【摘要】 基于MMS_Cumu late和GP-Apriori算法,提出一种针对图书馆新书推荐服务特点的广义关联规则挖掘算法MAR_LCR。不仅能挖掘出形如“读者-图书”的广义关联规则,而且还允许用户为不同的项设置不同的最小支持度。通过对候选集的产生过程进行改进,可大大压缩搜索空间。实验结果表明,MAR_LCR算法是有效的。最后,提出新书推荐模型。更多还原

【Abstract】 Based on MMS_Cumulate algorithm and GP-Apriori algorithm,a data mining algorithm,MAR_LCR is proposed for library new book recommendation service which is capable of finding generalized association rules in the form of "reader-book" and allows the user to specify multiple minimum supports for different items.The search space is greatly cut down by improving the process of candidate generation.Experiment results show that the MAR_LCR algorithm is highly effective.Finally,a new book recommendation model is proposed.更多还原