Abstract: The application of computer information management system (IMS for short here) in university management faces problems such as incomplete system software and complex system design. Applying clustering algorithms (CA for short here) to computer student IMS can help optimize the system’s overall effectiveness. This article constructed a computer student IMS based on computer technology and applied it to the management of college students. This article also combined CA to conduct relevant effectiveness tests on the system, in order to optimize the overall effectiveness of the system. Under the algorithm in this article, the average connection speed for each user accessing the system was 9.17 Mbps. The average reaction time was 0.34 seconds, the average security level was 92.47%, and the highest memory usage rate of the system was 34.27%; Under the decision tree algorithm, the average connection speed of each user accessing the system was 8.82 Mbps, and the average reaction time reached 0.64 s. The average security level was 88.41%, and the highest memory usage rate was 42.58%. Under the artificial neural network algorithm, the average connection speed of the system was 8.47 Mbps, the average response time was 0.86 s, and the highest memory usage rate was 45.97%. Analyzing the data reveals that the algorithm introduced in this paper significantly enhances system connection speed and reduces reaction time. This improvement not only enhances security measures but also minimizes memory usage, effectively optimizing the overall efficiency of the system.
Keywords: Computer information management system, university management work, student information management, system safety, clustering algorithm
