摘要
随着网络的发展,信息过载成为人们不得不面对的问题,个性化推荐系统便是解决该问题的有力工具,并受到了广泛的关注和研究。文章对推荐系统的定义进行了简单描述,分析比较了推荐系统目前较为流行的诸如关联规则、协同过滤类等推荐算法的含义和优缺点,提出了目前推荐系统尚未解决的问题。
With the development of the network,information overload has become a problem that people have to face.The personalized recommendation system is a powerful tool to solve the problem,and has received extensive attention and research.This paper briefly describes the definition of the recommendation system,analyzes and compares the meaning,advantages and disadvantages of the recommendation algorithms which are currently popular in the recommendation system,such as Association rules and Collaborative filtering etc.,and puts forward some problems that are still unresolved in recommendation system.
作者
代丽
樊粤湘
Dai Li;Fan Yuexiang(School of Economic Management,Zhejiang Sci-Tech University,Hangzhou,Zhejiang 310018,China)
出处
《计算机时代》
2019年第6期9-11,15,共4页
Computer Era
基金
国家自然科学基金项目(51575496)
中国博士后科学基金第62批面上一等资助项目
关键词
推荐系统
推荐算法
关联规则
协同过滤
recommendation system
recommendation algorithm
Association rules
Collaborative filtering