摘要
针对当前推荐技术普遍存在的产品内容分析难度大、用户评价信息稀疏和新用户推荐等问题,基于协同过滤技术,引入人口统计信息分析技术,提出一种混合推荐技术,并在Web资源系统中实现一个推荐模型实例。实验结果表明,应用该技术不但能够解决上述问题,相较传统的推荐技术,还能有效提高推荐质量。
Aiming at the common problems including difficulties in product content analysis, low density in customer scores and new customer recommendation, existing in recommendation technologies today, this paper designs a blending recommendation technology which employs demography analysis technology based on cooperating filtering technology, and implements a recommendation model instance in a Web resource system. Experimental results indicate that this technology can solve the problems mentioned before, and efficiently improve recommendation quality comparing to the traditional technologies.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第22期248-250,253,共4页
Computer Engineering
基金
国家"十一五"科技支撑计划基金资助项目"面向高性能宽带信息网的互动教育服务应用示范"(2007BAH09B05)
关键词
混合推荐技术
用户聚类
协同过滤
个性化资源推荐
blending recommendation technology
customer clustering
cooperating filtering
individualized resource recommendation
