摘要
在分析电子商务服务推荐系统基本工作原理的基础上,给出了推荐技术的分类标准。系统介绍了基于内容、协同过滤、基于关联规则、基于知识和基于人口统计信息等主要服务推荐算法。对这些算法的优缺点进行综合对比,对组合推荐算法的思路进行了简要介绍,给出了算法评价标准和实验常用数据集。最后,对推荐系统现存的主要问题进行了分析,并对未来的研究热点进行了预测和展望。
On the basis of analyzing the basic working principles of e-business recommendation system,the technical recommendation standard is given.The paper systematically introduces some common recommend technologies such as recommendation based on contents,collaborative filtering recommendation,rules,Knowledge-based and demographic-based recommendations.After that,the advantages and disadvantages of these above-mentioned technical recommendations are provided.The combined recommendation algorithm is briefly introduced.Recommendation evaluation and common data sets are also introduced.Then,existing problems on personalized recommendation are analyzed.Finally,Future research challenges facing e-business recommendation are presented.
作者
崔睿宇
杨怀洲
CUI Ruiyu;YANG Huaizhou(School of Computer Science,Xi'an Shiyou University,Xi'an 710065,China)
出处
《智能计算机与应用》
2019年第1期173-177,共5页
Intelligent Computer and Applications
基金
西安市科技计划项目(201805038YD16CG22(2))
关键词
服务推荐
电子商务
协同过滤
算法评价
service recommendation
E-business
collaborative filtering
algorithm evaluation
