IKARUS-Onto: A Methodology to Develop Fuzzy Ontologies from Crisp Ones

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P. Alexopoulos, M. Wallace, K. Kafentzis, D. Askounis, IKARUS-Onto: A Methodology to Develop Fuzzy Ontologies from Crisp Ones, Knowledge and Information Systems, vol 32(3), pp. 667-695, 2012

Abstract

Fuzzy Ontologies comprise a relatively newknowledge representation paradigm that is being increasingly applied in application scenarios in which the treatment and utilization of vague or imprecise knowledge are important. However, the majority of research in the area has mostly focused on the development of conceptual formalisms for representing (and reasoning with) fuzzy ontologies, while the methodological issues entailed within the development process of such an ontology have been so far neglected.With that in mind, we present in this paper IKARUS-Onto, a comprehensive methodology for developing fuzzy ontologies from existing crisp ones that significantly enhances the effectiveness of the fuzzy ontology development process and the quality, in terms of accuracy, shareability and reusability, of the process’s output.

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3 known citations

1. Giorgos Flouris, George Konstantinidis, Grigoris Antoniou, Vassilis Christophides, Formal Foundations for RDF/S KB Evolution, Knowledge and Information Systems, vol 35, pp. 153-191, 2013
2. M. Afsharchi, A. Didandeh, N. Mirbakhsh and B. Far, Common understanding in a multi-agent system using ontology-guided learning, Knowledge and Information Systems, vol 36(1), pp. 83-120, 2013
3. I. Zisis, Developement of a vague knowledge management system, Thesis, National Technical University of Athens, 2011