Abstract
Colleges and universities must generate a lot of student behavior data during the informatization construction, such as card usage data, grades and grade point data, etc. These data can fully reflect the trajectory of students’ activities. Therefore, strengthening the analysis and research of student behavior data will help the school to better manage it, so as to better build a smart campus. The purpose of this paper is to design a smart campus student behavior analysis system based on data mining algorithm. The relevant theories and technologies involved in the functional design and implementation of the student behavior analysis system based on data mining are studied. The software architecture, the design of the system operating system, the physical development architecture for storing system data, and the physical and logical design of the database are introduced. The detailed design process of system modules is analyzed, including integrated vertical behavior module, student behavior early warning module, student big data analysis report module, student behavior trajectory module, early warning rule design, and interface design module. 82% of students borrowed books recommended by the association analysis book model within three months.
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Acknowledgement
This work was financially supported by Xi'an Fanyi University, Construction project of counselor's studio of Xi'an Fanyi University “IPE and guidance studio for college students -- ideological and theoretical education and value guidance”.
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Han, W., Mansour, K. (2023). Student Behavior Analysis System in Smart Campus Based on Data Mining Algorithm. In: Abawajy, J.H., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) Tenth International Conference on Applications and Techniques in Cyber Intelligence (ICATCI 2022). ICATCI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-031-28893-7_44
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