摘要
从分析布尔向量与项集支持度的相关性质入手,利用计算机的逻辑"与"运算的高效率性以及通过布尔向量计算项集支持度的简单性,提出了基于布尔向量的关联规则挖掘算法。该算法只需一次扫描数据库,无需候选项集和"剪枝"操作,极大地提高了算法的效率。
Abstract： The algorithm of mining association rules based on Boolean vectors is proposed by analyzing relation theory of Boolean vectors and counting support of each item sets. It makes use of good efficiency of ＂AND＂ operation on Boolean vectors and the simplicity of counting support of each item sets. The improved algorithm overcomes the shortcoming of the traditional Apriori algorithm and can greatly enhance operational efficiency by only scanning database once, with no necessity of candidate item sets and pruning operation.
出处
《苏州科技学院学报（自然科学版）》
CAS
2008年第1期67-70,共4页
Journal of Suzhou University of Science and Technology （Natural Science Edition）
基金
江苏省高校哲学社会科学研究基金资助项目(06SJD870001)
