Jasmine Rah
2021
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
Qingyun Wang
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Manling Li
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Xuan Wang
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Nikolaus Parulian
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Guangxing Han
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Jiawei Ma
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Jingxuan Tu
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Ying Lin
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Ranran Haoran Zhang
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Weili Liu
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Aabhas Chauhan
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Yingjun Guan
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Bangzheng Li
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Ruisong Li
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Xiangchen Song
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Yi Fung
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Heng Ji
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Jiawei Han
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Shih-Fu Chang
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James Pustejovsky
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Jasmine Rah
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David Liem
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Ahmed ELsayed
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Martha Palmer
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Clare Voss
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Cynthia Schneider
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Boyan Onyshkevych
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations
To combat COVID-19, both clinicians and scientists need to digest the vast amount of relevant biomedical knowledge in literature to understand the disease mechanism and the related biological functions. We have developed a novel and comprehensive knowledge discovery framework, COVID-KG to extract fine-grained multimedia knowledge elements (entities, 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. All of the data, KGs, reports.
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Co-authors
- Qingyun Wang 1
- Manling Li 1
- Xuan Wang 1
- Nikolaus Parulian 1
- Guangxing Han 1
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