支持个性化推荐的用户分类规则挖掘的研究

提出了一种应用决策树分类技术进行用户分类的方法 ,通过对 Web会话文件的处理、赋予类标记及决策树分类过程 ,实现了根据访问模式对用户的分类 ,以便个性化推荐和指导能够针对不同类别的用户进行 ,从而提高 E- Ser-vices中个性化服务的质量 .还讨论了待分类数据集中条件属性的选择和决策属性的类标记问题 ,给出了应用分类规则进行推荐的过程

Study of User Classification Rule Mining for Personalized Recommendation

A method of classifying users using decision tree technique was presented in the paper, which realized users classification according to their access patterns through processing Web session file, signing class and classifying users using decision tree, so that personalized recommendation and guide can be done for different users, and E-Services quality was improved. Moreover, the problems of how to select testing attributes and sign classifying attribute in data set used to be classified were discussed, and the steps of recommendation using user classification rules was given