摘要
针对当前Web挖掘环境下个性化服务的性能不够高效的问题,运用协同过滤技术的理论与方法,研究了一种基于协同过滤的推荐阀值方法,并且提出了一种在线推荐模型。实验表明,在提高Web个性化服务方面,该模型具有更高的效率。
Collaborative filtering (CF) is a popular technology for building personalized service system. To improve personalized service performance under web-mining environment, a method of recommending threshold based on collaborative filtering is presented and a new online personalized recommendation model is proposed. Experimental results show this recommendation model is more effeetive in improving web personalized service.
出处
《北京信息科技大学学报(自然科学版)》
2013年第6期42-45,共4页
Journal of Beijing Information Science and Technology University
基金
国家自然科学基金面上资助项目(61370065)
关键词
协同过滤
WEB挖掘
个性化服务
collaborative filtering
web mining
personalized service