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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

  • Bodenhofer U. (2002): A note on approximate equality versus the Poincaré paradox. - Fuzzy Sets Syst., (to appear).
  • De Baets B. and Mesiar R. (1999): Triangular norms on product lattices. - Fuzzy Sets Syst., Vol. 104, No. 1, pp. 61-75.
  • 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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  • Wei Q., Chen G. and Wets G. (2000): Modifying fuzzy association rules with linguistic hedges.- 19th Int. Meeting of the North American Fuzzy Information Processing Society, Atlanta (USA), pp. 397-401.
  • 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.
  • Zadeh L. A. (1972): A fuzzy-set-theoretic interpretation of linguistic hedges. - J. Cybern., Vol. 2, No. 3, pp. 4-34.
  • Zadeh L. A. (1975): The concept of a linguistic variable and its application to approximate reasoning I, II, III. - Inf. Sci., Vol. 8, No. 3, pp. 199-249, No. 4, pp. 301-357; Vol. 9, No. 1, pp. 43-80.

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Bibliografia

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