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International Conference on Soft Computing and Data Mining

SCDM 2020: Recent Advances on Soft Computing and Data Mining pp 98–108Cite as

Genetic Algorithm Based Parallel K-Means Data Clustering Algorithm Using MapReduce Programming Paradigm on Hadoop Environment (GAPKCA)

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 978))

Abstract

Data clustering algorithm has been receiving considerable attention in many application areas such as data mining, document retrieval, image processing and pattern classification. A hybrid data clustering algorithm using the combination of genetic algorithm (GA) with a popular variant of K-Means clustering algorithm, parallel k-Means clustering algorithm (PKCA) is proposed in this paper. The objective of the proposed algorithm is to combine the search process of GA to generate new data clusters and apply parallel K-Means to further speed up the quality of the search process during clusters formation. The proposed approach is implemented using the popular MapReduce programming model on Hadoop framework. Experiments were conducted with multiple synthetic datasets to evaluate the performance of the proposed algorithm. Results show that the proposed algorithm was able to speed up document clustering process by 0.54 s on average and outperformed PKCA. Data analysts in marketing and finance, telecommunication and transport companies and researchers in academia can use this algorithm to make sense out of their huge volume of data.

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Author information

Authors and Affiliations

  1. Universiti Putra Malaysia, 43400 UPM, Selangor, Malaysia

    Sayer Alshammari & Maslina Binti Zolkepli

Authors
  1. Sayer Alshammari
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  2. Maslina Binti Zolkepli
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  3. Rusli Bin Abdullah
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Corresponding author

Correspondence to Maslina Binti Zolkepli .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Rozaida Ghazali

  2. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Nazri Mohd Nawi

  3. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor, Malaysia

    Mustafa Mat Deris

  4. School of Information Technology, Deakin University, Geelong Waurn Ponds Campus, VIC, Australia

    Jemal H. Abawajy

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Alshammari, S., Zolkepli, M.B., Abdullah, R.B. (2020). Genetic Algorithm Based Parallel K-Means Data Clustering Algorithm Using MapReduce Programming Paradigm on Hadoop Environment (GAPKCA). In: Ghazali, R., Nawi, N., Deris, M., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2020. Advances in Intelligent Systems and Computing, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-030-36056-6_10

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