Author: Wang, Qingyun; Li, Manling; Wang, Xuan; Parulian, Nikolaus; Han, Guangxing; Ma, Jiawei; Tu, Jingxuan; Lin, Ying; Zhang, Haoran; Liu, Weili; Chauhan, Aabhas; Guan, Yingjun; Li, Bangzheng; Li, Ruisong; Song, Xiangchen; Fung, Yi R.; Ji, Heng; Han, Jiawei; Chang, Shih-Fu; Pustejovsky, James; Rah, Jasmine; Liem, David; Elsayed, Ahmed; Palmer, Martha; Voss, Clare; Schneider, Cynthia; Onyshkevych, Boyan
Title: COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation Cord-id: tkpbfroi Document date: 2020_7_1
ID: tkpbfroi
Snippet: 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 gra
Document: 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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