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Chinese language is also an important way to understand Chinese culture and an important carrier to inherit and carry forward Chinese traditional culture. Chinese language teaching is an important way to inherit and develop Chinese language. Therefore, in the era of big data, data mining and analysis of Chinese language teaching can effectively sum...
Citations
... The article presents several forms of educational materials and shows how they may be used to enhance learning services [21] [22].The research explained about building the text clustering approach using convolutional neural networks may more effectively and thoroughly mine. Chinese character data led to the optimization of the k-means method to reach the desired accuracy [23]. The article developed the strength of the social and educational sectors involved with the standard of art education, as well as artistic potential. ...
... It has been demonstrated that the proposed strategy provides more accurate learning improvement than the current method. The existing methodologies like CNN [23], SVM [24] and KNN [25]. With the suggested system, accuracy is at 93%, while CNN is at 75%, SVM is at 63%, and KNN is at 82%. ...
Educational methods for data mining may be used to successfully analyze data from a variety of educational platforms, including e-learning, e-admission programs, and automated results management solutions, to provide very helpful insights into students' performance. Chinese language teaching will reach new heights as a result of the rapid advancement of network technology and the constant improvement of network transmission speed. Additionally, the acceptance of online payment methods is growing, simplifying international and web-based trade. Deep learning models have become more significant in many spheres of life recently. It made it possible for investigators to automatically extract superior characteristics from unprocessed data.With the aid of the Keras model, make it is easier for students to rapidly obtain practical knowledge with deep learning structures and boost their confidence and enthusiasm for learning. In this study, we investigate the Long Short-Term Memory (LSTM) deep neural network model with Novel Swarm Optimization (NSO) network to accurately forecast student improvement using historical data. The most cutting-edge LSTM and an optimization mechanism model (NSO) have been employed in this work to solve research issues based on sophisticated feature categorization and prediction. For Chinese academics, institutions, and government agencies to accurately anticipate performance, this study is very important. When paired with the optimization mechanism (NSO), LSTM's better sequence learning capabilities provide performance that is superior to the current state-of-the-art. The prediction accuracy of the suggested approach is 93%.
... Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: ...
