Big Data Computing and Mining in a Smart World

Leung, Carson K.

doi:10.1007/978-981-15-8731-3_2

Cited by 5 publications

(1 citation statement)

References 76 publications

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“…In the current era of big data [1][2][3][4][5][6], high volume of big data can be generated and collected from a wide variety of rich data sources at a rapid rate. Due to differences in level of veracity, some of these big data are precise while some others are imprecise and uncertain.…”

Section: Introductionmentioning

confidence: 99%

Big Data Science on COVID-19 Data

Leung

Chen

Shang

et al. 2020

2020 IEEE 14th International Conference on Big Data Science and Engineering (BigDataSE)

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In the current era of big data, high volume of big data can be generated and collected from a wide variety of rich data sources at a rapid rate. Embedded in these big data are useful information and valuable knowledge. Examples include healthcare and epidemiological data such as data related to patients who suffered from viral diseases like the coronavirus disease 2019 (COVID-19). Knowledge discovered from these epidemiological data via data science helps researchers, epidemiologists and policy makers to get a better understanding of the disease, which may inspire them to come up ways to detect, control and combat the disease. In this paper, we present a data science solution for analyzing big COVID-19 epidemiological data. The solution helps users to get a better understanding of information about the confirmed cases of COVID-19. Evaluation results show the benefits of our data science solution in discovering useful knowledge from big COVID-19 data.

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