University Smart Campus Service Platform Based on Data Mining

Nowadays, the amount of data in the information system is showing a trend of diversification and explosive growth. The concept of “smart campus” has been put forward and has developed by leaps and bounds in recent years. The purpose of this article is to construct a service platform based on data mining. First, it analyzes the background, significance and research content of the platform. Secondly, the overall structure design and process of the platform are analyzed in detail, and the UML tool is used to model the system. Then, based on the B/S architecture, six functional units of the system are designed and data mining is carried out. K-algorithm refers to and MapReduce Framework and other integrated applications are used in this system. Through the analysis of various types of student behavior data in the school, the potential value behind these data is found. The performance test results show that the system runs for 50 days, the PostgreSQL data volume reaches tens of millions, and the average data synchronization time reaches 49 seconds.