A fuzzy-rough approach to the representation of linguistic hedges

Authors:
Martine De Cock;Anna Maria Radzikowska;Etienne E. Kerre
Affiliations:
Dept. of Mathematics and Computer Science, Ghent University, Krijgslaan 281 (S9), B-9000 Gent, Belgium;Faculty of Mathematics and Information Science, Warsaw University of Technology, Plac Politechniki 1, 00-661 Warsaw, Poland;Dept. of Mathematics and Computer Science, Ghent University, Krijgslaan 281 (S9), B-9000 Gent, Belgium
Venue:
Technologies for constructing intelligent systems
Year:
2002

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Abstract

We present a new representation for linguistic hedges using a framework of fuzzy rough sets. In traditional fuzzy-set theoretical representations, properties of objects such as old and experienced, are represented by a fuzzy set P, while linguistic hedges (i.e. expressions like very, more or less, rather) are modelled by means of some transformations applied to P. In contrast to these approaches, we propose a representation which allows us to express the meaning of a statement like "x is very P" also relative to mutual resemblances between objects in the domain of discourse. This allows for adequate context-dependent characteristics of objects. Technically, this is achieved by using fuzzy rough approximators with respect to fuzzy resemblance relations representing mutual resemblances between objects. We show that this framework allows for flexible representation of some linguistic terms.