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

04/10/2020
by   Edwin Zhang, et al.
0

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.

READ FULL TEXT

page 4

page 6

research
07/14/2020

Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset

We present Covidex, a search engine that exploits the latest neural rank...
research
11/30/2020

CovidExplorer: A Multi-faceted AI-based Search and Visualization Engine for COVID-19 Information

The entire world is engulfed in the fight against the COVID-19 pandemic,...
research
09/27/2022

LitCovid in 2022: an information resource for the COVID-19 literature

LitCovid (https://www.ncbi.nlm.nih.gov/research/coronavirus/), first lau...
research
04/22/2020

CORD-19: The COVID-19 Open Research Dataset

The COVID-19 Open Research Dataset (CORD-19) is a growing resource of sc...
research
03/25/2023

Thistle: A Vector Database in Rust

We present Thistle, a fully functional vector database. Thistle is an en...
research
10/17/2021

Prioritization of COVID-19-related literature via unsupervised keyphrase extraction and document representation learning

The COVID-19 pandemic triggered a wave of novel scientific literature th...

Please sign up or login with your details

Forgot password? Click here to reset