Adaptation of “The Legend of Chunhyang” in Contemporary Korean Literature: the Analysis from the Perspective of Comparative Literary Variation based on the Optimized ItemCF and the Philosophical Dialectical Thought

Abstract

In the case of Joseon, the social development in the last millennium, the increasing aesthetic awareness, the admiration for Chinese literature and culture, the strong spread of advanced Chinese thought and culture, and the active exchanges between Joseon students and Chinese literati have provided the main soil for the emergence of literary theories in Joseon, and there are sufficient data to prove that Chinese literary texts and literary ideas have had an influence in Joseon. So far, numerous materials indicate that the formal essence and dialectical philosophical thought of Chinese literature have significantly influenced Korean culture and the mindset of Koreans. Moreover, in the process of fusion and evolution with Korean literature and philosophical thought, Chinese literature and philosophical ideas are influenced by native Korean culture, leading to variations. It can be said that without Chinese classical literature and philosophy, there would be no Korean classical literature and philosophy. Based on the evolution of Korean literature and the optimized ItemCF algorithm, this paper analyzes in depth the influence of Chinese classical literature on the literary creation of the Korean peninsula and accurately grasps the relationship between the origin and flow of Chinese and Korean classical literature. The experimental results indicate that the optimized ItemCF algorithm can accurately identify Chinese literary stories present in Korean literature, along with the underlying philosophical and dialectical ideas from Chinese literature. Moreover, through similarity analysis, the algorithm computes the potential evaluative value of Chinese stories within Korean literature, aiding in evaluating and analyzing philosophical and dialectical thinking within these narratives. The experiments prove that the optimized algorithm can significantly improve the data cleaning efficiency compared with ItemCF, and its user similarity matrix generation speed and efficiency are significantly improved by 20%. After the matrix test, the algorithm has obvious advantages for the variation of comparative literature.