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This paper first investigates the expressive features and developmental commonalities of Chinese modern and contemporary literary works, explains the paradoxical nature, and there are dilemmas in the expressive features by reviewing the data, and proposes the nationalized literary model and the cosmopolitan literary model, aiming to promote the development of Chinese modern and contemporary literature. Then, based on text mining techniques, atomic cuts are performed in the lowest fifth layer using Hidden Markov Models, and rough Chinese word splitting is performed using the n-shortest path method to find out the most likely n ambiguous word splitting results and text clustering analysis based on HMM-LDA topic models is performed on top of the splitting results. The results show that the HMM-LDA text recognition model is more accurate than the HMM text recognition model in terms of recall and accuracy of entity recognition in five categories of Chinese modern and contemporary literature: poetry, prose, drama, novel, and picture. Through this study, people gain a deeper understanding of modern and contemporary literature, gain some insight, and establish a foundation for promoting modern and contemporary literature.