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.
基于规则的推荐技术在数据集上挖掘项目关联和用户关联为当前用户做推荐。
Both item association and user association can be used to recommend for the current user in Rule-based recommendation.
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.
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.
应用推荐