Research on the Transmission Path of COVID-19 Based on Knowledge Graph Reasoning Technology
Abstract
The transmission process of the COVID-19 is complex. Traditional research on the transmission process mainly focuses on studying the overall transmission patterns or trends of infectious diseases at the macro level. It cannot analyze the transmission relationship between specific cases at the individual level or accurately locate the transmission path of the epidemic. And it is difficult to support precise prevention and control of infectious diseases. It is urgent to consider both spatiotemporal and semantic characteristics to study the transmission process of infectious diseases. This paper attempts to apply the knowledge reasoning technology in the Knowledge graph to the research on the transmission path of the COVID-19 epidemic based on the analysis of the population migrating from Wuhan during the COVID-19 epidemic, with a view to providing ideas.
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Fan F. Modeling and Analysis of novel coronavirus Epidemic Situation [D]. Central China Normal University, 2020, 4-5.
Hu DY, Gao F, Gu JG. Construction and visualization of COVID-19 prevention and control Knowledge graph [J]. Computer and Digital Engineering, 2020,48 (12): 2900.
Han S. Research on epidemic transmission model based on mobile behavior [D]. Jiangsu University, 2019, 2-4.
DOI: http://dx.doi.org/10.18686/mmf.v6i9.8857
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