摘要
云计算的出现,有效地解决大数据时代的数据冗余、处理速度慢、空间不足等难题,满足信息化社会快速发展的数据需求。首先简介云计算,大数据,几种经典的推荐算法和个性化推荐。然后把云平台与推荐系统的推荐引擎结合起来,利用协同过滤算法结合Map Reduce框架模式进行计算,分别基于共同好友和共同兴趣对一个微博大数据集进行处理并得出推荐结果,给用户推荐潜在关注者和关键字,并对实验结果进行分析得出结论,验证云计算能有效并且快速处理大数据,提高计算机大规模数据计算处理能力。
Emergence of cloud computing, effectively solves the era of big data, data redundancy, processing speed, lack of space and other problems, to meet the data needs of the information society rapid development. Firstly, introduces cloud computing,big data, several classic recommendation algorithm and personalized recommendations. Puts forward the collaborative filtering algorithm and Map Reduce frame-work based on common friend and common interest, deals with a big data set and outputting the result, recommending the potential fol-lowers and keywords to users. Puts forward the conclusion and outlook are, and analyzes the experimental results to conclude that cloud computing can effectively verify and rapid processing of large data, large-scale data to improve computer processing capabilities.
基金
广东省公益研究与能力建设专项资金项目(No.2016A020223012
No.2015A020217011)
广东省交通科技计划项目(No.2015-02-064)
广东省本科高校教学质量与教学改革工程项目(粤教高函[2015]133号)
广东外语外贸大学南国商学院2016年教改重大项目
广州大学华软软件学院重大科研培育项目20000104与教研项目KY201412
关键词
云计算
HADOOP
大数据
协同过滤
个性化推荐
Cloud Computing
Hadoop
Big Data
Collaborative Filtering（CF） Algorithm
Personalized Recommendation
