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A bibliometric analysis on Data Mining and Big Data

机译:数据挖掘与大数据的文献计量分析

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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.
机译:随着电子商务数据的越来越多的积累,数据挖掘和更新的大数据问题引起了越来越多的关注。本文根据研究数据库中的出版物期刊和文章对文献分析进行报告。 2014年数据挖掘和大数据排名前10位文章计数的排名比较显示,排名前10位的作者国家共有9个共同点,而排名前10位的作者组织只有2个共同点。在前10个研究领域中共有6个共同点,但在前10个期刊名称中只有2个共同点。但是,为大数据文献做出贡献的近1/3作者来自在数据挖掘主题方面有出版物的作者。希望他们在价值维度上的大数据研究可以更好地与数据挖掘知识和方法联系起来。

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