标题:Study of a new parallel K_NN network public opinion classification algorithm based on hadoop environment
作者:Xu, Jian ;Ma, Bin ;Xu, Jian
通讯作者:Xu, Jian
作者机构:[Xu, Jian ] School of Computer and Technology, Shandong University of Finance and Economics, Jinan, China;[Ma, Bin ;Xu, Jian ] Key Laboratory of Evide 更多
会议名称:4th International Conference on Advanced Design and Manufacturing Engineering, ADME 2014
会议日期:26 July 2014 through 27 July 2014
来源:Applied Mechanics and Materials
出版年:2014
卷:635-637
页码:1624-1627
DOI:10.4028/www.scientific.net/AMM.635-637.1624
关键词:Classification; Hadoop; K_nearest neighbor(K_NN); Network public opinion
摘要:A new kind of network public opinion classification method based on K_ nearest neighbor (K_NN) classification algorithm in Hadoop environment is studied in this paper. In the light of distributed storage and parallel processing Characteristics of Hadoop platform, the parallel K_NN classification algorithm in the frame of MapReduce is designed. The classification ability and execution efficiency of proposed scheme is verified and the results show that the parallel K_NN algorithm enhances the network public opinion classification precision and execution efficiently. © (2014) Trans Tech Publications, Switzerland.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84913614842&doi=10.4028%2fwww.scientific.net%2fAMM.635-637.1624&partnerID=40&md5=b0be15789821670c38db54325b1d5b78
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