Publication | Open Access
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
36
Citations
53
References
2020
Year
EngineeringKnowledge ExtractionText MiningNatural Language ProcessingKnowledge Graph EmbeddingsInformation RetrievalData ScienceData IntegrationBiomedical Text MiningBiomedical OntologyRelevant Biomedical KnowledgeMedicineKnowledge RetrievalKnowledge DiscoveryEpidemiologyDrug RepurposingScientific LiteratureDrug RepositioningDisease MechanismSystems BiologySemantic GraphHealth Informatics
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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