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Received:September 10, 2017 Revised:September 30, 2017
Received:September 10, 2017 Revised:September 30, 2017
中文摘要: 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.
Abstract: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.
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冯文杰,熊翱.基于新闻时效性的协同过滤推荐算法.计算机系统应用,2018,27(5):193-197
FENG Wen-Jie,XIONG Ao.Collaborative Filtering Recommendation Algorithm Based on News Timeliness.COMPUTER SYSTEMS APPLICATIONS,2018,27(5):193-197
冯文杰,熊翱.基于新闻时效性的协同过滤推荐算法.计算机系统应用,2018,27(5):193-197
FENG Wen-Jie,XIONG Ao.Collaborative Filtering Recommendation Algorithm Based on News Timeliness.COMPUTER SYSTEMS APPLICATIONS,2018,27(5):193-197
