摘要
对云计算技术和数据挖掘进行研究,分析Apriori算法,针对其局限性,提出优化方案,引入云计算中MapReduce模型,实现并行化。提出一种基于MapReduce的频繁项集挖掘方法,以提高算法的运行效率,降低算法执行所需的开销。
In this paper, it studies the cloud com puting technology and data m ining. It analyzes A priori algorithm ,in view of its lim itation.It puts forw ard optim ization schem e,and introduces the M pR educe m odel of cloud com puting to realize Parallelization.In order to im prove the efficiency of algorithm and to reduce the required execution overhead of algorithm ,it proposes a MapR educe method based on frequent item sets m ining.
出处
《莆田学院学报》
2014年第5期61-64,共4页
Journal of putian University
基金
福建省教育厅科技项目(JB12372)
关键词
云计算
数据挖掘
APRIORI算法
频繁项集
M apR educe
cloud com puting
data m ining
A priori algorithm
MapReduce
frequent item sets