摘要
由于推荐系统应用较广泛,众多研究学者致力于推荐系统性能的研究与改进。经过对影响推荐系统效果的两大因素——用户和物品的研究,对提高推荐系统的性能进行分析和建模。依据多方因素,构建用户画像。根据用户标签和物品特征的匹配程度进行推荐研究,为后续提高推荐系统准确率和实时性提供参考。
At present,the recommendation system is applied in many fields,and many research scholars are also working to recommend the improve. ment of system performance. This paper conducts related research on the two major factors affecting the effectiveness of the recommenda. tion system-users and articles,and analyzes and models the performance of the recommendation system. The user portrait is constructed from various factors,and the recommendation degree of the user label and the item feature is used to provide a reference for improving the accuracy and real-time of the recommendation system.
作者
黎丹雨
LI Dan-yu(School of Information Science,Xinhua College,Sun Yat-sen University,Guangzhou 510000)
出处
《现代计算机》
2019年第18期51-54,共4页
Modern Computer
基金
高等教育教学改革项目(No.2017J001)
关键词
推荐系统
用户画像
标签
Recommendation System
User Portrait
Label
