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Open interactive education algorithm based on cloud computing and big data

机译:基于云计算和大数据的开放式互动教育算法

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摘要

In order to improve the self-learning ability of cloud computing and scheduling ability of big data resources in open interactive education, an open interactive education algorithm based on cloud computing and big data is proposed. An information flow model for open education big data is constructed, and big data mining is conducted to an open interactive education platform through the association rules mining method based on parallel scheduling to extract semantic ontology information feature quantity of interactive education; spatial attribute clustering is performed in the cloud computing environment according to the feature extraction results, and big data information is scheduled through the multi-feature weight allocation method. Simulation results show that in open interactive education, this method can cause relatively good output performance of big data mining, relatively high accuracy of feature information clustering of open interactive education and relatively strong feature resolution and recognition ability of data output, which meets the educational resource scheduling and allocation requirements of open education.
机译:为了提高开放式交互式教育中大数据资源云计算和调度能力的自学能力,提出了一种基于云计算和大数据的开放式交互式教育算法。构建了开放教育大数据的信息流模型,通过基于并行调度,通过协会规则挖掘方法对开放式互动教育平台进行大数据挖掘,以提取互动教育的语义本体信息特征数量的并行调度;根据特征提取结果,在云计算环境中执行空间属性群集,并且通过多特征权重分配方法调度大数据信息。仿真结果表明,在开放式互动教育中,这种方法可能导致大数据挖掘的相对良好的输出性能,相对高的特征信息集群的开放式交互式教育和相对强大的特征分辨率和数据输出的识别能力,符合教育资源公开教育的调度与分配要求。

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