Aiming at the problems of incomplete information and low data mining efficiency in the current student management system, a college student portrait system is established based on Hadoop big data processing technology. The system collects student data from various business platforms in colleges and universities, and uses HDFS for data storage; uses canopy and k-means based clustering algorithms for multi-dimensional analysis of student data; uses Echart tool to visualize the analysis results and generate student portraits. Experiments show that the student portrait system based on canopy and k-means can describe students' images in multiple dimensions and help schools understand students more comprehensively.
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