Abstract
Mining fuzzy correlation rules is the task of finding correlation relationship between the two fuzzy itemsets in a transactional database. In many situations, however, fuzzy itemsets other than the two under consideration are also responsible for the observed correlation relationship, the effects of these fuzzy itemsets may influence the observed correlation relationship, and thus, the real correlation relationship cannot be really obtained. Therefore, in this research, the analysis of fuzzy partial correlation is used to construct a new algorithm for discovering the fuzzy partial correlation rule. The fuzzy partial correlation analysis can provide us the correlation relationship between two fuzzy itemsets when the influences of other fuzzy itemsets are held constant. Thus, by using the fuzzy partial correlation analysis, the fuzzy partial correlation rules which can show us the strong correlation relationship between the fuzzy itemsets when the influences of other fuzzy itemsets are removed can be effectively generated.
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