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, ...).

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