节点文献
基于Hadoop云平台的社交大数据协同过滤个性化推荐的研究与实现
Research and Implementation of Hadoop-Based Social Big Data Collaborative Filtering Personalized Recommendation
【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。
【Abstract】 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.
【Key words】 Cloud Computing; Hadoop; Big Data; Collaborative Filtering(CF) Algorithm; Personalized Recommendation;
- 【文献出处】 现代计算机(专业版) ,Modern Computer , 编辑部邮箱 ,2016年32期
- 【分类号】TP391.3
- 【被引频次】5
- 【下载频次】226