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

Wataru Okamoto | Zendy; Shun’ichi Tano | Zendy; T. Iwatani | Zendy; Atsushi Inoue | Zendy

Open Access

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

Author(s) -

Wataru Okamoto,

Shun’ichi Tano,

T. Iwatani,

Atsushi Inoue

Publication year - 2007

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2007.p0071

Subject(s) - computer science , interpretation (philosophy) , inference , statement (logic) , artificial intelligence , fuzzy logic , predicate (mathematical logic) , natural language processing , natural language , rule of inference , linguistics , programming language , philosophy

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 two examples transforming a fuzzy predicate of the natural language propositions and showed an effectiveness of the method.

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