COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
Qingyun Wang
Manling Li
Xuan Wang
Nikolaus Nova Parulian
G. Han
Jiawei Ma
Jingxuan Tu
Ying Lin
H. 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
D. Liem
Ahmed Elsayed
Martha Palmer
Clare Voss
Cynthia Schneider
Boyan A. Onyshkevych

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.
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