ISCAS OpenIR
基于Hadoop的电子商务推荐系统的设计与实现
Alternative TitleDesign and implementation of recommendation system for E-commerce on Hadoop
李文海; 许舒人
2014
Source计算机工程与设计
ISSN1000-7024
Volume35Issue:1Pages:130-136,143
English Abstract为了解决大数据应用背景下大型电子商务系统所面临的信息过载问题,研究了基于Hadoop构建分布式电子商务推荐系统的方案.采用基于MapReduce模型实现的算法具有较高的伸缩性和性能,能高效地进行离线数据分析.为了克服单一推荐技术的不足,设计了融合多种互补性推荐技术的混合推荐模型.实验结果表明,基于Hadoop平台实现的推荐系统具有较好的伸缩性和性能.
Indexed TypeCSCD
AbstractTo solve the information overload problem of large scale E-commerce systems in the big data era, a solution based on Hadoop is proposed, aiming at building a distributed recommendation system. Data analysis algorithms based on MapReduce programming model have high scalability and good performance. To overcome the limit of single recommendation technology, a hybrid model is adopted, which combines several complementary methods. Empirical studies show that the recommendation system on Hadoop has good scalability and efficiency.
Keyword分布式推荐系统 混合推荐 Hadoop 关联规则挖掘 协同过滤 Distributed Recommendation System Hybrid Hadoop Association Mining Collaborative Filtering
Department中国科学院软件研究所软件工程技术研究开发中心,北京100190;中国科学院研究生院,北京100190 中国科学院软件研究所软件工程技术研究开发中心,北京,100190
Language中文
CSCD IDCSCD:5046904
Content Type期刊论文
URIhttp://ir.iscas.ac.cn/handle/311060/16774
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
李文海,许舒人. 基于Hadoop的电子商务推荐系统的设计与实现[J]. 计算机工程与设计,2014,35(1):130-136,143.
APA 李文海,&许舒人.(2014).基于Hadoop的电子商务推荐系统的设计与实现.计算机工程与设计,35(1),130-136,143.
MLA 李文海,et al."基于Hadoop的电子商务推荐系统的设计与实现".计算机工程与设计 35.1(2014):130-136,143.
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