Abstract
In the era of “Internet + education,” the information technology and learning methods of college students have become inseparable. The rapid development of intelligent translation software can provide convenience for English-Chinese translation and computer English learning and simultaneously improve the quality and efficiency of professional English learning. Under such background, the English teaching of software majors is chosen as the breakthrough to analyze the measures of applying intelligent translation software during the teaching process. Therefore, a data mining algorithm including cluster analysis and BP neural network model is designed. Then, the cluster analysis algorithm is used to classify the data in different forms, which can improve the data utilization efficiency. In addition, K-means algorithm based on feature selection is improved to achieve better performance. In the comparison of translation speed and matching rate, our method is much better than other software.
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