首页> 外文期刊>Computing in science & engineering >Comparing the Use of Research Resource Identifiers and Natural Language Processing for Citation of Databases, Software, and Other Digital Artifacts
【24h】

Comparing the Use of Research Resource Identifiers and Natural Language Processing for Citation of Databases, Software, and Other Digital Artifacts

机译:比较使用研究资源标识符和自然语言处理的使用,以引用数据库,软件和其他数字工件的引用

获取原文
获取原文并翻译 | 示例

摘要

The Research Resource Identifier (RRID) was introduced in 2014 to better identify biomedical research resources and track their use across the literature, including key digital resources such as databases and software. Authors include an RRID after the first mention of any resource used. Here, we provide an overview of RRIDs and analyze their use for digital resource identification. We quantitatively compare the output of our RRID curation workflow with the outputs of automated text mining systems used to identify resource mentions in text. The results show that authors follow RRID reporting guidelines well, and that our natural language processing based text mining was able to identify nearly all of the resources identified by RRIDs as well as thousands more. Finally, we demonstrate how RRIDs and text mining can complement each other to provide a scalable solution to digital resource citation.
机译:2014年推出了研究资源标识符(RRID),以更好地识别生物医学研究资源并跟踪它们在文献中的使用,包括数据库和软件等关键数字资源。作者在第一次提及所使用的任何资源后,包括RRID。在这里,我们提供RRID的概述并分析其用于数字资源识别的用途。我们可以使用用于识别文本中的资源提到的自动文本挖掘系统的输出来定量比较我们的RRID策良工作流的输出。结果表明,作者遵循RRID报告指南,我们基于自然语言处理的文本挖掘能够识别几乎所有由RRID识别的资源以及数千次。最后,我们展示了RRID和文本挖掘如何相互补充,以便为数字资源引用提供可扩展的解决方案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号