TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection
May 09, 2020 ยท Declared Dead ยท ๐ SIGIR Forum
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Ellen Voorhees, Tasmeer Alam, Steven Bedrick, Dina Demner-Fushman, William R Hersh, Kyle Lo, Kirk Roberts, Ian Soboroff, Lucy Lu Wang
arXiv ID
2005.04474
Category
cs.IR: Information Retrieval
Citations
87
Venue
SIGIR Forum
Last Checked
3 months ago
Abstract
TREC-COVID is a community evaluation designed to build a test collection that captures the information needs of biomedical researchers using the scientific literature during a pandemic. One of the key characteristics of pandemic search is the accelerated rate of change: the topics of interest evolve as the pandemic progresses and the scientific literature in the area explodes. The COVID-19 pandemic provides an opportunity to capture this progression as it happens. TREC-COVID, in creating a test collection around COVID-19 literature, is building infrastructure to support new research and technologies in pandemic search.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Information Retrieval
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
R.I.P.
๐ป
Ghosted
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
๐
๐
Old Age
Neural Graph Collaborative Filtering
R.I.P.
๐ป
Ghosted
Self-Attentive Sequential Recommendation
R.I.P.
๐ป
Ghosted
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted