SGER: Utility and Usability of Text Mining for Biological Curation

生物学现在是一门信息科学，越来越依赖于大量的生物资源，比如专家管理的数据库。这些数据库中的知识最终来源于文献，但这种转移需要专家为数据库阅读、提取和构建信息，这既耗费人力，又耗费专业知识。支持该过程的文本挖掘和信息提取工具的性能已经取得了重大进展，其中大部分已经在挑战评估和评估的背景下得到了证明。然而，所有这些都有测量结果，如准确性和召回率，而不是关注工具是否帮助了预期的最终用户。PI将与数据库管理员密切合作，评估工具的影响，并制定评估方法来指导工具开发人员。这些度量将用于即将到来的文本挖掘评估，首次使评估过程具有互动性，并使评估效用和可用性成为可能。

Biology is now an information science, increasingly dependent on the array of biological resources, such as expert-curated databases. The knowledge in these databases ultimately derives from literature, but the transfer requires experts to read, extract and structure the information for the database, which is both labor and expertise expensive. There has been significant progress in performance of text mining and information extraction tools to support the process, much of which has been demonstrated in the context of challenge evaluations and assessment. However, all of these have measured results such as precision and recall, rather than focusing of whether the tools help the intended end users. The PI will work closely with database curators to assess the impact of the tools and develop evaluation methods to guide tool developers. The measures will be used in upcoming text mining evaluations, for the first time making the evaluation process interactive and enabling the evaluation of utility and usability.