A bibliometric analysis on data mining and big data

被引：0
作者：
Tseng S.-F. [1 ]
Won Y.-L. [1 ]
Yang J.-M. [1 ]
机构：
[1] Department of MIS, National Chengchi University, No. 64, Sec. 2, Zhinan Rd., Wenshan Dist., Taipei City
来源：
International Journal of Electronic Business | 2016年 / 13卷 / 01期
关键词：
Bibliometric analysis; Big data; Bradford's law; Bradford-Zipf's law; Data mining;
D O I：
10.1504/IJEB.2016.075333
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Along with more and faster accumulation of electronic business data, Data Mining and the newer Big Data issues are attracting more attention. This paper reports the literature analysis based on the publication journals and articles in the research databases. The ranking comparisons of top 10 article counts in 2014 on Data Mining and Big Data show that there are 9 in common in the top 10 author countries but only 2 in common in the top 10 author organisations. There are 6 in common in the top 10 research areas but only 2 in common in the top 10 journal names. However, near 1/3 authors contributing to the Big Data literature come from the pool of authors who have publications in the Data Mining subject. Hopefully, their Big Data research in the value dimension may link better to the Data Mining knowledge and methodologies. © 2016 Inderscience Enterprises Ltd.
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页码：38 / 69
页数：31
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