Multi-source Heterogeneous Data Fusion

被引:0
|
作者
Zhang, Lili [1 ]
Xie, Yuxiang [1 ]
Luan Xidao [2 ]
Zhang, Xin [1 ]
机构
[1] Natl Univ Def Technol, Changsha, Hunan, Peoples R China
[2] Changsha Univ, Changsha, Hunan, Peoples R China
基金
美国国家科学基金会;
关键词
big data; heterogeneous data; data fusion; heterogeneous data fusion; deep learning;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As the exponential growth of data in internet era, there comes the big data era. Big data fusion creates huge values that makes it a research hotspot. However, in big data era, data shows characters of large volume, velocity, veracity and especially variety which is also called heterogeneity. Multiple different sources of data lead to data heterogeneity. Multi-source heterogeneous data brings opportunities and challenges to big data fusion. This paper introduces big data fusion and methods for heterogeneous data fusion, especially focus on the application of deep learning methods in multi-source heterogeneous data fusion. Challenges of dealing with multi-source heterogeneous data fusion is also discussed.
引用
收藏
页码:47 / 51
页数:5
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