摘要
针对网络电视视频个性化推荐问题,提出了一种面向网络视频的基于内容和协同过滤组合推荐系统。系统整合了基于内容推荐和协同过滤推荐的优点,并在一定程度上避免了基于内容推荐或协同过滤推荐各自的缺点。设计了组合推荐系统各功能模块结构及其算法,实现了网络视频的用户个性化推荐。实验结果表明,组合推荐系统模型与算法优于单一推荐算法,获得了较高的推荐准确性。
Aiming at the personalized recommendation for internet television video, a hybrid recommendation system integrated by content-based and collaborative filtering was proposed. The system integrates the merits of the traditional recommendation systems based on above two methods, and avoids the disadvantages of them to some extent. This paper designs each function module structure and its algorithm, and realizes the personalized recommendation for internet television users. The experimental results show that the presented recommendation model and algorithm is superior to a single recommendation algorithm and can be obtained a higher predictive accuracy.
出处
《计算机工程与设计》
CSCD
北大核心
2013年第12期4379-4383,共5页
Computer Engineering and Design
基金
国家973重点基础研究发展计划基金项目(2012CB724106)
文化部科技创新基金项目(13-2013)
关键词
网络视频
基于内容
协同过滤
组合推荐
个性化推荐
internet video
content-based
collaborative filtering
hybrid recommendation
personalized recommendation
