科技创新与应用2024，Vol.14Issue(11)：49-52,4.DOI:10.19981/j.CN23-1581/G3.2024.11.012
融合协同过滤的XGBoost在音乐推送上的应用研究
王方圆 1张国华1
作者信息
- 1. 湖南工业大学 理学院,湖南 株洲 412000
- 折叠
摘要
Abstract
This paper studies a music recommendation algorithm based on fusion collaborative filtering and XGBoost.First,we used a collaborative filtering algorithm to calculate the similarity between users or items and obtained an initial list of recommendations as a recall set.Considering that the music recommendation list generated by collaborative filtering method still has some problems such as large computation and sparsity,the recommendation list is not so accurate.Next,we carried out feature extraction and feature engineering for each item in the recommendation list,and used XGBoost algorithm to predict it and got the final recommendation list.The contribution of this study is to propose a new music recommendation algorithm,which combines the advantages of collaborative filtering and XGBoost algorithm to get more accurate music recommendation list.关键词
XGBoost/协同过滤/推荐/应用/音乐推送Key words
XGBoost/collaborative filtering/recommendation/application/music push分类
信息技术与安全科学引用本文复制引用
王方圆,张国华..融合协同过滤的XGBoost在音乐推送上的应用研究[J].科技创新与应用,2024,14(11):49-52,4.
