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Massive AI based cloud environment for smart online education with data mining

机译:基于庞大的AI云环境,具有数据挖掘的智能在线教育

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Under the background of the deep integration of Internet technology and artificial intelligence technology with the field of education, the traditional teacher centered teaching mode is facing a historic change. How to guide students to learn and communicate actively, and explore and improve the new student-centered teaching mode, has become the key problem to be solved. In the mixed cloud environment, the data stream is disturbed, and the error of mining association data is large. Aiming at the problem of poor anti-interference of scattered point cloud adaptive compression mining algorithm, this paper analyzes the data mining technology in cloud environment. Firstly, the time series analysis model of big data information flow in hybrid cloud environment is constructed to analyze the data structure, and then the high-dimensional phase space of data information flow in hybrid cloud environment is reconstructed. In the reconstructed phase space, the association rules are extracted, and the extracted features are used as pheromones to guide data location mining, so as to improve the data mining algorithm.
机译:在互联网技术的深度集成的背景下,与教育领域的互联网技术和人工智能技术,传统教师以中心的教学模式面临着历史性的变化。如何引导学生积极学习和沟通,探索和改善新的学生中心的教学模式,已成为要解决的关键问题。在混合云环境中,数据流受到干扰,并且挖掘关联数据的错误很大。旨在散射点云自适应压缩挖掘算法缺陷抗干扰差的问题,分析了云环境中的数据挖掘技术。首先,构造了混合云环境中大数据信息流的时间序列分析模型,分析了数据结构,然后重建了混合云环境中的数据信息流的高维相位空间。在重建的相空间中,提取关联规则,提取的特征用作指导数据位置挖掘的信息素,从而提高数据挖掘算法。

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