A developed apriori algorithm based on frequent matrix

Abstract

Apriori is the most famous frequent pattern mining method. It scans dataset repeatedly and generate item sets by bottom-top approach. In order to reduce time complexity, we proposed a modified algorithm named as Frequent Matrix Apriori (FMA). Firstly, FMA scans the dataset only once to store frequent item information in a frequent matrix. Then, FMA discretize the matrix by the minimum support parameter which is generated automatically. Thirdly, it scans the discretized frequent matrix and find the most frequent item sets recursively. Experimental results proved that FMA is more effective than Apriori on time consuming with similar accuracy.