A multi-level conceptual data reduction approach based on the Lukasiewicz implication

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Author Elloumi, Samir en_US
Author Jaam, Jihad en_US
Author Hasnah, Ahmad en_US
Author Jaoua, Ali en_US
Author Nafkha, Ibtissem en_US
Available date 2009-12-30T07:40:05Z en_US
Publication Date 2003-06-20 en_US
Citation Samir 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 en_US
URI http://dx.doi.org/10.1016/j.ins.2003.06.013 en_US
URI http://hdl.handle.net/10576/10582 en_US
Abstract Starting 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. en_US
Language en en_US
Publisher Elsevier Science Inc en_US
Subject Fuzzy data reduction en_US
Subject Lukasiewicz implication en_US
Subject Fuzzy Galois connection en_US
Subject Precision level en_US
Title A multi-level conceptual data reduction approach based on the Lukasiewicz implication en_US
Type Article en_US


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