Knowledge mapping analysis of Chinese traditional culture under the strategy of common wealth

Abstract

Abstract With the continuous improvement of people’s living standards, their attention to the spiritual world and culture, especially traditional culture, is gradually increasing. With the help of the graph-based data structure of a knowledge graph, the connections between entities in conventional culture can be more intuitively displayed in the form of nodes and edges. Traditional knowledge is represented by the Trans series model in this paper, and the attention mechanism is integrated into the Graph Attention Network Model (GAT). The descriptive information of entities and relationships was introduced for pre-training initialization, and a Graph Attention Network Connection Prediction Model (BFGAT) was proposed to integrate the descriptive information and structural features and the BFGAT model was optimized by using information filtering operations. After the experimental study of the performance of the modified model, it is found that the score of the BFGAT model is 0.594 under the Hits@10 evaluation index in the dataset WN188RR, which is 0.01 and 0.018 higher than the two variant models, respectively, and the performance is better than that of other models. In the analysis of the ability of the knowledge graph to disseminate Chinese traditional culture, the number of searches for “Confucius” in Chinese traditional culture in the Americas is higher. The search frequency of Confucius has increased significantly from 2013 to 2014, from 830,000 times in 2013 to 2.95 million times in 2014, and the search frequency of Confucius in the Americas has reached 7.59 million times in 2023. It can be seen that the knowledge graph technology based on the knowledge graph attention network link prediction model has higher accuracy for keyword recognition and is also conducive to the wide dissemination of traditional Chinese culture.