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AuthorElloumi, Samir
AuthorJaam, Jihad
AuthorHasnah, Ahmad
AuthorJaoua, Ali
AuthorNafkha, Ibtissem
Available date2009-12-30T07:40:05Z
Publication Date2003-06-20
Publication NameInformation Sciences
CitationSamir Elloumi, Jihad Jaam, Ahmed Hasnah, Ali Jaoua, Ibtissem Nafkha, A multi-level conceptual data reduction approach based on the Lukasiewicz implication, Information Sciences, Volume 163, Issue 4, 18 June 2004, Pages 253-262
AbstractStarting from fuzzy binary data represented as tables in the fuzzy relational database, in this paper, we use fuzzy formal concept analysis to reduce the tables size to only keep the minimal rows in each table, without losing knowledge (i.e., association rules extracted from reduced databases are identical at given precision level). More specifically, we develop a fuzzy extension of a previously proposed algorithm for crisp data reduction without loss of knowledge. The fuzzy Galois connection based on the Lukasiewicz implication is mainly used in the definition of the closure operator according to a precision level, which makes data reduction sensitive to the variation of this precision level.
PublisherElsevier Science Inc
SubjectFuzzy data reduction
SubjectLukasiewicz implication
SubjectFuzzy Galois connection
SubjectPrecision level
TitleA multi-level conceptual data reduction approach based on the Lukasiewicz implication

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