COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation

Qingyun Wang; Manling Li; Xuan Wang; Nikolaus Parulian; Guangxing Han; Jiawei Ma; Jingxuan Tu; Ying Lin; Haoran Zhang; Weili Liu; Aabhas Chauhan; Yingjun Guan; Bangzheng Li; Ruisong Li; Xiangchen Song; Yi R. Fung; Heng Ji; Jiawei Han; Shih Fu Chang; James Pustejovsky; Jasmine Rah; David Liem; Ahmed Elsayed; Martha Palmer; Clare Voss; Cynthia Schneider; Boyan Onyshkevych

COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation

Qingyun Wang, Manling Li, Xuan Wang, Nikolaus Parulian, Guangxing Han, Jiawei Ma, Jingxuan Tu, Ying Lin, Haoran Zhang, Weili Liu, Aabhas Chauhan, Yingjun Guan, Bangzheng Li, Ruisong Li, Xiangchen Song, Yi R. Fung, Heng Ji, Jiawei Han, Shih Fu Chang, James PustejovskyJasmine Rah, David Liem, Ahmed Elsayed, Martha Palmer, Clare Voss, Cynthia Schneider, Boyan Onyshkevych

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions. We have developed a novel and comprehensive knowledge discovery framework, COVID-KG to extract fine-grained multimedia knowledge elements (entities and their visual chemical structures, relations and events) from scientific literature. We then exploit the constructed multimedia knowledge graphs (KGs) for question answering and report generation, using drug repurposing as a case study. Our framework also provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence.

Original language	English (US)
Title of host publication	NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics
Subtitle of host publication	Human Language Technologies, Demonstrations
Publisher	Association for Computational Linguistics (ACL)
Pages	66-77
Number of pages	12
ISBN (Electronic)	9781954085480
State	Published - 2021
Event	2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021 - Virtual, Online Duration: Jun 6 2021 → Jun 11 2021

Publication series

Name	NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations

Conference

Conference	2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021
City	Virtual, Online
Period	6/6/21 → 6/11/21

ASJC Scopus subject areas

Information Systems
Software
Computer Networks and Communications
Hardware and Architecture

Library availability

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Wang, Q., Li, M., Wang, X., Parulian, N., Han, G., Ma, J., Tu, J., Lin, Y., Zhang, H., Liu, W., Chauhan, A., Guan, Y., Li, B., Li, R., Song, X., Fung, Y. R., Ji, H., Han, J., Chang, S. F., ... Onyshkevych, B. (2021). COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation. In NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations (pp. 66-77). (NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations). Association for Computational Linguistics (ACL).

COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation. / Wang, Qingyun; Li, Manling; Wang, Xuan et al.
NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations. Association for Computational Linguistics (ACL), 2021. p. 66-77 (NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wang, Q, Li, M, Wang, X, Parulian, N, Han, G, Ma, J, Tu, J, Lin, Y, Zhang, H, Liu, W, Chauhan, A, Guan, Y, Li, B, Li, R, Song, X, Fung, YR, Ji, H , Han, J, Chang, SF, Pustejovsky, J, Rah, J, Liem, D, Elsayed, A, Palmer, M, Voss, C, Schneider, C & Onyshkevych, B 2021, COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation. in NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations. NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations, Association for Computational Linguistics (ACL), pp. 66-77, 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021, Virtual, Online, 6/6/21.

Wang Q, Li M, Wang X, Parulian N, Han G, Ma J et al. COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation. In NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations. Association for Computational Linguistics (ACL). 2021. p. 66-77. (NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations).

Wang, Qingyun ; Li, Manling ; Wang, Xuan et al. / COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation. NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations. Association for Computational Linguistics (ACL), 2021. pp. 66-77 (NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Demonstrations).

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abstract = "To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions. We have developed a novel and comprehensive knowledge discovery framework, COVID-KG to extract fine-grained multimedia knowledge elements (entities and their visual chemical structures, relations and events) from scientific literature. We then exploit the constructed multimedia knowledge graphs (KGs) for question answering and report generation, using drug repurposing as a case study. Our framework also provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence.",

author = "Qingyun Wang and Manling Li and Xuan Wang and Nikolaus Parulian and Guangxing Han and Jiawei Ma and Jingxuan Tu and Ying Lin and Haoran Zhang and Weili Liu and Aabhas Chauhan and Yingjun Guan and Bangzheng Li and Ruisong Li and Xiangchen Song and Fung, {Yi R.} and Heng Ji and Jiawei Han and Chang, {Shih Fu} and James Pustejovsky and Jasmine Rah and David Liem and Ahmed Elsayed and Martha Palmer and Clare Voss and Cynthia Schneider and Boyan Onyshkevych",

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T1 - COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation

AU - Wang, Qingyun

AU - Li, Manling

AU - Wang, Xuan

AU - Parulian, Nikolaus

AU - Han, Guangxing

AU - Ma, Jiawei

AU - Tu, Jingxuan

AU - Lin, Ying

AU - Zhang, Haoran

AU - Liu, Weili

AU - Chauhan, Aabhas

AU - Guan, Yingjun

AU - Li, Bangzheng

AU - Li, Ruisong

AU - Song, Xiangchen

AU - Fung, Yi R.

AU - Ji, Heng

AU - Han, Jiawei

AU - Chang, Shih Fu

AU - Pustejovsky, James

AU - Rah, Jasmine

AU - Liem, David

AU - Elsayed, Ahmed

AU - Palmer, Martha

AU - Voss, Clare

AU - Schneider, Cynthia

AU - Onyshkevych, Boyan

PY - 2021

Y1 - 2021

N2 - To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions. We have developed a novel and comprehensive knowledge discovery framework, COVID-KG to extract fine-grained multimedia knowledge elements (entities and their visual chemical structures, relations and events) from scientific literature. We then exploit the constructed multimedia knowledge graphs (KGs) for question answering and report generation, using drug repurposing as a case study. Our framework also provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence.

AB - To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions. We have developed a novel and comprehensive knowledge discovery framework, COVID-KG to extract fine-grained multimedia knowledge elements (entities and their visual chemical structures, relations and events) from scientific literature. We then exploit the constructed multimedia knowledge graphs (KGs) for question answering and report generation, using drug repurposing as a case study. Our framework also provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence.

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M3 - Conference contribution

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EP - 77

BT - NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics

PB - Association for Computational Linguistics (ACL)

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Y2 - 6 June 2021 through 11 June 2021

ER -

COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation

Abstract

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ASJC Scopus subject areas

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