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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
De Cock M., Kerre E. E. (2000) On (un)suitable fuzzy relations to model approximate equality.Submitted.
De Cock M., Kerre E. E. (2000) A New Class of Fuzzy Modifiers. Proceedings of ISMVL2000, IEEE Computer Society, 121–126.
De Cock M., Radzikowska A. M., Kerre E. E. (2000) Modelling Linguistic Modifiers using Fuzzy—Rough Structures. Proceedings of IPMU2000, 1735–1742.
Dubois D., Prade H. (1990) Rough Fuzzy Sets and Fuzzy Rough Sets. Int. J. of General Systems 17 (2–3), 191–209.
Dubois D., Prade H. (1992) Putting fuzzy sets and rough sets together. Intelligent Decision Support, Roman Slowiríski (ed.), Kluwer Academic, 203–232.
Kerre E. E., De Cock M. (1999) Linguistic Modifiers: an overview. Fuzzy Logic and Soft Computing, Guoqing Chen, Mingsheng Ying, Kai-Yaun Cai (eds), Kluwer Academic Publishers, 69–85.
Lakoff G. (1973) Hedges: a Study in Meaning Criteria and the Logic of Fuzzy Concepts. Journal of Philosophical Logic 2, 458–508.
Novak V., Perfilieva I. (1999) Evaluating Linguistic Expressions and Functional Fuzzy Theories in Fuzzy Logic. Computing with Words in Information/Intelligent Systems 1: Foundations, L. A. Zadeh, J. Kacprzyk (eds.), Studies in Fuzziness and Soft Computing 33, Springer-Verlag, Heidelberg.
Pawlak Z. (1982) Rough sets. Int. J. of Computer and Information Science 11 (5), 341–356.
Radzikowska A. M., Kerre E. E. A Comparative Study of Fuzzy Rough Sets. To appear inFuzzy Sets and Systems.
Radzikowska A. M., Kerre E. E. A General Calculus of Fuzzy Rough Sets. Submitted.
Thiele H. (1997) Fuzzy Rough Sets versus Rough Fuzzy Sets — an Interpretation and a Comparative Study using Concepts of Modal Logic. Proceedings of EUFIT-97, vol. I, 159–167
Thiele H. (1998) Interpreting linguistic hedges by concepts of functional analysis and mathematical logic. Proceedings of EUFIT-98, vol. I, 114–119
Zadeh L.A. (1972) A Fuzzy-Set-Theoretic Interpretation of Linguistic Hedges. Journal of Cybernetics2,3, 4–34
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
De Cock, M., Radzikowska, A.M., Kerre, E.E. (2002). A Fuzzy-Rough Approach to the Representation of Linguistic Hedges. In: Bouchon-Meunier, B., Gutiérrez-Ríos, J., Magdalena, L., Yager, R.R. (eds) Technologies for Constructing Intelligent Systems 1. Studies in Fuzziness and Soft Computing, vol 89. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1797-3_3
Download citation
DOI: https://doi.org/10.1007/978-3-7908-1797-3_3
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-662-00329-9
Online ISBN: 978-3-7908-1797-3
eBook Packages: Springer Book Archive