混合推荐算法在基于机器学习的影片推荐系统中的应用  

Application of Hybrid Recommendation Algorithm in Film Recommendation System Based on Machine Learning

作　　者：赵峰[1] ZHAO Feng(Taizhou Polytechnic College,Taizhou Jiangsu 225300,China)

机构地区：[1]泰州职业技术学院智能制造学院,江苏泰州225300

出　　处：《泰州职业技术学院学报》2023年第4期52-55,共4页Journal of Taizhou Polytechnic College

摘　　要：文章主要以实现基于机器学习的影片推荐系统为背景,具体应用适合的机器学习算法,包括采用基于隐语义模型的协同过滤、基于加权因子的混合协同过滤和基于内容的推荐算法进行混合推荐的算法,解决新用户冷启动问题,以期提高影片推荐系统的实时性。Traditional recommendation algorithms often encounter problems such as small recommendation changes,slow running speed,and poor performance when facing massive amounts of data and iterations.Based on the back⁃ground of realizing a movie recommendation system based on machine learning,this paper specifically applies suit⁃able machine learning algorithms,including collaborative filtering based on semantic model,hybrid collaborative fil⁃tering based on weighting factor and hybrid recommendation algorithm based on content,to solve the cold start problem of new users,so as to improve the real-time performance of the movie recommendation system.

关 键 词：影片推荐系统 协同过滤 混合推荐 算法 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]