摘要
用户兴趣建模是个性化服务的核心,考虑到情景信息对用户偏好的影响,对融和情景信息的用户行为日志数据进行深入研究,提出了一种基于情景信息的用户兴趣建模方法.该方法首先通过计算情景相似度来获得用户当前情景的近似情景集;对"用户-兴趣项-情景"三维模型采用情景预过滤的方法降维处理.然后根据用户浏览内容得到用户兴趣主题,分析页面内容得到每种主题的兴趣关键词,建立基于层次向量空间模型的用户兴趣模型.实验结果表明,本文提出的基于情景信息的用户兴趣模型对用户兴趣的预测误差控制在9%以内,是有效的.
The user＇s interest model is the core component in a personalized services system. Considering the impact of context information on user interests, this paper deeply studies the user behavior log data based on context information, and proposes a user interest modeling method based on context information. First, we get the user＇s context set by calculating the context similarity, and reduce the dimension of the ＂user-interest item-context＂ 3D model through the method of context pre-filtering. Second, user browsing content forms interest topic, and web page content forms interest keyword. Then a hierarchical vector space model is set up based on the user profile. The experimental result shows that the prediction error of user interest degree is controlled within 9%, which is effective.
出处
《计算机系统应用》
2017年第1期152-156,共5页
Computer Systems & Applications
