Information Retrieval and Extraction on COVID-19 Clinical Articles Using Graph Community Detection and Bio-BERT Embeddings

Debasmita Das, Yatin Katyal, Janu Verma, Shashank Dubey, AakashDeep Singh, Kushagra Agarwal, Sourojit Bhaduri, RajeshKumar Ranjan

Abstract
In this paper, we present an information retrieval system on a corpus of scientific articles related to COVID-19. We build a similarity network on the articles where similarity is determined via shared citations and biological domain-specific sentence embeddings. Ego-splitting community detection on the article network is employed to cluster the articles and then the queries are matched with the clusters. Extractive summarization using BERT and PageRank methods is used to provide responses to the query. We also provide a Question-Answer bot on a small set of intents to demonstrate the efficacy of our model for an information extraction module.
Anthology ID:
2020.nlpcovid19-acl.7
Volume:
Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020
Month:
July
Year:
2020
Address:
Online
Editors:
Karin Verspoor, Kevin Bretonnel Cohen, Mark Dredze, Emilio Ferrara, Jonathan May, Robert Munro, Cecile Paris, Byron Wallace
Venue:
NLP-COVID19
SIG:
Publisher:
Association for Computational Linguistics
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URL:
https://aclanthology.org/2020.nlpcovid19-acl.7
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Cite (ACL):
Debasmita Das, Yatin Katyal, Janu Verma, Shashank Dubey, AakashDeep Singh, Kushagra Agarwal, Sourojit Bhaduri, and RajeshKumar Ranjan. 2020. Information Retrieval and Extraction on COVID-19 Clinical Articles Using Graph Community Detection and Bio-BERT Embeddings. In Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020, Online. Association for Computational Linguistics.
Cite (Informal):
Information Retrieval and Extraction on COVID-19 Clinical Articles Using Graph Community Detection and Bio-BERT Embeddings (Das et al., NLP-COVID19 2020)
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