正负关联规则挖掘在电子商务中的应用研究

摘要

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.%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.