Apriori_T Algorithm based on item sets information table

Discovery of association rules in transaction database is a very important research area of data mining. The discovery of association rules includes two steps, finding out all frequent item sets at first, and then creating strong association rules by frequent item sets. Apriori algorithm is a basic algorithm of finding frequent item sets, which is simple and easy to implement. But apriori algorithm needs to scan the transaction database for several times, and creates a lot of candidate items, which leads to low efficiency. An algorithm named Aprioi_T based on item sets information table is proposed to improve the efficiency. Aprioi_T algorithm avoids scanning the transaction database repeatedly, and reducing the I/O spending of the system, overcomes the defects of Apriori algorithm.