一种基于矩阵和权重改进的Apriori算法

An Improved Apriori Algorithm Based Matrix and Weight

提出基于矩阵和权重的一种改进算法——MW_Apriori算法.该算法首先通过扫描一次事务数据库来构造0-1事务矩阵,其次赋予项和事务权重,并计算项的权重支持度,从而得到频繁项集.实验结果表明,MW_Apriori算法避免了数据库的重复扫描,使得时间和空间的耗费显著减少,同时能有效地挖掘出隐藏的、更有价值的事件.

An improved algorithm,which is called MW_Apriori algorithm is proposed based on the matrix and weight in this paper.Firstly,build the 0-1transaction matrix by scanning transaction database.Then items and transactions are assigned to weights,and the weighted support of items are caculated,accordingly gettig the frequent itemsets.Experiments show that MW_Apriori algorithm avoids rescanning the database,making the cost of time and space significantly reduced,at the same time can effectively mine the hidden and valuable rare events.