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

• URL: http://arxiv.org/abs/2007.00576v6
• Date: Wed, 12 May 2021 03:30:44 GMT
• Title: COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
• Authors: 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
• Abstract summary: We have developed a novel and comprehensive knowledge discovery framework, COVID-KG, to extract fine-grained multimedia knowledge elements from scientific literature. Our framework also provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence.
• Score: 79.33545724934714
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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