Research on naïve Bayesian and hidden Markov model on Hadoop in cluster computing applications Online publication date: Fri, 04-May-2018
by K. Muralisankar; A.M.J. Md. Zubair Rahman
International Journal of Internet Technology and Secured Transactions (IJITST), Vol. 7, No. 4, 2017
Abstract: In the frontier of increasing research in cluster computing the data processing becomes simple to manage and access. The available innovative methods are mapping and parallel processing which fails in large data processing. The complexity increases as the data processing capability increases and also maintaining the production of data is a vital role in data processing and it is related to the infrastructure of environment. This needs to be monitored in order to develop the technologies along with control management. The Hadoop is the proposed data processing method in cluster computing environment which gives efficient data processing with high accuracy with no error. Cluster computing has a tradition of processing data using random field model out of this approaches the computation time is much greater as of now. This proposed model utilises the naïve Bayesian model along with Markov in cluster computing and provides better yield in data retrieval and analysis process.
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