Massive AI based cloud environment for smart online education with data mining
Ying Pei, Gang Li · 2021
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.