English

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

Computation and Language 2020-08-19 v1 Information Retrieval

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.

Keywords

Cite

@article{arxiv.2008.07880,
  title  = {COVID-SEE: Scientific Evidence Explorer for COVID-19 Related Research},
  author = {Karin Verspoor and Simon Šuster and Yulia Otmakhova and Shevon Mendis and Zenan Zhai and Biaoyan Fang and Jey Han Lau and Timothy Baldwin and Antonio Jimeno Yepes and David Martinez},
  journal= {arXiv preprint arXiv:2008.07880},
  year   = {2020}
}

Comments

COVID-SEE is available at http://covid-see.com