摘要
构建个性化知识推荐系统是数字图书馆实现个性化信息服务的有效手段,推荐服务的关键在于完整地理解用户偏好并能准确作出判断。提出了一种基于语义扩展的知识推荐方法,通过分析读者文献检索、浏览的行为提取读者偏好,利用扩展激活模型建立读者偏好档案,据此对文献资源进行匹配和分级,从而向读者提供个性化的知识推荐服务。
Personalized knowledge recommendation is the effective measure to provide individual information service in digital library, however, a complete understanding of user profile and accurate recommendation are essential. In this paper, the method adopts a semantic--expansion approach to build the user profile by analyzing documents previously read by the person. Once the customer profile is constructed, personalized contents can be provided by the system.
出处
《图书馆学研究》
CSSCI
2008年第11期44-49,共6页
Research on Library Science
关键词
个性化服务
知识推荐
语义扩展
personalized information service knowledge recommendation semantic expansion
