基于关联规则相关性分析的Web个性化推荐研究  

Research on Web personalized recommendation based on correlation analysis of association rule

作　　者：易芝[1] 汪林林[1] 王练[1] 

机构地区：[1]重庆邮电大学计算机科学与技术学院,重庆400065

出　　处：《重庆邮电大学学报（自然科学版）》2007年第2期234-237,共4页Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)

摘　　要：通过分析关联规则在Web个性化推荐中存在的问题,对Web个性化推荐的关联规则相关性分析算法进行改进,并进行了详细的论证和仿真实验。实验结果表明改进的算法能实现更低支持度的推荐,能提高推荐的准确率和速度。Through discussing the problems occur in Web personalized recommendations, an improved algorithm based on correlation analysis of association rule is proposed. The experiment is performed and the results show that the improved algorithm can not only realize Web personalization with lower support but also increase the recommendation precision and speed.

关 键 词：关联规则挖掘 关联规则相关性分析 WEB个性化推荐 支持度 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]