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首页> 外文期刊>International Journal of Internet Technology and Secured Transactions >Research on naive Bayesian and hidden Markov model on Hadoop in cluster computing applications
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Research on naive Bayesian and hidden Markov model on Hadoop in cluster computing applications

机译:集群计算应用中基于Hadoop的朴素贝叶斯和隐马尔可夫模型研究

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摘要

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 naive Bayesian model along with Markov in cluster computing and provides better yield in data retrieval and analysis process.
机译:在集群计算研究不断发展的前沿,数据处理变得易于管理和访问。可用的创新方法是映射和并行处理,这在大数据处理中是失败的。复杂度随着数据处理能力的提高而增加,并且保持数据的产生在数据处理中至关重要,它与环境的基础结构有关。为了与控制管理一起开发技术,需要对其进行监视。 Hadoop是集群计算环境中提出的数据处理方法,该方法可提供高效,高精度且无错误的数据处理。集群计算具有使用随机场模型处理数据的传统,这种方法的计算时间到现在为止要大得多。该模型在聚类计算中利用朴素的贝叶斯模型和马尔可夫模型,在数据检索和分析过程中提供了更好的收益。

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