The Beauty of Context and Its Expression in Chinese Language Literature: Based on the Perspective of Semantic Contrastive Analysis

This paper conducts an in-depth study centering on the beauty of context and its expression in Chinese language literature, mainly from the perspective of semantic contrastive Analysis. Firstly, the study utilizes various natural language processing techniques including LSTM neural network and GRU model to acquire and process textual semantic information by constructing a specific Chinese language contextual model. Then, an empirical analysis of Chinese language literature was conducted, and accuracy and recall were used as evaluation criteria to compare different Chinese language contextual models. The results show that the LSTM-GRU-based Chinese language contextual model significantly improves accuracy and recall. In addition, the model’s effectiveness in improving the ability of contextual Analysis in Chinese language literature is demonstrated through the review and Analysis of Chinese language literary works. Finally, the article proposes strategies to improve the ability of contextual Analysis in Chinese language literature. © 2023 Xiaojing Chen, published by Sciendo.