从WOS地址字段提取二级机构数据的半自动数据清洗方法
发布时间：2018-08-27 12:12
【摘要】：各高校都需要统计本校各个二级机构Web of Science(WOS)发文情况,论文提出一种基于正则表达式的半自动数据清洗方法,可从WOS地址字段中提取出发文机构排名、所属二级机构名称以及对应作者群,并以2015年南京师范大学WOS发文统计为例,进行实证研究,分析出各院系发文情况和作者发文情况。
[Abstract]:All colleges and universities need to count the Web of Science (WOS) status of their secondary institutions. In this paper, a semi-automatic data cleaning method based on regular expression is proposed, which can extract the ranking of the sending agencies from the WOS address field. The second level organization name and the corresponding author group, and take the 2015 Nanjing normal University WOS publication statistics as an example, carries on the empirical research, analyzes each school department to publish the situation and the author to send the article the situation.
【作者单位】： 南京师范大学图书馆科技查新站;
【基金】：2015年江苏省社会科学基金项目“历史文化古迹高保真全自动数字化平台建设研”(项目编号:15TQB005)研究成果之一
【分类号】：G353.1
，
本文编号：2207241
[Abstract]:All colleges and universities need to count the Web of Science (WOS) status of their secondary institutions. In this paper, a semi-automatic data cleaning method based on regular expression is proposed, which can extract the ranking of the sending agencies from the WOS address field. The second level organization name and the corresponding author group, and take the 2015 Nanjing normal University WOS publication statistics as an example, carries on the empirical research, analyzes each school department to publish the situation and the author to send the article the situation.
【作者单位】： 南京师范大学图书馆科技查新站;
【基金】：2015年江苏省社会科学基金项目“历史文化古迹高保真全自动数字化平台建设研”(项目编号:15TQB005)研究成果之一
【分类号】：G353.1
，
本文编号：2207241
本文链接：https://www.wllwen.com/tushudanganlunwen/2207241.html
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