Quantitative Association Rules Mining Algorithm Based on Matrix

Abstract

How to improve the efficiency of discovering the frequent item sets is a major problem in mining association rules. This paper analysised the idea and performance of the general quantitative association rules algorithm ,and put forward a quantitative association rules mining algorithm based on matrix, the new algorithm firstly transformed quantitative database into Boolean matrix ,then used boolean "and" operation to generate frequent item sets on matrix vector .It effectively solved the bottleneck of Apriori algorithm which iteratively produced frequent item sets in the general quantitative association rules algorithm . The results of experiments and analysis showed that the new algorithm effectively improved the efficiency of mining quantitative association rules.