From Computing with Words (CWW) to Reasoning with Fuzzy Concepts (RFC)

被引：0
作者：
Wang, Yingxu [1 ,2 ]
机构：
[1] Univ Calgary, Schulich Sch Engn, Dept Elect & Comp Engn, Int Inst Cognit Informat & Cognit Comp ICIC, 2500 Univ Dr NW, Calgary, AB T2N 1N4, Canada
[2] Univ Calgary, Hotchkiss Brain Inst, Calgary, AB T2N 1N4, Canada
来源：
2016 ANNUAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY (NAFIPS) | 2016年
基金：
加拿大自然科学与工程研究理事会;
关键词：
Fuzzy reasoning; fuzzy concept; fuzzy semantics; cognitive linguistics; reasoning with fuzzy concepts; computing with words; cognitive computing; soft computing; computational intelligence; DENOTATIONAL MATHEMATICS; REFERENCE MODEL; ALGEBRA; BRAIN;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The fuzzy nature of language structures and semantics is formally studied towards a methodology for reasoning with fuzzy concepts (RFC). Mathematical models of fuzzy concepts and fuzzy semantics are introduced based on concept algebra and semantic algebra. The semantic effects of fuzzy modifiers and quantifiers on fuzzy concepts are quantitatively analyzed. Experiments on collective intension and extension elicitation for fonnal concepts demonstrate that fuzziness of human knowledge stem from the cognitive complexity, inexplicitness, subjectivity, diversity, redundancy, incompleteness, mixed synonyms, infonnal representation, incoherent attributes, divergent objects, and contextual influence. The RFC methodology provides a formal approach to computing with words (CW) for cognitive robots, deep machine learning, and fuzzy systems to rigorously manipulate fuzzy language entities, semantics, and reasoning in a wide range of applications.
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页数：6
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