BDBC-KG-NLP/COVID-19-tracker
北航大数据高精尖中心研究团队进行数据来源的整理与获取,利用自然语言处理等技术从已公开全国4626确诊患者轨迹中抽取了基本信息(性别、年龄、常住地、工作、武汉/湖北接触史等)、轨迹(时间、地点、交通工具、事件)及病患关系形成结构化信息
This project helps public health researchers and government agencies by transforming scattered, unstructured text data about COVID-19 confirmed patient movements into organized, usable information. It takes official public announcements and patient narratives as input, and outputs structured data including demographics, travel history (times, locations, transport), and patient relationships. This data can be used by epidemiologists and public health officials for studying disease spread and informing prevention strategies.
No commits in the last 6 months.
Use this if you need structured, detailed information on COVID-19 patient travel histories and demographics for research or public health analysis.
Not ideal if you require real-time tracking data or information beyond the scope of confirmed patient trajectories and basic personal data.
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86
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MIT
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Last pushed
Mar 22, 2020
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