A Recommended Method for Teaching Information Resources of English Chinese Translation Based on Deep Learning

In the context of mass industry and innovative education, educational institutions and educators need to focus on cultivating students’ innovation ability and creativity, and prepare students for their future employment and career development by providing courses and practical opportunities for innovative education. At the same time, enterprises and industries also need to cooperate with educational institutions to jointly promote the development of innovative education and cultivate innovative talents that meet the needs of the mass industry. In order to ensure the effectiveness of English Chinese translation teaching information resource recommendation and improve the accuracy of English Chinese translation teaching information resource recommendation, a deep learning based English Chinese translation teaching information resource recommendation method is proposed. By analyzing students’ demand for teaching information resources in English Chinese translation, convolutional neural networks are used to extract the characteristics of teaching information resources in English Chinese translation. By utilizing the self coding neural network in deep learning methods, the correlation between English Chinese translation teaching information resources is excavated, and a recommendation model for English Chinese translation teaching information resources is constructed to achieve English Chinese translation teaching information resource recommendation. The experimental results show that the method proposed in this paper has a good recommendation effect on teaching information resources for English Chinese translation, and can effectively improve the accuracy of teaching information resource recommendation for English Chinese translation.