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Model of Cloud-Based Services for Data Mining Analysis

机译:用于数据挖掘分析的基于云的服务模型

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New cloud-based services are being developed constantly in order to meet the need for faster, reliable and scalable methods for knowledge discovery. The major benefit of the cloud-based services is the efficient execution of heavy computation algorithms in the cloud simply by using Big Data storage and processing platforms. Therefore, we have proposed a model that provides data mining techniques as cloud-based services that are available to users on their demand. The widely known data mining algorithms have been implemented as Map/Reduce jobs that are been executed as services in cloud architecture. The user simply chooses or uploads the dataset to the cloud, makes appropriate settings for the data mining algorithm, executes the job request to be processed and receives the results. The major benefit of this model of cloud-based services is the efficient execution of heavy computation data mining algorithm in the cloud simply by using the Ankus - Open Source Big Data Mining Tool and StarfishHadoop Log Analyzer. The expected outcome of this research is to offer the integration of the cloud-based services for data mining analysis in order to provide researchers with reliable collaborative data mining analysis model.
机译:为了满足对知识发现的更快,可靠和可扩展方法的需求,正在不断开发新的基于云的服务。基于云的服务的主要好处是,只需使用大数据存储和处理平台,即可在云中高效执行繁重的计算算法。因此,我们提出了一个模型,该模型提供数据挖掘技术作为基于云的服务,可供用户按需使用。众所周知的数据挖掘算法已实现为Map / Reduce作业,这些作业在云体系结构中作为服务执行。用户只需选择数据集或将数据集上传到云,为数据挖掘算法进行适当的设置,执行要处理的作业请求并接收结果。这种基于云的服务模型的主要好处是,只需使用Ankus-开源大数据挖掘工具和StarfishHadoop Log Analyzer,即可在云中高效执行大量计算数据挖掘算法。这项研究的预期结果是为数据挖掘分析提供基于云的服务的集成,以便为研究人员提供可靠的协作数据挖掘分析模型。

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