关联规则和事务集分组技术在图书馆个性化推荐系统中的应用研究

The Application Research of Association Rules and Affairs Grouping Technique in Library Individualized Recommendation System

通过对经典Apriori算法挖掘过程的分析，提出了基于事务集分组技术的关联算法；该算法先按专业、年级和借阅数量等特性对读者聚类．然后分别对每个类进行关联分析，图书推荐质量较经典Apriori算法有所提高。

This paper puts forward the correlation algorithm which is based on affairs grouping technique by the analysis of classical Apriori algorithm＇s mining process .Readers are clustered by profession, grade, borrowing amount and other characteristics. Then, correlation analysis is made on each group. The book recommendation quality of this algorithm is better than the classical Apriori algorithm.