摘要
近年来,商品的种类和数量迅速增长,使消费者难以找到感兴趣的产品。各大电商平台开始利用推荐技术为用户提供更好的服务,其中使用最多的是协同过滤推荐算法。主要概括了协同过滤推荐算法的核心思想,归纳了它的相似度公式和相应的评价法则,并总结了该算法目前存在的一些问题,以及研究人员针对这些问题给出的解决方案,最后提出了推荐算法的未来的改进方向。
In recent years,the variety and quantity of commodities have increased rapidly,which makes it difficult for consumers tofind products of interest.Major e-commerce platforms begin to use recommendation technology to provide better services for users,among which collaborative filtering recommendation algorithm is the most widely used.This paper mainly summarizes the core idea of collaborative filtering recommendation algorithm,summarizes its similarity formula and corresponding evaluation rules,and sum-marizes the existing problems of the algorithm,as well as the solutions given by researchers to these problems.Finally,the future improvement direction of the recommendation algorithm is proposed.
作者
秦灿
李旭东
QIN Can;LI Xu-dong(College of Computer Science and Engineering,Wuhan Institute of Technology,Wuhan 430205,China)
出处
《电脑知识与技术》
2019年第5期288-291,共4页
Computer Knowledge and Technology
关键词
电子商务
推荐技术
协同过滤
精准推荐
机器学习
E-commerce
recommendation technology
collaborative filtering
precise recommendation
Machine learning
