实验表明，该算法比使用基于关联规则和基于用户事务的推荐算法的精确性有较大幅度的提高。
The experiments show that, comparing with the recommendation algorithms based on association rule or on user transaction, the algorithm precision is improved greatly.
UAPOMR系统的推荐算法包括基于事务聚类的推荐和基于关联规则聚类的推荐。
The recommended algorithm of UAPOMR system includes recommendation based on transaction_clusters and recommendation based on association rules clusters.
提出了一个基于用户浏览兴趣的推荐规则集生成算法，在度量用户浏览兴趣时综合考虑了用户浏览时间和对该页面的访问次数。
A algorithm for generating recommendation rule set is proposed based on the users browsing interest, which is measured by considering synth.
应用推荐