Research on Text Multi-Feature Fusion Algorithm Based on AM-CNN

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Abstract

How to know the changes of students' emotions in real time in online education has always been one of the important issues concerned by education departments and teachers. Making use of the special functions of global, part of speech and positional attention mechanisms in text processing, a deep learning network model based on the combination of multiple attention mechanisms and convolution neural networks is proposed. Firstly, the blending characteristics between the types of attention mechanism and CNN are analyzed by using the standard ChnSentiCorp_htl_all data set to clarify the effectiveness of the combination of the three attention mechanisms and CNN. Then the model is applied to the analysis of the evaluation text of the course "big data Technology principles and applications"on the MOOC of Chinese universities, and it is verified that the evaluation indexes of this model are better than the existing conventional models.

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Wensong, W., & Xiange, S. (2021). Research on Text Multi-Feature Fusion Algorithm Based on AM-CNN. In Journal of Physics: Conference Series (Vol. 1924). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1924/1/012032

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