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http://dx.doi.org/10.36498/kbigdt.2020.5.1.125

A Direction of Politic Support for Infectious Disease in Busan Using Time-series Clustering: Focusing on COVID-19 Cases  

Kwun, Hyeon-Ho (부산대학교 산업공학과)
Kim, Do-Hee (부산대학교 산업공학과)
Park, Chan-Ho (부산대학교 산업공학과)
Lee, Eun-Ju (부산대학교 산업공학과)
Cho, KiHaing (부산광역시)
Bae, Hye-Rim (부산대학교 산업공학과)
Publication Information
The Journal of Bigdata / v.5, no.1, 2020 , pp. 125-138 More about this Journal
Abstract
After the spread of COVID-19 in 2020, the country's Crisis Alert Level went up to the highest level, Level 4. Respond of COVID-19 pandemic, Governments, and cities secured each province's duty for the citizens. The government provided health assistance first and stepped forward to support the necessary resources for the citizens. Busan City proposed policy response to prepare and implement the Corona support for each county as well. The high occupant rate of self-business owners lost basic incomes, and the effect varies on industries. In our paper, to avoid any crisis in such an epidemic, we propose a clustering analysis for the guidance of policy support for Busan City. By analyzing patterns and clustering on districts and Sectors, we would like to provide reference materials for determining the direction of support and guiding preemptive response in the event of a similar epidemic.
Keywords
COVID-19; Policy Support; Pattern; Clustering; Preemptive;
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