Integrative Development of Modern Literary Works and Traditional Culture Combined with Semantic Association Network Modeling

Abstract

Abstract The coupling framework of modern literary works and traditional culture is first discussed in this paper, and the intrinsic connection between them is examined. Secondly, a semantic-associated information extraction network model is constructed using LSTM and attention mechanism, and the target semantic fusion is achieved through semantic space conversion and semantic-associated information extraction. Finally, the dataset and empirical analysis confirm the SAIEDMMA model’s effectiveness. The results show that the F1 value of the SAIE-DMMA model on the Total-Text dataset and ICDAR2015 dataset is 85.59% and 87.72%, respectively. The traditional culture of folk culture has the highest degree of integration in modern literature, and the growth of its literature from 2017 to 2021 is 1,273 books. This shows that the semantic correlation information extraction network can analyze the semantics of the integration of modern literary works and traditional culture, and it can also be used to promote the effective inheritance and development of traditional culture so that modern literary works are closer to public life.