摘要
随着信息科学技术和移动互联网技术的快速发展,各种信息数据持续呈指数级爆发式快速增长。当今数据分析主要的目标是充分发掘出隐藏在海量数据背后信息,以此来推动各行业稳定持续发展。显然,云计算技术的出现为海量数据挖掘工作提供了便利,在传统单机模式的数据挖掘基础上,Hadoop云计算平台能够将信息数据分片处理,并将数据片分配到各个节点并行处理,大大提高了数据处理的效率。文章详细研究了基于Hadoop云计算平台的模糊聚类算法,充分利用Hadoop云计算平台并行化来解决对大规模海量数据挖掘的问题,并能够为社会经济发展作出贡献。
With the rapid development of information science and technology and mobile internet technology, all kinds of information data continue to grow rapidly in an exponential type. The main goal of today’s data analysis is to fully discover the information hidden behind mass data, in order to promote the stable and sustainable development of all industries. Obviously, the emergence of cloud computing technology provides convenience for massive data mining, mining in the traditional stand-alone mode on the basis of the data, Hadoop cloud computing platform can be processing information data,and the data is allocated to each node parallel processing, greatly improving the efficiency of data processing. This paper studies the FCM clustering algorithm based on Hadoop cloud computing platform. It makes full use of Hadoop cloud computing platform parallelization to solve the problem of massive massive data mining, and can contribute to social and economic development.
出处
《信息通信》
2018年第2期84-86,共3页
Information & Communications
基金
宜昌市大学应用基础研究项目A17-302-a13
三峡大学教学研究项目J2017015
关键词
聚类分析
数据挖掘
云计算
Clustering Analysis
Data Mining
Cloud Computing
