Paper:
Language: English:

An Inference Method for Fuzzy Quantified Natural Language Propositions Based on New Interpretation of Truth Qualification

Wataru Okamoto^, Shun’ichi Tano^, Toshiharu Iwatani^,
and Atsushi Inoue^****

^Yokohama, Kanagawa 240-0042, Japan
^University of Electro-Communications, Chofu, Tokyo 182-8585, Japan
^Kobe Steel Ltd., Kobe, Hyogo 651-8585, Japan
^****Eastern Washington University, Cheney, WA 99004-2412, USA

Received: December 12, 2005

Accepted: May 31, 2006

Keywords: natural language, fuzzy inference, fuzzy quantifiers, truth qualifiers, modifiers

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.1 pp. 71-78, 2007

Abstract

In this paper, we propose a method that affects inference results leading to a new interpretation of a truth qualification by adding a weight attribute to truth qualified fuzzy sets. With this method, we can obtain different inference results depending on the truth qualifiers by transforming a statement with fuzzy quantified and truth qualified natural language propositions. We applied our method to four examples transforming a fuzzy predicate of the natural language propositions and showed an effectiveness of the method.

Reference

[1] L. A. Zadeh, “PRUF-A meaning representation language for natural language,” International Journal of Man Machine Studies, Vol.10, pp. 395-460, 1978.

[2] L. A. Zadeh, “A Theory of Approximate Reasoning,” Machine Intelligence, Vol.9, New York: Halstead Press, pp. 149-194, 1979.

[3] L. A. Zadeh, “A Computational Approach to Fuzzy Quantifiers in Natural Languages,” Computers and Mathematics with Applications, Vol.9, pp. 149-184, 1983.

[4] D. Dubois and H. Prade, “Gradual Inference Rules in Approximate Reasoning,” Information Sciences, Vol.61, pp. 103-122, 1992.

[5] W. Okamoto, S. Tano, T. Iwatani, and A. Inoue, “Inference Method for Natural Language Propositions involving Fuzzy Quantifiers in FLINS,” Proceedings of Third IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’94), Orlando, pp. 1023-1028, 1994.

[6] W. Okamoto, S. Tano, T. Iwatani, and A. Inoue, “Inference Method for Truth-Qualified Natural Language Propositions involving Fuzzy Quantifiers,” Proceedings of Second European Congress on Intelligent Techniques and Soft Computing (EUFIT’94), Aachen, pp. 1594-1598, 1994.

[7] W. Okamoto, S. Tano, T. Iwatani, and A. Inoue, “Inference Method for Natural Language Propositions Involving Fuzzy Quantifiers,” Japanese Journal of Fuzzy Theory and Systems, Vol.7, No.4, pp. 509-536, 1995.

[8] W. Okamoto, S. Tano, A. Inoue, and R. Fujioka, “Constrains on Natural Language Propositions Involving Fuzzy Quantifiers by Truth-Qualification and Inference Method for the Propositions,” Journal of Japan Society for Fuzzy Theory and Systems, Vol.8, No.3, pp. 519-531, 1996 (in Japanese).

[9] W. Okamoto, S. Tano, A. Inoue, and R. Fujioka, “Inference Method for Fuzzy Quantified and Truth Qualified Natural Language Propositions,” Electronics and Communications in Japan, Part 3, Vol.83, No.2, pp. 22-43, 2000.

[10] S. Tano, W. Okamoto, T. Iwatani, A. Inoue, and R. Fujioka, “Fuzzy Natural Language Communication System – FLINS: Concept and Conversation Examples,” Proceedings of Fourth IEEE International Conference on Fuzzy Systems and Second International Fuzzy Engineering Symposium (FUZZ-IEEE/IFES’95), Yokohama, pp. 1039-1044, 1995.

[11] R. Fujioka, S. Tano, W. Okamoto, A. Inoue, and T. Iwatani, “Treatment of Fuzziness in Natural Language by Fuzzy Lingual System – FLINS,” Proceedings of Fourth IEEE International Conference on Fuzzy Systems and Second International Fuzzy Engineering Symposium (FUZZ-IEEE/IFES’95), Yokohama, pp. 1045-1050, 1995.

[12] W. Okamoto, S. Tano, A. Inoue, and R. Fujioka, “A Generalized Inference Method for Natural Language Propositions Involving Fuzzy Quantifiers and Truth Qualifiers,” Proceedings of 14th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’05), Reno, pp. 672-677, 2005.