典型文献
Personalized movie recommendation method based on ensemble learning
文献摘要：
Aiming at the personalized movie recommendation problem, a recommendation algorithm in-tegrating manifold learning and ensemble learning is studied. In this work, manifold learning is used to reduce the dimension of data so that both time and space complexities of the model are mitigated. Meanwhile, gradient boosting decision tree (GBDT) is used to train the target user profile prediction model. Based on the recommendation results, Bayesian optimization algorithm is applied to optimize the recommendation model, which can effectively improve the prediction accuracy. The experimental results show that the proposed algorithm can improve the accuracy of movie recommendation.
文献关键词：
中图分类号：
作者姓名：
YANG Kun;DUAN Yong
作者机构：
School of Information Science and Engineering,Shenyang University of Technology,Shenyang 110870,P.R.China
文献出处：
引用格式：
[1]YANG Kun;DUAN Yong-.Personalized movie recommendation method based on ensemble learning)[J].高技术通讯（英文版）,2022(01):56-62
A类：
tegrating
B类：
Personalized,movie,recommendation,method,ensemble,learning,Aiming,personalized,problem,algorithm,manifold,studied,In,this,work,used,reduce,dimension,data,that,both,space,complexities,model,are,mitigated,Meanwhile,gradient,boosting,decision,tree,GBDT,train,target,user,profile,prediction,Based,results,Bayesian,optimization,applied,optimize,which,can,effectively,improve,accuracy,experimental,show,proposed
AB值：
0.546878
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