基于新闻时效性的协同过滤推荐算法  

Collaborative Filtering Recommendation Algorithm Based on News Timeliness

作　　者：冯文杰 熊翱[1] FENG Wen-Jie;XIONG Ao(Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China)

机构地区：[1]北京邮电大学网络技术研究院,北京100876

出　　处：《计算机系统应用》2018年第5期193-197,共5页Computer Systems & Applications

摘　　要：提出一种基于新闻时效性的协同过滤推荐算法.首先对新闻的时效性进行了特征分析,建立了新闻时效性模型,然后结合新闻时效性改进了基于用户的协同过滤算法.最后进行了仿真实验,实验结果表明,该方法可以有效提高推荐算法的性能,改善新闻推荐准确度和召回率.A collaborative filtering recommendation algorithm based on news timeliness is proposed. Firstly, by analyzing the characteristics of the news timeliness, the timeliness model of news is established. Then, the user-based collaborative filtering algorithm is improved combining the news timeliness model. Finally, the experimental results show that this method can highly enhance the performance of user-based collaborative filtering algorithm, and ameliorate the accuracy and recall rate of news recommendation.

关 键 词：协同过滤 新闻推荐 时效性模型 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]