摘要
针对传统信息推荐方式精度偏低的问题,引入用户画像作为推荐基础,在深入研究文本分类和用户行为后,提出一种基于动态用户画像的推荐方法.该方法通过动态分析用户历史数据,预测用户的兴趣变化趋势,从而实现动态推荐.离线实验证明,该方法在预测用户偏好变化方面具有一定优势,相较于传统的基于标签的信息推荐,提高了推荐精度.
To solve the problem about low accuracy of traditional information recommendation method, this paper introduces the user portrait as the recommended basis, and proposes the recommendation method based on dynamic user portraits after further studying about the text classification and user behavior. By dynamically analyzing the user＇s historical data and predicting the user＇s interest trends, this method achieves dynamic recommendations. The off-line experiment improves that this method has some advantages in predicting user preference changes compared with the traditional label-based information recommendation, and it improves the recommendation accuracy.
作者
刘勇
吴翔宇
解本巨
LIU Yong;WU Xiang-Yu;XIE Ben-Ju(Information Science and Technology Academy, Qingdao University of Science and Technology, Qingdao 266061, China;（Qingdao HZCJ New Information and Technology Co. Ltd., Qingdao 266000, China)
出处
《计算机系统应用》
2018年第6期236-239,共4页
Computer Systems & Applications
关键词
信息推荐
用户画像
用户行为
information recommendation
user portrait
user behavior
