For College Entrance Admission Data Analysis System

With online admission work become more and more perfect, the informatization and the format unification for admissions have provided a good environment to the data processing, the statistics and the effective use. It is very important to analyses the calendar year of college enrollment data and mining useful information and provides a reference for college admissions.Data mining is using an objective statistics and analysis through a large number of data, found that the underlying law, to identify hidden patterns and thus to predict future trends. After the 20 years of development, data mining has become a multi-functional, very mature, representative of the algorithm, and has been applied successfully in many fields.First,this paper introduces the relevant theory of data mining technology knowledge; Then, the association rules mining algorithm and the decision tree algorithm which are used commonly in data mining are emphatically analyzed, and for the problems that traditional association rules mining algorithms need to scan the database many times, generate a great deal of candidate itemsets and treat each item as uniformity, a weighted association rules mining algorithm based on matrix is proposed. It only needs to scan the database once, and does not generate candidate itemsets. Meanwhile, the items with low frequency and high importance can be mined quickly. Finally, in the realization of papers, through the consideration desired by data mining purposes, demand analysing, system designing and results analysing, design the data analysis system for university admission. Under the Windows XP environment, using MS Visual C + + 6.0 as a development tool and Microsoft Access as database server provides background operation, Utilizing the improved mining algorithm for association rules and ID3 algorithm design a system for college admissions data analysis, using this system mining some ordinary college admissions database in ShanXi province, and drawing the effective association rules and classification rules, providing decision support for the college enrollment and management work.