Prototypical knowledge for interpreting fuzzy concepts and quantifiers
The ability to understand truly natural language expressions which involve fuzzy concepts and quantifiers (like many, few, most, etc.) presents many problems, some of which are worth mentioning: cardinality of a fuzzy set, extensions of the classical syllogisms to fuzzy syllogisms, dispositions, etc...
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Published in | Fuzzy sets and systems Vol. 23; no. 3; pp. 361 - 370 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
1987
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Subjects | |
Online Access | Get full text |
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Summary: | The ability to understand truly natural language expressions which involve fuzzy concepts and quantifiers (like many, few, most, etc.) presents many problems, some of which are worth mentioning: cardinality of a fuzzy set, extensions of the classical syllogisms to fuzzy syllogisms, dispositions, etc. Apart from these problems, which have been discussed in the literature, the main difficulty in evaluating such expressions is the strong interaction between the definition of the fuzzy concept and the domain knowledge.
In this paper we will try to make such a claim apparent and describe some initial solutions, which provide an intelligent system with the capability of representing and understanding fuzzy concepts and quantifiers by taking into account domain knowledge. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0165-0114 1872-6801 |
DOI: | 10.1016/0165-0114(87)90048-0 |