  Multidimensional association rule mining searches for interesting
relationship among the values from different dimensions or attributes in a
relational database. In this method the correlation is among set of dimensions
i.e., the items forming a rule come from different dimensions. Therefore each
dimension should be partitioned at the fuzzy set level. This paper proposes a
new algorithm for generating multidimensional association rules by utilizing
fuzzy sets. A database consisting of fuzzy transactions, the Apriory property
is employed to prune the useless candidates, itemsets.
