Inference method for fuzzy quantified and truth qualified natural language propositions

被引:0
|
作者
Okamoto, W [1 ]
Tano, S
Inoue, A
Fujioka, R
机构
[1] NEC Corp Ltd, Kawasaki, Kanagawa 216, Japan
[2] Univ Electrocommun, Chofu, Tokyo 182, Japan
[3] Univ Cincinnati, Cincinnati, OH 45220 USA
[4] Kobe Steel Ltd, Kobe, Hyogo 65122, Japan
关键词
natural language; fuzzy inference; fuzzy quantifier; truth qualifier;
D O I
10.1002/(SICI)1520-6440(200002)83:2<22::AID-ECJC3>3.0.CO;2-S
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes an inference method for fuzzy quantified and truth qualified natural language propositions. For example, for "Most tall men are heavy is true," a modified proposition "Many more or less tall men are heavy is true," can be derived by inference. For the quantifier "more or less," the fuzzy quantifier "many" can be derived analytically. Three types of fuzzy quantifiers (the monotonically nonincreasing type such as "few," the monotonically nondecreasing type such as "most," and the single-peaked type such as "several"), as well as the monotonic and injection type truth quantified qualifier such as true and false, are considered. For a proposition containing those quantifiers/qualifiers, it is shown that the fuzzy quantifier can be derived analytically by the fuzzy inference, for the modification to quantify the fuzzy subject part. (C) 1999 Scripta Technica, Electron Comm Jpn Pt 3, 83(2): 22-43, 2000.
引用
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页码:22 / 43
页数:22
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