy Ontology Evolution: Classification of a New Individual," Journal of Emerging Technologies in Web Intelligence, Vol. 6, No. 1, pp. 9-14, February 2014. doi:10.4304/jetwi.6.1.9-14
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