To solve the excessive utilization of back-end data caused by the sharp increase in the visit and consultation on the intelligent learning platform in the era of novel coronavirus epidemic, this study proposed to introduce Co-attention mechanism (Co-attention) into the Bidirectional Long Short Term Memory model (Bi-LSTM). The study employed Multi-layer Perception Network (MLP) for classification and screening to accurately judge the semantic repeatability. Lastly the study carried out contrast experiments for different models, using 1150 consultation posts about transposed determinant, using Newton’s Leibniz formula to calculate definite integral, using Laplace’s theorem to calculate determinant, how to do model analysis of STATA panel data, under what circumstances is the weighted least square method applicable, how to realize the Pareto optimality and finding the area of trapezoid with curve side from MOOC platform of Chinese universities. Results show that this model performs better than other existing models on the judgment accuracy and its accuracy is up to 89.42%.
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