Data Mining In Wisdom Campus And IT’s Applications

With the advance of information technologies on office, now the wisdom campus is becoming the subject in campus construction, and has achieved certain results, the popularity of the E-card in the universities is a good example. However, a wealth of large and independent data is generated, such as student consumption data, the data from different sources including Internet data, the entrance guard Information and so on. Since the students’learning life is closely related to these data, therefore how to dig the useful information from these data, easing the situation of "data explosion, lack of knowledge", improving these data’s utilization and providing useful information predictability and timely, has became an urgent need in guiding building wisdom campus.In view of the above requirements, a visual wisdom campus data mining platform based on B/S architecture was designed and implemented in this paper, which including "logistics related data mining module","students related data mining module" and "dean related data mining module". Besides, data mining technologies and their algorithms were studied in order to choose a rational algorithm to each module function. And three strategies were proposed to against the shortcomings of C4.5for multi-fragmentation, over-fitting and inefficient. In "students related data mining module", the classification of students was realized based on the improved C4.5algorithm. In "dean related data mining module", the clustering of consumer information was implemented based on k-means algorithm and correlation analysis about scores was achieved based on Apriori algorithm. And the results show that it was effective to use data mining technologies to find useful information in the wisdom campus, and it has close relationship among student achievements, student attendance, access, consumption and other information.