本論文修改Apriori演算法對候選項目組掃瞄交易資料庫的方式，加入刪除未包含候選項目組之交易資料的概念，提出兩個有效率的演算法，稱之為efficiency_Apriori演算法及efficiency_MQA-1演算法，分別探勘關聯規則、及包含有項目數量的關聯規則。從實驗評估中顯示，efficiency_Apriori演算法及efficiency_MQA-1演算法可分別有效提昇Apriori演算法、及MQA-1演算法的執行效能。

This paper modifies the approach of scanning the transaction database of the Apriori algorithm for candidate itemsets, and adds the idea of the deleting the transaction data which do not contain the candidate itemsets. Two algorithms, called efficiency_Apriori and efficiency_MQA-1, are proposed to mine association rules and association rules including
the quantities of items, respectively. The experiments show that the efficiency_Apriori algorithm and the efficiency_MQA-1 algorithm can effectively improve the performance of the Apriori algorithm and the MQA-1 algorithm, respectively.