正负关联规则挖掘在电子商务中的应用研究  

Application Research of Positive and Negative Association Rules Mining in the E-Commerce

作　　者：纪怀猛[1] 

机构地区：[1]福州大学阳光学院基础部,福州350015

出　　处：《计算机与数字工程》2012年第6期148-150,共3页Computer & Digital Engineering

摘　　要：如何根据用户当前的访问行为,预测他下一个感兴趣的商品,做出针对性的推荐成为电子商务的一个重要研究内容。文章提出了一种不需产生大量非频繁项集的关联规则挖掘算法,该算法利用相关性很好的改善了经典Apriori算法中存在大量冗余规则问题。最后通过实验证明了算法的有效性。It is an important e-commerce research field to predict a user＇s next commodity of interest and then,to recommend a specific based on his current visit behavior.In this paper,an association rule mining algorithm that does not need to produce a large number of infrequent item sets is proposed.By using the correlation of a rule,a good solution can be made to the problem of the existence of a large number of redundant rules in the classic Apriori algorithm.Finally,the effectiveness of the algorithm is proved by experiments.

关 键 词：负关联规则 电子商务 相关性 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]