An analysis on effective classification method for massive data in cloud computing environment

被引:0
|
作者
Wang Qian [1 ]
机构
[1] Tianjin Vocat Inst, Network Ctr, Tianjin 300402, Peoples R China
来源
APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY | 2014年 / 513-517卷
关键词
cloud computing; feature selection; associative Classification;
D O I
10.4028/www.scientific.net/AMM.513-517.2315
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The network information in cloud computing environment is in the format of massive data with high dimension features. In order to increase the accuracy of massive data automatic classification, this paper proposes a relevant massive data classification algorithm. This algorithm first transfers the features of the massive data in the cloud computing environment into one multi-objective optimization problem. In the specific mining area, the algorithm associatively classifies the massive data information and the selective standard is the high accuracy. The simulation and experiment test the performance of the algorithm which shows the algorithm can effectively classify the features of the massive data in the cloud computing. The algorithm can increase the accuracy and efficiency of the automatic classification which is an effective method for massive data.
引用
收藏
页码:2315 / 2319
页数:5
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