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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 11
3244-3251,3257

Parallel K-means algorithm based on MapReduce and MSSA

Liu Weiming1
Cui Yu1
Mao Yimin1
Liu Wei2
1. School of Information Engineering, Jiangxi University of Science & Technology, Ganzhou Jiangxi 341000, China
2. School of Information Engineering, Gannan University of Science & Technology, Ganzhou Jiangxi 341000, China
DOI: 10.19734/j.issn.1001-3695.2022.04.0149

Abstract

In the big data environment, the parallel K-means clustering algorithm suffers from poor clustering effect, unbalanced data partition, cluster centroid sensitivity. To solve these problems, this paper proposed a parallel K-means algorithm based on MapReduce and MSSA(MR-MSKCA). Firstly, MR-MSKCA designed a dimensionality reduction strategy(DRKCAE), which used Kendall correlation coefficient and deep sparse autoencoder to weight features and extract features to improve the clustering effect of high-dimensional data. Secondly, it proposed a UPS, which divided the dataset and obtained uniform data partition. Finally, this paper proposed MSSA to get the parallel K-means clustering centroid, which solved the problem of initial centroid sensitivity. Compared with MR-KNMF, MR-PGDLSH and MR-GAPKCA, the running time of MR-MSKCA decreased by 45.1%, 49.1%, 59.8%, and the clustering effect increased by 19.2%, 22.8%, 24%. Experiments show that the MR-MSKCA not only has excellent performance, but also has strong adaptability with large-scale dataset.

Foundation Support

2020年度科技创新2030—“新一代人工智能”重大项目(2020AAA0109605)
国家自然科学基金资助项目(41562019)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.04.0149
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 11
Section: Algorithm Research & Explore
Pages: 3244-3251,3257
Serial Number: 1001-3695(2022)11-006-3244-08

Publish History

[2022-06-21] Accepted Paper
[2022-11-05] Printed Article

Cite This Article

刘卫明, 崔瑜, 毛伊敏, 等. 基于MapReduce和MSSA的并行K-means算法 [J]. 计算机应用研究, 2022, 39 (11): 3244-3251,3257. (Liu Weiming, Cui Yu, Mao Yimin, et al. Parallel K-means algorithm based on MapReduce and MSSA [J]. Application Research of Computers, 2022, 39 (11): 3244-3251,3257. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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