從WOS地址字段提取二級機(jī)構(gòu)數(shù)據(jù)的半自動數(shù)據(jù)清洗方法
發(fā)布時間：2018-08-27 12:12
【摘要】：各高校都需要統(tǒng)計本校各個二級機(jī)構(gòu)Web of Science(WOS)發(fā)文情況,論文提出一種基于正則表達(dá)式的半自動數(shù)據(jù)清洗方法,可從WOS地址字段中提取出發(fā)文機(jī)構(gòu)排名、所屬二級機(jī)構(gòu)名稱以及對應(yīng)作者群,并以2015年南京師范大學(xué)WOS發(fā)文統(tǒng)計為例,進(jìn)行實證研究,分析出各院系發(fā)文情況和作者發(fā)文情況。
[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.
【作者單位】： 南京師范大學(xué)圖書館科技查新站;
【基金】：2015年江蘇省社會科學(xué)基金項目“歷史文化古跡高保真全自動數(shù)字化平臺建設(shè)研”(項目編號:15TQB005)研究成果之一
【分類號】：G353.1
，
本文編號：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.
【作者單位】： 南京師范大學(xué)圖書館科技查新站;
【基金】：2015年江蘇省社會科學(xué)基金項目“歷史文化古跡高保真全自動數(shù)字化平臺建設(shè)研”(項目編號:15TQB005)研究成果之一
【分類號】：G353.1
，
本文編號：2207241
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