基于垂直事务关系的快速Apriori算法

A fast Apriori algorithm based on vertical transcation relation

针对Apriori算法需要多次扫描数据库的缺陷,提出一种基于垂直事务关系的改进算法XApriori。该方法对原始事务数据库扫描后,采用项集事务垂直对应关系的位集合数据存储结构,并构建逻辑生成候选项集策略,利用数值统计的方法生成候选项集并确定频繁项集,实现关联规则的挖掘。对比实验结果表明,改进算法比Aprior算法关联规则挖掘的效率有所提高。

A fast algorithm XApriori algorithm based on vertical transaction relation is proposed to overcome the shortcomings of the Apriori algorithm repeatedly scanning the database many times. After the original transaction database is scanned and the bit set data storage structure of item sets transaction vertical correspondence relationship is adopted, the local generation candidate item sets strategy is constructed. Then the candidate item sets are generated by means of numerical statistics and the frequent item sets are determined. Theoretical analysis and experimental results show that the improved XAPriori algorithm is more efficient than Aprior algorithm.