Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned
arXiv:2004.05125
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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Cited by in corpus (9)
- CORD-19: The COVID-19 Open Research Dataset
- Rapidly Bootstrapping a Question Answering Dataset for COVID-19
- A Deep Dive on the Impact of COVID-19 in Software Development
- CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization
- COVID-SEE: Scientific Evidence Explorer for COVID-19 Related Research
- Answering Questions on COVID-19 in Real-Time
- Meta-research on COVID-19: An overview of the early trends
- Extracting a Knowledge Base of COVID-19 Events from Social Media
- MS MARCO: Benchmarking Ranking Models in the Large-Data Regime