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The mass data mining research based on the information platform of Internet of Things

机译:基于物联网信息平台的海量数据挖掘研究

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This paper analyzes the key technologies of the distributed data, and proposes the solution of the mass data processing based on the Information platform of Internet of Things. The solution uses Hadoop as the open source framework to realize the distributed computing system, and uses Mahout as the data mining algorithm library to realize the parallelization of k-means clustering algorithm. This will achieve the high efficiency and the large expansibility through the mass data processing. The mass data source used in this project is from the intelligent agricultural Information service platform. The system takes the deployment test on the mass sensing information, and it optimizes and parallelizes the K-means algorithm to realize the mass data processing based on the Information platform of Internet of Things. It can make the statistical analysis, and provide fine management and other services. the algorithm is used to improve the efficiency and the accuracy of the platform with the supercomputing and the reliable storage ability.
机译:本文分析了分布式数据的关键技术,提出了基于物联网信息平台的海量数据处理解决方案。该解决方案使用Hadoop作为开放源代码框架来实现分布式计算系统,并使用Mahout作为数据挖掘算法库来实现k-means聚类算法的并行化。通过海量数据处理,将实现高效率和大可扩展性。该项目中使用的海量数据源来自智能农业信息服务平台。该系统对海量感知信息进行了部署测试,并优化和并行化了K-means算法,实现了基于物联网信息平台的海量数据处理。它可以进行统计分析,并提供精细的管理等服务。该算法通过超级计算和可靠的存储能力,提高了平台的效率和准确性。

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