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2002 | 12 | 3 | 371-382
Tytuł artykułu

A context-based approach to linguistic hedges

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
We present a framework of L-fuzzy modifiers for L being a complete lattice. They are used to model linguistic hedges that act on linguistic terms represented by L-fuzzy sets. In the modelling process the context is taken into account by means of L-fuzzy relations, endowing the L-fuzzy modifiers with a clear inherent semantics. To our knowledge, these L-fuzzy modifiers are the first ones proposed that are suitable to perform this representation task for a lattice L different from the unit interval. In the latter case they undoubtedly outperform the traditional representations, such as powering and shifting hedges, from the semantical point of view.
Rocznik
Tom
12
Numer
3
Strony
371-382
Opis fizyczny
Daty
wydano
2002
otrzymano
2002-03-01
poprawiono
2002-06-01
Twórcy
  • Fuzziness and Uncertainty Modelling Research Unit, Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281, B-9000 Gent, Belgium
  • Fuzziness and Uncertainty Modelling Research Unit, Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281, B-9000 Gent, Belgium
Bibliografia
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  • De Cock M. and Kerre E. E. (2000): A new class of fuzzy modifiers. - Proc. ISMVL2000 (30th IEEE Int. Symp. Multiple-Valued Logic), Computer Society, Cortland (USA), pp. 121-126.
  • De Cock M. and Kerre E. E. (2001): Approximate equality is no fuzzy equality. - Proc. EUSFLAT2001 (Int. Conf. European Society for Fuzzy Logic and Technology), Leicester (UK), pp. 369-371.
  • De Cock M. and Kerre E. E. (2002a): Fuzzy modifiers based on fuzzy relations. -Inf. Sci., (to appear).
  • De Cock M. and Kerre E. E. (2002b): On (un)suitable fuzzy relations to model approximate equality. -Fuzzy Sets Syst., (to appear).
  • De Cock M., Nachtegael M. and Kerre E. E. (2000): Images under Fuzzy relations: A Master-Key to Fuzzy Applications, In: Intelligent Techniques and Soft Computing in Nuclear Science and Engineering (D. Ruan, H. A. Abderrahim, P. D'hondt and E. E. Kerre, Eds.) -Singapore: World Scientific.
  • De Cock M., Žabokrtský Z. and Kerre E. E. (2001): Representing linguistic hedges by L-fuzzy modifiers. -Proc. CIMCA'01 (Int. Conf. Computational Intelligence for Modelling Control and Automation), Las Vegas (USA), pp. 64-72 (CD-ROM).
  • De Cooman G. and Kerre E. E. (1994): Order norms on bounded partially ordered sets. -J. Fuzzy Math., Vol. 2, No. 2, pp. 281-310.
  • du Bois N., De Cock M., Kerre E. E. and Babuvska R. (2002): A fuzzy set theoretical approach to the automatic generation of absenteeism analyses in natural language. - Proc. IPMU2002 (9th Int. Conf. Information Processing and Management of Uncertainty in Knowledge-Based Systems), Annecy (France), Vol. III, pp. 1961-1968.
  • Drossos C. and Navara M. (1997): Matrix composition of t-norms, In: Enriched Lattice Structures for Many-Valued and Fuzzy Logics, Proceedings of 18th Linz Seminar on Fuzzy Set Theory (E.P. Klement and S. Gottwald, Eds.). - Luiz, Johannes Kepler Univ., pp. 95-100.
  • Goguen J. (1967): L-fuzzy sets. - J. Math. Anal. Applic., Vol. 18, No. 1, pp. 145-174.
  • Hellendoorn H. (1990): Reasoning with Fuzzy Logic. -Ph. D. Thesis, T.U. Delft (the Netherlands).
  • Kerre E. E. (Ed.) (1993): Introduction to the basic principles of fuzzy set theory and some of its applications. - Communication and Cognition, Gent.
  • Kerre E. E. and De Cock M. (1999): Linguistic modifiers: An overview, In: Fuzzy Logic and Soft Computing (Chen G., Ying M. and Cai K.-Y., Eds.). - Dordrecht: Kluwer Academic Publishers, pp. 69-85.
  • Klawonn F. (2002): Should fuzzy equality and similarity satisfy transitivity? Comments on the paper by M. De Cock and E. Kerre. -Fuzzy Sets Syst., (to appear).
  • Lakoff G. (1973): Hedges: A study in meaning criteria and the logic of fuzzy concepts. - J. Phil. Logic, Vol. 2, No. 4, pp. 458-508.
  • Novák V. and Perfilieva I. (1999): Evaluating linguistic expressions and functional fuzzy theories in fuzzy logic, In: Computing with Words in Information Intelligent Systems 1: Foundations (Zadeh L. A. and Kacprzyck J., Eds.). - Heidelberg: Springer-Verlag, pp. 383-406.
  • Novák V., Perfilieva I. and Mouckour J. (1999): Mathematical Principles of Fuzzy Logic. -Boston: Kluwer.
  • Orlowska E. and Radzikowska A. (2001): Information relations and operators based on double residuated lattices. - Proc. RELMICS'6 (6-th Int. Workshop Relational Methods in Computer Science), Aisterwijk (the Netherlands), pp. 169-186.
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  • Xu Y., Ruan D. and Liu J. (1999): Uncertainty automated reasoning in intelligent learning of soft knowledge. - Proc. ICST Workshop Information and Communication Technology for Teaching and Training, Gent (Belgium), pp. 29-45.
  • Xu Y., Ruan D. and Liu J. (2000): Approximate reasoning based on lattice-valued propositional logic L_{vpl}, In: Fuzzy IF-THEN Rules in Computational Intelligence, Theory and Applications (Ruan D. and Kerre E. E., Eds.) - Boston: Kluwer Academic Publishers, pp. 81-105
  • Zadeh L. A. (1965): Fuzzy sets. - Inf. Contr., Vol. 8, No. 3, pp. 338-353.
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Typ dokumentu
Bibliografia
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