Paper:
Language: English:

A Generalized Inference Method for Fuzzy Quantified and Truth-Qualified Natural Language Propositions

Wataru Okamoto^, Shun’ichi Tano^, Atsushi Inoue^,
and Ryosuke Fujioka^****

^Yokohama, Kanagawa 240-0042, Japan
^University of Electro-Communications, Chofu, Tokyo 182-8585, Japan
^Eastern Washington University, Cheney, WA 99004-2412, USA
^****Kobe Sogo Sokki Co., Ltd, Kobe, Hyogo 650-0012, Japan

Received: December 19, 2006

Accepted: April 25, 2007

Keywords: natural language, fuzzy inference, fuzzy quantifier, truth qualifier, modifier

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.5 pp. 502-510, 2007

Abstract

We propose a generalized inference method for constructing natural language communication. The method is used to obtain fuzzy quantifier Q’ when “QA are F is τ →Q’ (m’A) are mF is m’’τ” is inferred (Q, Q’: fuzzy quantifiers, A: fuzzy subject, m, m’, m’’: modifiers, F: fuzzy predicate, τ: truth qualifier). We show that Q’ is resolved step by step for a non-increasing type (few, ...) and a non-decreasing type (most, ...).

Reference

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

[2] L. A. Zadeh, “A Computational Approach to Fuzzy Quantifiers in Natural Languages,” Comp. and Maths with Appls., 9, pp. 149-184, 1983.

[3] W. Okamoto, S. Tano, T. Iwatani, and A. Inoue, “Inference Method for Natural Language Propositions Involving Fuzzy Quantifiers in FLINS,” Proceedings of IEEE International Conference on Fuzzy Systems, Orlando, pp. 1023-1028, 1994.

[4] 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.

[5] W. Okamoto, S. Tano, A. Inoue, and R. Fujioka, “Constraints 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).

[6] W. Okamoto, S. Tano, A. Inoue, and R. Fujioka, “Inference Method for Natural Language Propositions Involving Fuzzy Quantifiers and Truth Qualifiers,” Proceedings of IEEE International Conference on Fuzzy Systems, Yokohama, pp. 955-962, 1995.

[7] 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: Fundamental Electronic Science (published by SCRIPTA TECHNICA), Vol.83, No.2, pp. 22-43, 2000.

[8] 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 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’05), Reno, pp. 672-677, 2005.