A Fast Algorithm for Mining Association Rules

• 作 者: 黄刘生 陈华平 王洵 陈国良
• 机 构: National High Performance Computing Center, Department of Computer Science University of Science & T
• 出 处: 计算机科学技术学报(英文版)
• 发表日期: 2000年6期
• 关键词: database data mining large itemset association rule minimum support minimum conf

In this paper, the problem of discovering association rules between items in a large database of sales transactions is discussed, and a novel algorithm,BitMatrix, is proposed. The proposed algorithm is fundamentally different from the known algorithms Apriori and AprioriTid. Empirical evaluation shows that the algorithm outperforms the known ones for large databases. Scale-up experiments show that the algorithm scales linearly with the number of transactions.