Abstract: Association rules discovery is an important research topic in data mining.The article will mine Data-Item set compression to a Boolean Vector Matrix.The algorithm only needs to scan the database one time and rational use of data storage structure so that it would not generate a large number of candidate sets.Experiment results indicate that the algorithm is not only simple，but also has good efficiency compared with the Apriori algorithm.When you mine a large database and long item-set，the mining effect of this way is more visible than the Apriori algorithm.

摘要： 关联规则发现是数据挖掘中的重要研究课题之一。将挖掘的数据事务集压缩到一个布尔型向量矩阵中，只需扫描数据库一次，合理利用数据存储结构，且不会产生大量的候选集。实验表明，该算法不仅实现简单，与经典的Apriori算法进行相比，效率也有大幅提高，特别对大事务集、长项目集数据挖掘效果更为明显。