Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned

• URL: http://arxiv.org/abs/2004.05125v1
• Date: Fri, 10 Apr 2020 17:12:29 GMT
• Title: Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned
• Authors: Edwin Zhang, Nikhil Gupta, Rodrigo Nogueira, Kyunghyun Cho, and Jimmy Lin
• Abstract summary: We present the Neural Covidex, a search engine that exploits the latest neural ranking architectures. This paper describes our initial efforts and offers a few thoughts about lessons we have learned along the way.
• Score: 88.42878484408469
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present the Neural Covidex, a search engine that exploits the latest neural ranking architectures to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institute for AI. This web application exists as part of a suite of tools that we have developed over the past few weeks to help domain experts tackle the ongoing global pandemic. We hope that improved information access capabilities to the scientific literature can inform evidence-based decision making and insight generation. This paper describes our initial efforts and offers a few thoughts about lessons we have learned along the way.

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