首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于Mahout分布式协同过滤推荐算法分析与实现
引用本文:曾志浩,张琼林,姚贝,孙琪.基于Mahout分布式协同过滤推荐算法分析与实现[J].湖南农业大学学报(自然科学版),2015(3):67-72.
作者姓名:曾志浩  张琼林  姚贝  孙琪
作者单位:(湖南工业大学 计算机与通信学院,湖南 株洲412007)
摘    要:随着信息技术和互联网的发展,在信息过载的时代,用户面对海量的信息,难以正确选择。协同过滤推荐是个性化推荐中比较成熟的算法,但其稀疏性、冷启动、可扩展性问题仍然存在,尤其是不能应用于分布式推荐。在Hadoop平台上,Mahout实现了分布式基于项目的协同过滤推荐算法,该算法能够有效解决传统算法的海量数据处理的效率问题和可扩展性问题。实验结果表明,Mahout上基于项目的协同过滤推荐算法具有较好的计算高效性和可扩展性。

关 键 词:分布式协同过滤  Mahout  推荐系统

Analysis and Implementation of Distributed Collaborative Filtering Recommendation Algorithm Based on Mahout
ZENG Zhi-hao,ZHANG Qiong-lin,YAO Bei,SUN Qi.Analysis and Implementation of Distributed Collaborative Filtering Recommendation Algorithm Based on Mahout[J].Journal of Hunan Agricultural University,2015(3):67-72.
Authors:ZENG Zhi-hao  ZHANG Qiong-lin  YAO Bei  SUN Qi
Abstract:With the development of information technology and Internet, facing the vast amount of information, it is difficult to correctly choose for users in the era of information overload. Collaborative filtering is a relatively mature algorithm in personalized recommendation, but its sparsity, cold start, scalability problems still exist, especially can not be applied to distributed recommendation. On the platform of Hadoop, Mahout realized the distributed item-based collaborative filtering recommendation algorithm, and the algorithm can effectively solve massive data processing efficiency and scalability problem of the traditional algorithm. The experimental results show that, collaborative filtering algorithm has the high calculation efficiency and good scalability based on Mahout.
Keywords:distributed collaborative filtering  mahout  recommendation system
点击此处可从《湖南农业大学学报(自然科学版)》浏览原始摘要信息
点击此处可从《湖南农业大学学报(自然科学版)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号