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Frontiers of Supercomputing
Vol. 3, No. 1, Apr. 2020


High Performance Clustering to Improve Data Mining Techniques

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a University of Baghdad, Baghdad, Iraq

 

Highlights and Novelties
1- An increasing amount of data is approaching into existence each day and power to process this data calls for cluster computers which are a set of a computer that operates together, only to be viewed as a single computer, to process and compute data.

2- People are pretty dependent on computers and their computational power more and more every day. As a consequence, those outcomes need to be accurate and be calculated fast.

3- Parallel computing is a more rapid way to process instructions by breaking the large task into smaller tasks using an organized effort to process data simultaneously.

4- Data clustering has been confirmed to be a favorable data mining technique. Recently, there have been various attempts for clustering data mining algorithms.

 

Manuscript Abstract
An increasing amount of data is approaching into existence each day and power to process this data calls for cluster computers which are a set of a computer that operates together, only to be viewed as a single computer, to process and compute data. People are pretty dependent on computers and their computational power more and more every day. As a consequence, those outcomes need to be accurate and be calculated fast. Parallel computing is a more rapid way to process instructions by breaking the large task into smaller tasks using an organized effort to process data simultaneously. Data clustering has been confirmed to be a favorable data mining technique. Recently, there have been various attempts for clustering data mining algorithms. For that reason, Cluster computing is used to create redundancy in a computer network to ensure that it will regularly be to be had and that it is going to not fail.

 

Keywords
 Data clustering   Data mining   Parallel programming   High performance 

 

Copyright and Licence
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors. This manuscript is published in Open-Access manner based on the copyright licence of Creative Commons Attribution Non Commercial 4.0 International (CC BY-NC 4.0).

 

Cite this manuscript as
Heba Fadhil, "High Performance Clustering to Improve Data Mining Techniques," Frontiers of Supercomputing, vol. 3, no. 1, pp. 1-2, Apr. 2020.

 

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Manuscript ID: 331
Pages: 1-2
Submitted: 2020-03-22
Accepted: 2020-04-22
Published: 2020-04-30


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Journal's Title
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Journal

Frontiers of Supercomputing
ISSN: 2467-298X

ISSN: 2467-298X
Frequency: Biannually
Accessability: Online - Open Access
Founded in: Apr. 2018
Publisher: ICSES
DOI Suffix: 10.31424/icses.fos