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Multidimensional Data Mining on the Early Scientific Talents of China

The cultivation of high-level talents in either scientific or engineering domain is of significant importance to the development of a country. From the perspective of data science, this paper takes the group of academicians of the Chinese Academy of Sciences and the Chinese Academy of Engineering as an example to explore the method of cultivating high-end talents. Through multidimensional data analysis, it is of great significance to explore the spatial pattern and time evolution characteristics of the first generation of top natural science talents in China, to deepen the understanding of the growth and education laws of talents, optimize top-level design, and implement targeted scientific policies. It is found that Chinese culture and Chinese native universities have made significant contributions for the early scientific talents of China, and the analysis method of data science can be used to facilitate the education innovation.