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arXiv 1409.4898cs.DL
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从Web-of-Science数据生成大型网络

The Generation of Large Networks from Web-of-Science Data

Loet Leydesdorff, Gohar Feroz Khan, Lutz Bornmann

摘要:

20世纪90年代,我们中的一个人开发了一系列免费软件程序(http://www.leydesdorff.net/indicators),使用户能够将从Web-of-Science(Thomson Reuters)下载的数据组织成一个关系数据库,然后以各种格式导出矩阵供进一步分析(例如,用于合著者分析)。矩阵的基本格式将每个文档显示为一行中的一个案例,这些案例可以归因于列中的不同变量。这种方法的一个限制是迄今为止关系数据库通常具有变量数量的上限,例如256或1024。在这个简短的交流中,我们报告了一种通过使用txt2Pajek.exe(可从http://www.pfeffer.at/txt2pajek/获得免费软件)来规避此限制的方法。

英文摘要:

During the 1990s, one of us developed a series of freeware routines (http://www.leydesdorff.net/indicators) that enable the user to organize downloads from the Web-of-Science (Thomson Reuters) into a relational database, and then to export matrices for further analysis in various formats (for example, for co-author analysis). The basic format of the matrices displays each document as a case in a row that can be attributed different variables in the columns. One limitation to this approach was hitherto that relational databases typically have an upper limit for the number of variables, such as 256 or 1024. In this brief communication, we report on a way to circumvent this limitation by using txt2Pajek.exe, available as freeware from http://www.pfeffer.at/txt2pajek/.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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