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Key Issue: Text mining, copyright and the benefits and barriers to innovation

机译：关键问题：文本挖掘，版权以及创新的收益和障碍

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Do you want to cure cancer? It doesn’t matter whether your research is about solving one of the grand challenges of humanity or addressing a more humble question – your first step is likely to be looking at what others have done before. Due to the ever-increasing?number of scholarly publications (about 1.5 million new articles published every year), building up an overview of any field of study is an extremely time-consuming process. In prominent topics such as cancer research, it is even more difficult: for the last ten years?alone, the UK PubMed Central (UKPMC) database lists 312,308 citations with the word ‘cancer’ in the title – browsing them at the leisurely pace of 85 per day will take you about ten years. And by that time, ten years’ worth of new articles on cancer will have appeared.?To make such a search even more complex, relevant articles may not feature the keyword ‘cancer’ and critical information may be hiding in a footnote within a completely unrelated publication. There is huge potential for advancing knowledge by systematically identifying,?analysing and cross-referencing existing research, but the work required is prohibitively time-consuming and expensive. Unless we use machines to help us – and that is where text mining comes into play.
机译：你想治愈癌症吗？无论您的研究是要解决人类面临的重大挑战之一，还是要解决一个更谦虚的问题，都没有关系–您的第一步很可能是看看其他人之前所做的事情。由于学术出版物的数量不断增加（每年出版约150万篇新文章），对任何研究领域进行概述都是非常耗时的过程。在诸如癌症研究之类的突出主题中，这甚至更加困难：仅在过去十年中，英国PubMed Central（UKPMC）数据库就列出312,308条在标题中带有“ cancer”字样的引用-以轻松的速度浏览它们。每天85天将花费您大约十年的时间。到那时，将出现长达十年的关于癌症的新文章。为了使这种搜索更加复杂，相关文章可能没有使用关键字“癌症”，关键信息可能完全隐藏在脚注中。无关的出版物。通过系统地识别，分析和交叉引用现有研究，有巨大的发展知识的潜力，但是所需的工作非常耗时且昂贵。除非我们使用机器来帮助我们-否则文本挖掘将发挥作用。

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