The Application Of Data Mining In Enrolment Decision

With the continuous advance of the higher education and the yearly enrollment expansion, coupled with student pool declining, it’s more intense competition among the institutions in the source of students between. Additionally there are a large number of colleges and universities in Jiangsu province, the problems such as few qualified candidates and low report rate are more obvious. Thus a real problem of how to effectively process and analysis the information of student pool for accomplishing enrollment task effectively with fewer expenses becomes distinctive among most colleges and institutes.Many universities in Jiangsu province have a long history and a lot of biogenesis information. This information can easily be processed and will become a reference to guide the work of the admissions. But this information is not attached great importance that makes these data become worthless.At present, these colleges haven’t found out instructive and scientific knowledge from historical data to guide them in recruitment work.Data mining is a process to extract or’dig out’knowledge from a large amount of source data. The thesis will use the technique of association rules and decision tree in data mining to complete a series of work such as building the data mining process model and mining analysis for Jiangsu Province accumulated a large number of " junior college student to undergraduate" data over the years. Then find the guidance information of recruitment and enrollment propaganda work, so as to improve the efficiency of school enrollment.Firstly, the thesis describes the concept, principle, implementation tools and methods of data mining technology.According to the implementation of the universities and colleges admissions characteristics and enrollment propaganda, and then following the requirement of data mining technology, the author structures the overall architecture of the information which" junior college student to undergraduate" students pool data classification and analysis.The main content of this thesis includes constructing student pool information data model, and analysis data on the basic of association rules and decision tree classification analysis. We can find out some meaningful information to guide universities’decision of recruitment propaganda and enrollment publicity overall planning that avoid the phenomenon that the waste of resources in the enrollment.