摘要： 在分析基于位向量和无向图Apriori的基础上，提出一种改进的关联规则算法VGApriori。该算法将事务数据库的多次扫描和支持度计算转化为位向量的计算，将频繁项集的挖掘转换为无向图的完全子图挖掘，进一步缩减候选项集，提高频繁项集的发现效率。该算法在高校教学管理系统应用中取得较好的效果。

关键词: 关联规则, Apriori算法, 位向量, 无向图, 候选项集

Abstract: This paper proposes an improved Apriori algorithm VGApriori, which is based on bit vector and undirected graph methods. The algorithm maps the database into a Boolean matrix by scanning the database, and the frequent itemsets can be generated by simple vector operation and undirected itemsets Graph search. The efficiency is distinctly improved in discovers frequent itemsets. This algorithm is applied in college teaching management and achieves good results.

Key words: association rule, Apriori algorithm, bit vector, undirected graph, candidate itemsets

中图分类号: 

• TP311