@inproceedings{hope-etal-2020-scisight,
title = "{S}ci{S}ight: Combining faceted navigation and research group detection for {COVID}-19 exploratory scientific search",
author = "Hope, Tom and
Portenoy, Jason and
Vasan, Kishore and
Borchardt, Jonathan and
Horvitz, Eric and
Weld, Daniel and
Hearst, Marti and
West, Jevin",
editor = "Liu, Qun and
Schlangen, David",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = oct,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.emnlp-demos.18",
doi = "10.18653/v1/2020.emnlp-demos.18",
pages = "135--143",
abstract = "The COVID-19 pandemic has sparked unprecedented mobilization of scientists, generating a deluge of papers that makes it hard for researchers to keep track and explore new directions. Search engines are designed for targeted queries, not for discovery of connections across a corpus. In this paper, we present SciSight, a system for exploratory search of COVID-19 research integrating two key capabilities: first, exploring associations between biomedical facets automatically extracted from papers (e.g., genes, drugs, diseases, patient outcomes); second, combining textual and network information to search and visualize groups of researchers and their ties. SciSight has so far served over 15K users with over 42K page views and 13{\%} returns.",
}
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<abstract>The COVID-19 pandemic has sparked unprecedented mobilization of scientists, generating a deluge of papers that makes it hard for researchers to keep track and explore new directions. Search engines are designed for targeted queries, not for discovery of connections across a corpus. In this paper, we present SciSight, a system for exploratory search of COVID-19 research integrating two key capabilities: first, exploring associations between biomedical facets automatically extracted from papers (e.g., genes, drugs, diseases, patient outcomes); second, combining textual and network information to search and visualize groups of researchers and their ties. SciSight has so far served over 15K users with over 42K page views and 13% returns.</abstract>
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%0 Conference Proceedings
%T SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search
%A Hope, Tom
%A Portenoy, Jason
%A Vasan, Kishore
%A Borchardt, Jonathan
%A Horvitz, Eric
%A Weld, Daniel
%A Hearst, Marti
%A West, Jevin
%Y Liu, Qun
%Y Schlangen, David
%S Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2020
%8 October
%I Association for Computational Linguistics
%C Online
%F hope-etal-2020-scisight
%X The COVID-19 pandemic has sparked unprecedented mobilization of scientists, generating a deluge of papers that makes it hard for researchers to keep track and explore new directions. Search engines are designed for targeted queries, not for discovery of connections across a corpus. In this paper, we present SciSight, a system for exploratory search of COVID-19 research integrating two key capabilities: first, exploring associations between biomedical facets automatically extracted from papers (e.g., genes, drugs, diseases, patient outcomes); second, combining textual and network information to search and visualize groups of researchers and their ties. SciSight has so far served over 15K users with over 42K page views and 13% returns.
%R 10.18653/v1/2020.emnlp-demos.18
%U https://aclanthology.org/2020.emnlp-demos.18
%U https://doi.org/10.18653/v1/2020.emnlp-demos.18
%P 135-143
Markdown (Informal)
[SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search](https://aclanthology.org/2020.emnlp-demos.18) (Hope et al., EMNLP 2020)
ACL