Application of Data Mining and Analysis Techniques in the China Biographical Database (CBDB)

Data mining and analysis techniques hold significant importance in the construction and application within relational databases, highlighting substantial advancements in integrating technology with scientific research methodologies. This paper primarily investigates three major technical developments. First, the use of VS Code for data vectorization training provides “templates” for neural network models, facilitating the automation of data extraction. Second, by utilizing QGIS technology, vector spatial analysis is conducted on specific groups to further interpret geographic data information in depth; third, using GEPHI, the influence tension of character relationships is quantified through GEPHI with degree centrality as the core indicator, to perform social network analysis on specific groups, thereby understanding the mechanisms of information transmission and the diffusion of influence. Through these technical approaches, this study offers valuable insights into the construction of relational databases, providing comprehensive recommendations for data extraction, spatial analysis, and social network analysis.