摘要
提出基于关联的聚类分析方法,挖掘具有相似访问兴趣的用户访问模式,分离不相关的用户模式,并提出基于关联的聚类算法。实验证明,该算法大量减少不相关的用户访问模式,提高个性化推荐质量。为进一步研究个性化推荐技术奠定基础。
In order to provide better personalized recommendation service, and cluster analysis methods based on association has been improved, which mining model of the users access with interests of similar access, and user model of non--related is separated a clustering. An algorithm based on association is proposed. It is proved that the algorithm can reduce a large number of user model of non--related, so improve the quality of the personalized recommendations. It is laid the foun- dation to further study the personalized recommendation technology.
出处
《计算技术与自动化》
2010年第1期130-133,共4页
Computing Technology and Automation
关键词
关联规则
数据挖掘
聚类
个性化推荐
association rules
data mining
clustering
personalized recommendation
