Paper Title :Machine Learning-based Feature Data Analysis for Top Cloud Computing Service Providers

Author :Hongju Jung, Kyeong-Seok Han, Soo-Jin Seol, Su-Hee Hong

Article Citation :Hongju Jung ,Kyeong-Seok Han ,Soo-Jin Seol ,Su-Hee Hong , (2020 ) " Machine Learning-based Feature Data Analysis for Top Cloud Computing Service Providers " , International Journal of Advances in Computer Science and Cloud Computing (IJACSCC) , pp. 7-12, Volume-8,Issue-1

Abstract : This research paper describes the machine learning-based feature data analysis for top cloud computing service providers to establish the future strategies to get their competitive advantage. We use the public data (12,422 cases) that the cloud computing service providers announced for their marketing purposes since 2015 using LDA(Latent Dirichlet Allocation) tool. We also perform keyword network analysis to check the relations among keywords. In order to predict the future the computer learned the trends based on the training data using H2O GBM(Gradient Boosting Model) algorithm provided by Python. The accuracy is 85.7% in all service providers case. Keywords - Cloud Computing Service Providers, Competitive Advantage, LDA(Latent Dirichlet Allocation) Tool, Machine Learning, Big Data.

Type : Research paper

Published : Volume-8,Issue-1

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