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Reproducibility in Natural Language Processing: A Case Study of Two R Libraries for Mining PubMed/MEDLINE

机译:自然语言处理中的可重现性:两个用于挖掘PubMed / MEDLINE的R库的案例研究

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摘要

There is currently a crisis in science related to highly publicized failures to reproduce large numbers of published studies. The current work proposes, by way of case studies, a methodology for moving the study of reproducibility in computational work to a full stage beyond that of earlier work. Specifically, it presents a case study in attempting to reproduce the reports of two R libraries for doing text mining of the PubMed/MEDLINE repository of scientific publications. The main findings are that a rational paradigm for reproduction of natural language processing papers can be established; the advertised functionality was difficult, but not impossible, to reproduce; and reproducibility studies can produce additional insights into the functioning of the published system. Additionally, the work on reproducibility lead to the production of novel user-centered documentation that has been accessed 260 times since its publication—an average of once a day per library.
机译:当前,由于大量出版的研究成果未能广为宣传而导致科学危机。通过案例研究,当前的工作提出了一种方法,用于将计算工作中的可重复性研究移至较早期工作更为完整的阶段。具体地说,它提供了一个案例研究,试图重现两个R库的报告,以便对科学出版物的PubMed / MEDLINE资料库进行文本挖掘。主要发现是可以建立自然语言处理论文复制的理性范式。广告功能很难复制,但并非不可能复制;重复性研究可以为已发布系统的功能提供更多见解。此外,有关可复制性的工作还导致制作了以用户为中心的新颖文档,该文档自出版以来已被访问260次,每个库平均每天访问一次。

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