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Guest Editorial: Scholarly Big Data
IEEE Transactions on Emerging Topics in Computing ( IF 5.1 ) Pub Date : 2021-03-08 , DOI: 10.1109/tetc.2021.3059329
Feng Xia , C. Lee Giles , Huan Liu , Kuansan Wang

The papers in this special section focus on Big Data as it applies to scholarly information - or scholarly Big Data. This represents the vast quantity of research output, which can be acquired from digital libraries, such as journal articles, conference proceedings, theses, books, patents, experimental data, etc. It also encompasses various scholarly related data, such as author demography, academic social networks, and academic activities. The abundance of scholarly data enables the study of the academic society from a big data perspective. The dynamic and diverse nature of scholarly big data requires different data management techniques and advanced data analysis methods. Therefore, emerging topics such as scholarly big data acquisition, storage, management and processing are important issues for the research community.

中文翻译:

客座社论:学术大数据

在此特殊部分中的论文着重于大数据,因为它适用于学术信息或学术大数据。这代表了大量的研究成果,可以从数字图书馆中获取,例如期刊文章,会议论文集,论文,书籍,专利,实验数据等。它还包含各种与学术有关的数据,例如作者人口统计学,学术研究社交网络和学术活动。大量的学术数据可以从大数据的角度进行学术界的研究。学术大数据的动态性和多样性要求不同的数据管理技术和先进的数据分析方法。因此,诸如学术界的大数据获取,存储,管理和处理之类的新兴主题对于研究界来说是重要的问题。
更新日期:2021-03-09
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