Published December 30, 2021
| Version v1
Journal article
Open
COVID-19 Data Clustering and Testing with K-Means Mapper and Reducer
Creators
- 1. Department of Information Technology, S.R.K.R. Engg College, China-Amiram, Bhimavaram (A.P),
- 2. Assistant Professor, Department of Information Technology, S.R.K.R. Engg College, China-Amiram, Bhimavaram (A.P),
Contributors
- 1. Publisher
Description
Due to the emergence of a new infectious disease (COVID-19), the worldwide data volume has been quickly increasing at a very high rate during the last two years. Due its infectious, and importance, in this paper, K-Means clustering procedure is applied on COVID data in MapReduce based distributed computing environment. The proposed system is store, process and tests the large volume of COVID-19 data. Experimental results had been proved that this process is adaptable to COVID-19 data in the formation of trusted clusters. .
Files
B96541211221.pdf
Files
(328.4 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:0ac42988dac8a952783029955b70be3a
|
328.4 kB | Preview Download |
Additional details
Related works
- Is cited by
- Journal article: 2278-3075 (ISSN)
Subjects
- ISSN
- 2278-3075
- Retrieval Number
- 100.1/ijitee.B96541211221