中国科学院软件研究所机构知识库
Advanced  
ISCAS OpenIR  > 软件所图书馆  > 期刊论文
Title:
基于Hadoop的电子商务推荐系统的设计与实现
Alternative Title: Design and implementation of recommendation system for E-commerce on Hadoop
Author: 李文海 ; 许舒人
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
Source: 计算机工程与设计
Issued Date: 2014
Volume: 35, Issue:1, Pages:130-136,143
Indexed Type: CSCD
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
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.
English Abstract: To 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.
Language: 中文
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16774
Appears in Collections:软件所图书馆_期刊论文

Files in This Item:

There are no files associated with this item.


Recommended Citation:
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,2014-01-01,35(1):130-136,143.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[李文海]'s Articles
[许舒人]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[李文海]‘s Articles
[许舒人]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2019  中国科学院软件研究所 - Feedback
Powered by CSpace