摘要
随着互联网的普及以及音乐库的高速更新换代,用户对音乐的需求变得越来越大,传统的推荐算法已经无法满足用户及时准确地寻找到所喜欢的音乐。因此,针对传统音乐推荐算法的不足,通过对协同过滤推荐算法的分析,提出基于内容和协同过滤加权融合的音乐推荐算法。与传统推荐算法及部分相关推荐算法比较,加权融合推荐算法计算出的推荐结果可以更高效快速地将用户感兴趣的音乐推荐出来。
With the popularity of the internet and the high-speed update of music libraries,users’demand for music has become greater and greater,and the traditional recommendation algorithms have been unable to satisfy users in finding their favorite music in time and accurately.Therefore,in view of the shortcomings of traditional music recommendation algorithms,we proposes a music recommendation algorithm based on content and collaborative filtering weighted fusion through the analysis of collaborative filtering recommendation algorithms.Compared with the traditional recommendation algorithm and some related recommendation algorithms,the recommendation results calculated by this weighted fusion recommendation algorithm can more efficiently and quickly recommend the music that users are interested in.
作者
彭余辉
张小雷
孙刚
PENG Yuhui;ZHANG Xiaolei;SUN Gang(School of Computer and Information Engineering,Fuyang Normal University,Fuyang 236037,China)
出处
《安庆师范大学学报（自然科学版）》
2021年第2期44-48,53,共6页
Journal of Anqing Normal University(Natural Science Edition)
基金
安徽省教育厅自然科学研究重点项目(KJ2018A0328,KJ2019A0532,KJ2019A0542,KJ2020ZD48)
阜阳师范大学大数据与智能计算创新团队(XDHXTD201703)
阜阳市人文社会科学研究专项项目(FYSK2019QD10)。
关键词
内容
协同过滤
融合
音乐推荐算法
content
collaborative filtering
fusion
music recommendation algorithm
