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Parallel PAM Clustering Algorithm for Learning Analytics
http://hdl.handle.net/20.500.12678/0000006388
http://hdl.handle.net/20.500.12678/00000063882b653119-72ac-4ca1-a0ed-a7663ce26e0e
ef4193f6-60be-42ab-aa44-9afa4dcbd5a1
Name / File | License | Actions |
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Publication type | ||||||
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Conference paper | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Parallel PAM Clustering Algorithm for Learning Analytics | |||||
Language | en | |||||
Publication date | 2017-11-02 | |||||
Authors | ||||||
Nway Yu Aung | ||||||
Swe Zin Hlaing | ||||||
Description | ||||||
Learning Analytics (LA) is defined as an area of research and application and is related to academic analytics, action analytics, and predictive analytics. This paper focuses the handling huge amount of data for better analysis. The challenges facing LA are regarding the need to increase the scope of data capture so that the complexity of the learning process can be more accurately reflected in analysis. This paper focuses on handling huge amount of data for better analysis. Partition Around Medoids (PAM) algorithm is one of the partition clustering algorithms. It tackles the problem in an iterative. However, it is not widely used for large data because of its high computational complexity. Parallelization technique can solve this problem. So, this paper proposed parallel PAM algorithm which is implemented by using Spark framework. This paper showed that the partition algorithm on Spark is slightly better than execution time tradition PAM algorithm. |
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Keywords | ||||||
Clustering, PAM, Spark | ||||||
Conference papers | ||||||
ICAIT-2017 | ||||||
1-2 November, 2017 | ||||||
1st International Conference on Advanced Information Technologies | ||||||
Yangon, Myanmar | ||||||
Workshop Session | ||||||
https://www.uit.edu.mm/icait-2017/ |