摘要
为了使个性化新闻推荐系统中,用户兴趣模型更好的被系统所理解,提出了用户兴趣模型的表示和更新机制。根据新闻领域的特点,基于ODP构建新闻领域本体,建立基于领域本体的加权关键词用户兴趣模型。基于用户行为,分析用户对页面的兴趣度,改进了用户兴趣模型的表示和更新方式。该模型能准确描述用户兴趣的动态变化过程,区分用户的长期和短期兴趣。随着用户浏览新闻页面的不断增加,该模型不断自我更新,跟踪用户兴趣变化,并能发现用户新的兴趣。
In order that personalized news recommendation system can understand user interest model better, we propose an approach of building and updating user interest model. The article build news domain ontology based on ODP and build weighted-keywords user interest model based on domain ontology, in accordance with the characteristics of news information. We gather user behavior and analysis the user interest to the news based on the behavior. In the study, we improve the presentation and updating mechanism of user interest model. The model can describe the dynamic changes of user interest accurately. It can differentiate long-term and short-term interests as well. As more and more news pages are browsed, it can be updated and trace the changes of interests and detect the new coming interests.
出处
《情报科学》
CSSCI
北大核心
2014年第5期127-130,共4页
Information Science
基金
山东省软科学项目(2011RKGB5025)
关键词
兴趣模型
本体
更新机制
user interest model
ontology
updating mechanism
作者简介
宫玲玲（1988-），女，山东烟台人，硕士研究生，主要从事情报学、网络信息系统研究．
