Research Trends, Enabling Technologies and Application Areas for Big Data

被引:3
|
作者
Lundberg, Lars [1 ]
Grahn, Hakan [1 ]
机构
[1] Blekinge Inst Technol, Dept Comp Sci, S-37179 Karlskrona, Sweden
关键词
survey; Big Data; telecommunication; image processing; smart cities; manufacturing; parallel processing; storage systems; cloud computing; deep learning; DATA ANALYTICS; SOCIAL MEDIA; PERFORMANCE; OPPORTUNITIES; ARCHITECTURE;
D O I
10.3390/a15080280
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The availability of large amounts of data in combination with Big Data analytics has transformed many application domains. In this paper, we provide insights into how the area has developed in the last decade. First, we identify seven major application areas and six groups of important enabling technologies for Big Data applications and systems. Then, using bibliometrics and an extensive literature review of more than 80 papers, we identify the most important research trends in these areas. In addition, our bibliometric analysis also includes trends in different geographical regions. Our results indicate that manufacturing and agriculture or forestry are the two application areas with the fastest growth. Furthermore, our bibliometric study shows that deep learning and edge or fog computing are the enabling technologies increasing the most. We believe that the data presented in this paper provide a good overview of the current research trends in Big Data and that this kind of information is very useful when setting strategic agendas for Big Data research.
引用
收藏
页数:15
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