摘要
个性化影片推荐服务是解决目前网络及家庭数字电视应用中影片资源迅速增长,用户"信息迷航"的有效方法。针对影片点播应用,给出了个性化影片推荐服务的体系结构、影片数据建模、用户兴趣偏好模型进行了研究,实现无需用户输入传统推荐方法所需相关个性兴趣信息即可返回与用户当前兴趣相关的影片推荐列表,提出了基于本体论的影片模型,并建立用户兴趣偏好模型,给出了对推荐过程中结合用户信息反馈对推荐结果进行自适应的调整算法。
Personalized Movie Recommendation is an effective solution for quickly increased video resources and user＇s ＂Information Lost＂ in interactive video application. Aiming at the Movie on Demand application the system framework of our personalized movie recommendation service, movie data model and user profile model are studied, and the recommended listing for interest-relevant movies without any user profile information as required in traditional recommendation is realized. The authors propose Ontology-based Movie Model and build a new algorithm to find out user＇s interest and preference model, finally, give an adaptive algorithm to adjust recommendation result combined with user＇s feedback.
出处
《电子技术（上海）》
2009年第10期62-65,共4页
Electronic Technology
基金
国家863项目(2007AA01Z235)
安徽省优秀青年科技基金资助项目
项目编号:08040106910
关键词
个性化服务
影片推荐系统
本体论
用户模型
自适应调整算法
V ideo personalization
movie recommendation system
ontology
user profile
adaptive algorithm
