COVIDSeer : Extending the CORD-19 Dataset
COVIDSeer : Extending the CORD-19 Dataset
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COVIDSeer：扩展 CORD-19 数据集
DOI：
10.1145/3395027.3419597
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Giles, C.L.
中科院分区：
文献类型：
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作者：
Rohatgi, S.;Karishma, Z.;Chhay, J.;Keesara, S.R.R.;Wu, J.;Caragea, C.;Giles, C.L.
我们开发了艾伦人工智能研究所发布的CORD-19数据集的增强版本。SeerSuite项目中的工具用于利用CORD-19数据集中未直接提供的原始文章中的信息。我们增加了728个新的摘要，70，102个图和31，446个表格，其中包括当前数据发布中未提供的标题。我们还基于我们创建的新数据集构建了一个垂直搜索引擎COVIDSeer。COVIDSeer有一个相对简单的架构，具有关键字过滤和类似的论文推荐等功能。其目标是提供一个系统和数据集，帮助科学家更好地浏览有关COVID-19的文献。丰富的数据集可以作为现有数据集的补充。该搜索引擎提供关键词增强搜索，有望帮助生物医学和生命科学研究人员、医学生和公众更有效地探索冠状病毒相关文献。整个数据集和系统将开放源代码。
We develop an enhanced version of CORD-19 dataset released by the Allen Institute for AI. Tools in the SeerSuite project are used to exploit information in original articles not directly provided in the CORD-19 datasets. We add 728 new abstracts, 70,102 figures and 31,446 tables with captions that are not provided in the current data release. We also built a vertical search engine COVIDSeer based on the new dataset we created. COVIDSeer has a relatively simple architecture with features like keyword filtering, and similar paper recommendation. The goal was to provide a system and dataset that can help scientists better navigate through the literature concerning COVID-19. The enriched dataset can serve as a supplement to the existing dataset. The search engine, which offers keyphrase-enhanced search, will hopefully help biomedical and life science researchers, medical students, and the general public to more effectively explore coronavirus-related literature. The entire data set and the system will be made open source.