5Ws Model for BigData Analysis and Visualization

被引:23
|
作者
Zhang, Jinson [1 ]
Huang, Mao Lin [1 ,2 ]
机构
[1] Univ Technol Sydney, Sch Software, Fac Engn & IT, Sydney, NSW 2007, Australia
[2] Tianjin Univ, Sch Comp Software, Tianjin 300072, Peoples R China
关键词
Big Data analysis; Big Data pattern; data dimensions; data density; Big Data visualization; VISUAL ANALYTICS;
D O I
10.1109/CSE.2013.149
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Big Data, which contains image, video, text, audio and other forms of data, collected from multiple datasets, is difficult to process using traditional database management tools or applications. In this paper, we establish the 5Ws model by using 5Ws data dimension for Big Data analysis and visualization. 5Ws data dimension stands for; What the data content is, Why the data occurred, Where the data came from, When the data occurred, Who received the data and How the data was transferred. This framework not only classifies Big Data attributes and patterns, but also establishes density patterns that provide more analytical features. We use visual clustering to display data sending and receiving densities which demonstrate Big Data patterns. The model is tested by using the network security ISCX2012 dataset. The experiment shows that this new model with clustered visualization can be efficiently used for Big Data analysis and visualization.
引用
收藏
页码:1021 / 1028
页数:8
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