COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations (Naacl-Hlt 2021)
; : 66-77, 2021.
Article
in English
| Web of Science | ID: covidwho-2068449
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. All of the data, KGs, reports(1), resources, and shared services are publicly available(2).
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Collection:
Databases of international organizations
Database:
Web of Science
Language:
English
Journal:
2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations (Naacl-Hlt 2021)
Year:
2021
Document Type:
Article
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