Finding Useful Information for Big Data

被引：1
作者：
Shi, Yong [1 ]
机构：
[1] Kennesaw State Univ, Dept Comp Sci & Informat Syst, Kennesaw, GA 30144 USA
来源：
INTERNATIONAL JOURNAL OF GRID AND DISTRIBUTED COMPUTING | 2015年 / 8卷 / 03期
关键词：
Big data; nearest neighboring search; clustering algorithms;
D O I：
10.14257/ijgdc.2015.8.3.02
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In this paper, we present our work on information analysis for big data. Big data is generated every day in various fields such as complex physics simulations, genomics, meteorology, as well as biological and environmental research. Traditional data mining applications cannot handle big data well because the data sets are so large and complex. In this paper we present our approach to analyzing the information that is hidden in the big data using various strategies. This proposed approach can assist to improve the performance of existing data analysis technologies, such as data mining approaches in Bioinformatics and other fields.
引用
收藏
页码：11 / 21
页数：11
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