Research and Analysis of Student Portrait Based on Campus Big Data

With the rapid development of smart campuses, college business platforms have gradually accumulated a large amount of student behavior data. Facing the massive campus data, how to extract the hidden and valuable information from it has become an urgent problem for universities to solve. In this project, an user model with five dimensions is proposed, in which include students' basic information, learning ability, consumption level, daily habits and interest preferences. Based on the method of data collection, processing and mining, the students' feature attributes are extracted and student portraits are constructed. Finally, the experimental results show that the student portrait constructed can well describe the digital features of student users, and to a certain extent, provide data basis for decision-making support of teaching management department in universities.