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Fuzzy data compression based on data dependencies
Author(s) -
Ma Z. M.,
Zhang W. J.,
Mili F.
Publication year - 2002
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.10029
Subject(s) - computer science , fuzzy logic , data mining , axiom , fuzzy set operations , fuzzy classification , functional dependency , fuzzy set , fuzzy number , defuzzification , focus (optics) , artificial intelligence , theoretical computer science , mathematics , relational database , physics , geometry , optics
In this article, we focus on the issues of fuzzy data dependencies. After introducing the notion of semantic equivalence degree, fuzzy functional and multivalued dependencies are defined. A set of sound and complete inference rules, similar to Armstrong's axioms for classic cases, for fuzzy functional dependencies (FFDs) and fuzzy multivalued dependencies (FMVDs) are proposed. The strategies and approaches for compressing fuzzy values by FFDs and FMVDs are investigated. By such processing, the unnecessary elements are eliminated from a fuzzy value and its range is compressed. © 2002 Wiley Periodicals, Inc.