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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Bibliographic Details
Published inFuzzy sets and systems Vol. 23; no. 3; pp. 361 - 370
Main Authors Lesmo, Leonardo, Torasso, Pietro
Format Journal Article
LanguageEnglish
Published Elsevier B.V 1987
Subjects
Fuzzy quantifiers
Knowledge representation
Linguistic variables
Natural language
Prototypical knowledge
Prototypical knowledge
Natural language
Fuzzy quantifiers
Linguistic variables
Knowledge representation
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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.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0165-0114
1872-6801
DOI:10.1016/0165-0114(87)90048-0