摘要
网络上的信息越来越丰富和杂乱,大家都希望能在尽可能短的时间内从网上获得有效的信息,因此对于推荐系统的要求越来越严格。在推荐算法已经发展较完善的背景下,本文对协同过滤算法、基于内容的推荐、基于流行度的推荐、基于模型的推荐、基于关联规则的推荐以及混合算法等不同的推荐算法进行分析并判断各种算法的优势和劣势,并对推荐算法的发展趋势提出了简单的看法,对于推荐系统的研究以及核心算法的选择具有良好的参考价值。
The information on the network is more and more abundant and disordered.We all hope to get effective information from the Internet as soon as possible,so the requirements for the recommendation system are more and more strict.In the context of the development of recommendation algorithms,this paper analyzes different recommendation algorithms,such as collaborative filtering algorithm,content-based recommendation,popularity based recommendation,model-based recommendation,association rule-based recommendation and hybrid algorithm,and judges the advantages and disadvantages of various algorithms,and puts forward a simple view on the development trend of recommendation algorithm The research of recommendation system and the selection of core algorithm have good reference value.
作者
邱莉萍
范腾
刘睿卿
唐斌斌
Qiu liping;Fan Teng;Liu Ruiqing;Tang Binbin(School of computer science,Nanhua University,Hengyang Hunan,421000;Chuanshan college,Nanhua University,Hengyang Hunan,421000)
出处
《电子测试》
2020年第17期129-130,共2页
Electronic Test
关键词
推荐算法
协同过滤
关联规则
混合算法
Recommendation algorithm
collaborative filtering
association rules
filtering algorithm
