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Managing expectations: assessment of chemistry databases generated by automated extraction of chemical structures from patents

机译:管理期望:评估从专利中自动提取化学结构生成的化学数据库

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摘要

BackgroundFirst public disclosure of new chemical entities often takes place in patents, which makes them an important source of information. However, with an ever increasing number of patent applications, manual processing and curation on such a large scale becomes even more challenging. An alternative approach better suited for this large corpus of documents is the automated extraction of chemical structures. A number of patent chemistry databases generated by using the latter approach are now available but little is known that can help to manage expectations when using them. This study aims to address this by comparing two such freely available sources, SureChEMBL and IBM SIIP (IBM Strategic Intellectual Property Insight Platform), with manually curated commercial databases.
机译:背景技术新化学实体的首次公开披露通常发生在专利中,这使它们成为重要的信息来源。但是,随着专利申请数量的不断增加,如此大规模的手动处理和固化变得更具挑战性。更适合这种大型文档集的另一种方法是自动提取化学结构。现在可以使用通过后一种方法生成的许多专利化学数据库,但是鲜为人知,在使用它们时可以帮助管理期望值。本研究旨在通过将两个免费提供的资源SureChEMBL和IBM SIIP(IBM战略知识产权洞察平台)与手动管理的商业数据库进行比较来解决此问题。

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