摘要
随着新时代信息社会的快速发展,作为用户与产品沟通的平台,推荐系统越来越重要,人们对推荐系统的要求也变得越来越高。笔者详细剖析了协同过滤算法的常见问题与解决方案,提出一种新的融合协同过滤和XGBoost的推荐算法。通过分析项目和用户的潜在关系,提高推荐算法的准确性,为进一步优化推荐系统提供帮助。
With the rapid development of information society in the new era,as a platform for communication between users and products,recommender system is becoming more and more important.Therefore,our requirements for recommender system are becoming higher and higher.At the collaborative filtering algorithm in this paper,common problems and solutions of collaborative filtering algorithm,a new hybrid algorithm is proposed,the fusion of collaborative filtering and XGBoost recommendation algorithm was proposed,based on the analysis of the project and the user's potential,improve the accuracy of recommendation algorithm,for the further improvement recommendations to make a good help.
作者
宋雯婷
马佳琳
SONG Wenting;MA Jialin(School of Software,Shenyang Normal University,Shenyang Liaoning 110000,China)
出处
《信息与电脑》
2021年第16期56-58,共3页
Information & Computer
