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. SciSight1 has so far served over 15K users with over 42K page views and 13% returns.
| Original language | English |
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| Title of host publication | EMNLP 2020 - Conference on Empirical Methods in Natural Language Processing, Proceedings of Systems Demonstrations |
| Editors | Qun Liu, David Schlangen |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 135-143 |
| Number of pages | 9 |
| ISBN (Electronic) | 9781952148620 |
| State | Published - 2020 |
| Externally published | Yes |
| Event | 2020 System Demonstrations of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020 - Virtual, Online Duration: 16 Nov 2020 → 20 Nov 2020 |
Publication series
| Name | EMNLP 2020 - Conference on Empirical Methods in Natural Language Processing, Proceedings of Systems Demonstrations |
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Conference
| Conference | 2020 System Demonstrations of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020 |
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| City | Virtual, Online |
| Period | 16/11/20 → 20/11/20 |
Bibliographical note
Publisher Copyright:© 2020 Association for Computational Linguistics.