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Fuzzy identification in fuzzy databases: The nuanced relational division
Author(s) -
Mouaddib Noureddine
Publication year - 1994
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550090506
Subject(s) - fuzzy logic , weighting , extension (predicate logic) , fuzzy classification , division (mathematics) , identification (biology) , operator (biology) , computer science , fuzzy set operations , data mining , relation (database) , fuzzy number , artificial intelligence , mathematics , fuzzy set , arithmetic , biology , medicine , biochemistry , chemistry , botany , repressor , transcription factor , gene , radiology , programming language
In the present article we review the main research works in fuzzy databases; propose an extension of relation division operator to fuzzy databases; provide a model for fuzzy information and resolve the identification problem in fuzzy databases. For this, three notions are relevant: (a) the concept of nuanced information for representing fuzzy values and the associated nuance, (b) the nuanced division operator, (c) the possibility of weighting attributes in order to express data and query pertinence and trust. We then show how to resolve the problem of fuzzy identification with the nuanced division operator. © 1994 John Wiley & Sons, Inc.