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
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
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.