Abstract
The aim of this paper is to apply main theories of fuzzy natural logic together with fuzzy GUHA method for a linguistic characterization of relationships in data. Namely, we utilize the theory of intermediate quantifiers, which provides mathematical interpretation of natural language expressions describing quantity such as “Almost all”, “Few” etc., to describe relationships in data using vague terms that are natural in human expression. We provide an algorithm for computation of truth degrees of expressions containing such quantifiers. Moreover, we discuss some basic properties of intermediate quantifiers (contraries, contradictories, sub-contraries and sub-alterns), which formulate the graded Peterson’s square of opposition, and which can be used to infer new expressions from existing ones.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
Applying of delta connective in this definition we solve the problem \( \vdash \pmb {\lnot }(\forall x)(Bx\pmb {\Rightarrow }Ax)\equiv (\exists x)(Bx\mathop {\pmb { \& }}\nolimits \pmb {\lnot }Ax)\) then \(\mathscr {M}(\pmb {\lnot }\mathbf {A}\not \equiv \mathbf {O})=1\) since \(\mathbf {O}\mathrel {:=}\,(\exists x)(Bx\pmb {\wedge }\pmb {\lnot }Ax)\).
References
Novák, V.: A formal theory of intermediate quantifiers. Fuzzy Sets Syst. 159(10), 1229–1246 (2008)
Novák, V.: On fuzzy type theory. Fuzzy Sets Syst. 149, 235–273 (2005)
Murinová, P., Novák, V.: A formal theory of generalized intermediate syllogisms. Fuzzy Sets Syst. 186, 47–80 (2013)
Murinová, P., Novák, V.: Analysis of generalized square of opposition with intermediate quantifiers. Fuzzy Sets Syst. 242, 89–113 (2014)
Lakoff, G.: Linguistics and natural logic. Synthese 22, 151–271 (1970)
Novák, V.: A comprehensive theory of trichotomous evaluative linguistic expressions. Fuzzy Sets Syst. 159(22), 2939–2969 (2008)
Novák, V.: Perception-based logical deduction. In: Reusch, B. (ed.) Computational Intelligence, Theory and Applications, pp. 237–250. Springer, Berlin (2005)
Novák, V., Lehmke, S.: Logical structure of fuzzy IF-THEN rules. Fuzzy Sets Syst. 157, 2003–2029 (2006)
Hájek, P.: The question of a general concept of the GUHA method. Kybernetika 4, 505–515 (1968)
Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proceedings 20th International Conference on Very Large Databases, pp. 487–499, Chile, AAAI Press (1994)
Hájek, P., Havránek, T.: Mechanizing Hypothesis Formation: Mathematical Foundations For A General Theory. Springer, Heidelberg (1978)
Tan, P.-N., Kumar, V., Srivastava, J.: Selecting the right objective measure for association analysis. Inf. Syst. 29(4), 293–313 (2004)
Geng, L., Hamilton, H.J.: Interestingness measures for data mining: a survey. ACM Comput. Surv. 38(3), 9 (2006)
Moyse, G., Lesot, M., Bouchon-Meunie, B.: Oppositions in fuzzy linguistic summaries. In: FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems, Turkey, pp. 1–8 (2015)
Peterson, P.L.: Intermediate Quantifiers: Logic, linguistics, and Aristotelian semantics. Ashgate, Aldershot (2000)
Kacprzyk, J., Zadrożny, S.: Linguistic database summaries and their protoforms: towards natural language based knowledge discovery tools. Inf. Sci. 173, 281–304 (2005)
Yager, R.: A new approach to the summarization of data. Inf. Sci. 28, 69–86 (1982)
Yager, R.: On ordered weighted averaging operators in multicriteria decision making. IEEE Trans. Syst. Man Cybern. 18, 182–190 (1988)
Yager. R.: On linguistic summaries of data. In: Piatetsky-Shapiro, G., Frawley, W.J. (eds.) Knowledge Discovery in Databases, pp. 347–363 (1991)
Yager, R.: Linguistic summaries as a tool for database discovery. In: Proceedings of FUZZIEEE 1995 Workshop on Fuzzy Database Systems and Information Retrieval, Yokohama, pp. 79–82 (1995)
Kacprzyk, J., Yager, R.R.: Linguistic summaries of data using fuzzy logic. Int. J. Gen Syst 30, 133–154 (2001)
Yager, R.R., Kacprzyk, J., Zadrożny, S.: Linguistic summaries of data using fuzzy logic. Int. J. Appl. Math. Comput. Sci. 10, 813–834 (2001)
Kacprzyk, J., Zadrożny, S.: Linguistic summarization of data sets using association rules. In: Proceedings of FUZZ-IEE’03, St. Louis, USA, pp. 702–707 (2003)
Westerståhl, D.: Quantifiers in formal and natural languages. In: Gabbay, D., Guenthner, F. (eds.)Handbook of Philosophical Logic, vol. 4, pp. 1–131. D. Reidel, Dordrecht (1989)
Westerståhl, D.: Aristotelian syllogisms and generalized quantifiers. Studia Logica: Int. J. Symbolic Logic 48, 577–585 (1989)
Glöckner, I.: Fuzzy Quantifiers: A Computational Theory. Springer, Berlin (2006)
Keenan, E.L., Westerståhl, D.: Quantifiers in formal and natural languages. In: van Benthem, J., ter Meulen, A. (eds.) Handbook of Logic and Language, pp. 837–893. Elsevier, Amsterdam (1997)
Peters, S., Westerståhl, D.: Quantifiers in Language and Logic. Claredon Press, Oxford (2006)
Holčapek, M.: Monadic L-fuzzy quantifiers of the type \(\langle 1^n, 1\rangle \). Fuzzy Sets Syst. 159, 1811–1835 (2008)
Hájek, P.: Metamathematics of Fuzzy Logic. Kluwer, Dordrecht (1998)
Pereira-Fariña, M., Díaz-Hermida, F., Bugarín, A.: On the analysis of set-based fuzzy quantified reasoning using classical syllogistics. Fuzzy Sets Syst. 214, 83–94 (2013)
Pereira-Fariña, M.: Juan C. Vidal, F. Díaz-Hermida, and A. Bugarín. A fuzzy syllogistic reasoning schema for generalized quantifiers. Fuzzy Sets Syst. 234, 79–96 (2014)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
Murinová, P., Burda M.: Linguistic characterization of natural data by applying intermediate quantifiers on fuzzy association rules. J. Fuzzy Set Valued Anal. (2017). accepted
Fisher, R.A.: The use of multiple measurements in taxonomic problems. Ann. Eugenics 7(2), 179–188 (1936)
Anderson, E.: The species problem in iris. Ann. Mo. Bot. Gard. 23(3), 457–509 (1936)
Agrawal, R., Imielinski, T., Swarmi, A.: Mining association rules between sets of items in large databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 207–216, Washington D.C., U.S.A., (1993)
Acknowledgment
The paper has been supported by the project “LQ1602 IT4Innovations excellence in science”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Murinová, P., Burda, M., Pavliska, V. (2018). An Algorithm for Intermediate Quantifiers and the Graded Square of Opposition Towards Linguistic Description of Data. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds) Advances in Fuzzy Logic and Technology 2017. EUSFLAT IWIFSGN 2017 2017. Advances in Intelligent Systems and Computing, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-319-66824-6_52
Download citation
DOI: https://doi.org/10.1007/978-3-319-66824-6_52
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66823-9
Online ISBN: 978-3-319-66824-6
eBook Packages: EngineeringEngineering (R0)