Data Analysis Method of Talent Cultivation Based on Relational Graph

Data Analysis Method of Talent Cultivation Based on Relational Graph

A large amount of data are produced in the process of postgraduate training. Based on relational graph technology, a complete technical scheme is proposed inclouding big data integration, relationship extraction and visualization. It can serve the training of high-level talents in Colleges and universities. Firstly, it analyzes the characteristics of postgraduate training big data, and puts forward the construction of multi-layer concept entity to complete the concept model of relation graph. And a classification algorithm based frequent item mining is proposed to analyze the employment data. Then, a communication architecture among indifferent relational databases and graph database is designed to solve the problem of access conflict. The research method completes the distributed integration of training big data, excavates and displays the training information and its rules to guide the education practice. Take the school of information science and technology of North China University of technology as an example to show the application effect. This method is suitable for expressing the relationship between complex structured big data in a certain professional field, especially the data sets stored in different relational databases. It can not only clearly show the relationship between different granularity entities, but also greatly improve the efficiency of relationship extraction.