COVID-SEE: Scientific Evidence Explorer for COVID-19 Related Research

August 18, 2020 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Karin Verspoor, Simon ล uster, Yulia Otmakhova, Shevon Mendis, Zenan Zhai, Biaoyan Fang, Jey Han Lau, Timothy Baldwin, Antonio Jimeno Yepes, David Martinez arXiv ID 2008.07880 Category cs.CL: Computation & Language Cross-listed cs.IR Citations 19 Venue arXiv.org Last Checked 4 months ago
Abstract
We present COVID-SEE, a system for medical literature discovery based on the concept of information exploration, which builds on several distinct text analysis and natural language processing methods to structure and organise information in publications, and augments search by providing a visual overview supporting exploration of a collection to identify key articles of interest. We developed this system over COVID-19 literature to help medical professionals and researchers explore the literature evidence, and improve findability of relevant information. COVID-SEE is available at http://covid-see.com.
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