Abstract
In order to solve the problem of poor clustering effect of K-means algorithm when dealing with massive high-dimensional data on Hadoop platform, and the existing improved algorithm is not conducive to parallelization. An improved K-means algorithm based on Hash is proposed on Hadoop platform. Firstly, the massive high-dimensional data is mapped to a compressed identification space, and then the clustering relationship is mined, and the initial clustering center is selected to avoid the sensitivity of the traditional K-means algorithm to randomly select the initial clustering center, and reduced the number of iterations of the K-means algorithm. Secondly, the overall parallelization of the algorithm is implemented in the framework of Map Reduce, and the degree of parallelization and execution efficiency is enhanced through the mechanisms of partition and combine. Finally, the experiments show that the algorithm not only improves the accuracy and stability of clustering, but also has a good processing speed.
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References
Jinhai, Zhang J, Wu R (2018) A spectral clustering algorithm for large data based on improved sampling weighted kernel K-means. Surv Mapp Bull (11):78–82
Liu W, Zhang J (2018) An improved K-means clustering algorithm. Mod Bus Ind 39(19):196–198
He M (2018) Research on power load data classification algorithm based on Hadoop platform. Xi’an University of Science and Technology
Zhao W, Ma H, He Q (2009) Parallel K-means clustering based on map reduce. In: CloudCom 2009. LNCS, vol 5931, pp 674–679
Miao Y, Zhang J et al (2014) New clustering algorithm based on Hadoop. Comput Sci 41(4):269–272
Zhang S, Wu Z (2014) Clustering algorithm optimization research based on Hadoop. Comput Sci 41(4):269–272
Yang M, Ma C, Wang Y, Zhang Z (2019) An improved FCMM algorithm for K-means clustering. Comput Appl Res (07):1–6
Wang B (2018) Research on clustering K-means algorithm based on Hadoop platform. Comput Lett (04):18–20 (2018)
Zhang S, Dong Y, Chen X (2018) Research on the design of HKM clustering algorithm based on cloud computing platform Hadoop. J Appl Sci 36(03):524–534
Miu Y, Zhang J (2014) A new clustering algorithm based on Hadoop platform. Comput Sci 41(4):269–272
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Hou, X. (2020). An Improved K-means Clustering Algorithm Based on Hadoop Platform. In: Xu, Z., Choo, KK., Dehghantanha, A., Parizi, R., Hammoudeh, M. (eds) Cyber Security Intelligence and Analytics. CSIA 2019. Advances in Intelligent Systems and Computing, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-030-15235-2_146
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DOI: https://doi.org/10.1007/978-3-030-15235-2_146
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