网络环境中个性化推荐系统研究

Study of Personalized Recommendation System on Internet

提出一个结合本体论及通用个人资料的个性化推荐模式。首先以网络分类服务作为本体论来解释用户的网络浏览行为,以此挖掘用户的偏好;其次,利用Web使用挖掘技术过滤多余的浏览记录,增强个性化的准确度;最后,利用本体论的层次结构特点,从用户偏好类别中挖掘其潜在偏好,产生符合用户特征的通用个人资料。

This paper presents a personalized recommendation system by using Ontology and universal user profile. Firstly, the Website directory service is used as Ontology to identify user＇s browsing behaviors on Internet to discover user preferences. Secondly, the redundant Web logs are filtered out by using Web usage mining technology , which can enhance the accuracy of personalization. Finally, from user preference directory, user＇ s potential preference is discovered by using the hierarchical property, that is, to bring out the universal user profile which match the characteristics of the user.