Research on big data women's portrait platform based on knowledge graph analysis

This study adopts the scientific knowledge graph research methodology, utilizing Cite Space information visualization software and China National Knowledge Infrastructure (CNKI) for visual analysis. It focuses on 483 journal papers from the CNKI database about personalized courses based on women profiling in China, especially revolutionary women. The research visually analyzes the studies on personalized platforms based on women's portrait in China. The study reveals that establishing student profiles involves using data science and educational technology methodologies such as machine learning, data mining, and artificial intelligence to process and analyze student information. This investigation aims to assist educational professionals in swiftly and accurately detecting the developmental trends of platforms based on women's portrait from a vast literature corpus. Furthermore, it aids in tracking dynamic hotspots in personalized platforms based on women's portrait and understanding the developmental directions of such platforms.