Method for quantitative association rule mining based on decimal-binary conversion

Aiming at the issues on the method of quantitative association rule mining based on section partition, this paper introduces a method based on decimal-binary conversion. In the method, all numeric values are converted into the binary values, and then each digit of binary values is mapped to two Boolean attributes, the method of BAR mining is adopted for analyzing the association rules between the Boolean attributes. The advantages of this method is that no distortion is introduced during type conversion of source data, and the complexity of sequent BAR mining can be reduced efficiently.