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This paper presents methods of dividing quantitative attributes into fuzzy domains with multi-granularity representation of data based on hedge algebra approach. According to this approach, more information is expressed from general to specific knowledge by explored association rules. As a result, this method brings a better response than the one using usual single-granularity representation of data. Furthermore, it meets the demand of the authors as the number of exploring rules is higher.

PARTITION FUZZY DOMAIN WITH MULTI-GNANULARITY REPRESENTATION OF DATA BASING ON HEDGE ALGEBRA APPROACH