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JACIII Vol.11 No.1 pp. 71-78
doi: 10.20965/jaciii.2007.p0071
(2007)

Paper:

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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
Published:
January 20, 2007
Creative Commons License
Keywords:
natural language, fuzzy inference, fuzzy quantifiers, truth qualifiers, modifiers
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.
Cite this article as:
W. Okamoto, S. Tano, T. Iwatani, and A. Inoue, “An Inference Method for Fuzzy Quantified Natural Language Propositions Based on New Interpretation of Truth Qualification,” J. Adv. Comput. Intell. Intell. Inform., Vol.11 No.1, pp. 71-78, 2007.
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