Constructing public health evidence knowledge graph for decision-making support from COVID-19 literature of modelling study | |
Yang YR(杨芸榕)2; Zhidong Cao2; Pengfei Zhao2; Dajun Daniel Zeng2; Qingpeng Zhang1; Yin Luo2 | |
刊名 | Journal of Safety Science and Resilience |
2021-08 | |
页码 | 146-156 |
文献子类 | 期刊 |
英文摘要 | The needs of mitigating COVID-19 epidemic prompt policymakers to make public health-related decision under the guidelines of science. Tremendous unstructured COVID-19 publications make it challenging for policymakers to obtain relevant evidence. Knowledge graphs (KGs) can formalize unstructured knowledge into structured form and have been used in supporting decision-making recently. Here, we introduce a novel framework that can extract the COVID-19 public health evidence knowledge graph (CPHE-KG) from papers relating to a modelling study. We screen out a corpus of 3096 COVID-19 modelling study papers by performing a literature assessment process. We define a novel annotation schema to construct the COVID-19 modelling study-related IE dataset (CPHIE). We also propose a novel multi-tasks document-level information extraction model SS-DYGIE++ based on the dataset. Leveraging the model on the new corpus, we construct CPHE-KG containing 60,967 entities and 51,140 relations. Finally, we seek to apply our KG to support evidence querying and evidence mapping visualization. Our SS-DYGIE++(SpanBERT) model has achieved a F1 score of 0.77 and 0.55 respectively in document-level entity recognition and coreference resolution tasks. It has also shown high performance in the relation identification task. With evidence querying, our KG can present the dynamic transmissions of COVID-19 pandemic in different countries and regions. The evidence mapping of our KG can show the impacts of variable non-pharmacological interventions to COVID-19 pandemic. Analysis demonstrates the quality of our KG and shows that it has the potential to support COVID-19 policy making in public health. |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/48947] |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心 |
通讯作者 | Zhidong Cao |
作者单位 | 1.香港城市大学 2.中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yang YR,Zhidong Cao,Pengfei Zhao,et al. Constructing public health evidence knowledge graph for decision-making support from COVID-19 literature of modelling study[J]. Journal of Safety Science and Resilience,2021:146-156. |
APA | Yang YR,Zhidong Cao,Pengfei Zhao,Dajun Daniel Zeng,Qingpeng Zhang,&Yin Luo.(2021).Constructing public health evidence knowledge graph for decision-making support from COVID-19 literature of modelling study.Journal of Safety Science and Resilience,146-156. |
MLA | Yang YR,et al."Constructing public health evidence knowledge graph for decision-making support from COVID-19 literature of modelling study".Journal of Safety Science and Resilience (2021):146-156. |
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