摘要
介绍一种Apriori的改进算法,该算法通过寻找大于最小支持计数的最大频繁项集,可以直接得到最终频繁项集,将改进算法应用到图书馆书目推荐服务中,并对改进算法与Apriori算法进行算法的性能分析及实验数据的运行时间对比,实验证明改进算法在运行速度和挖掘性能上较经典Apriori算法有显著提高。
This paper presents an improved Apriori algorithm. The algorithm can directly get the final frequent set by finding the maximum frequent set which is greater than the minimum support count, and can be applied to bibliographic recommendation service. Meanwhile, the paper makes a comparison of algorithm performance and running time of experimental data between disconnected Apriori algorithm and Apriori algorithm. The results show that disconnected Apriori algorithm than the Apriori algorithm has significantly improved both in running speed and excavating performance.
出处
《图书情报工作》
CSSCI
北大核心
2011年第5期109-112,共4页
Library and Information Service
基金
湖南省高校图工委科研课题"基于关联规则的书目推荐服务研究"(项目编号:2009L020)研究成果之一
作者简介
邓奇强，男，1979年生，馆员，技术服务部主任，发表论文6篇。
