Application And Research Of Data Mining In The Graduate Enrollment Quality

With the rapid development of the computer technology and the database technology, the ability of people to collect data has been greatly improved. At the same time, a large amount of data have been accumulated. Usually, people only do some simple query or editing on these data. However, there is lots of useful knowledge and rules are implied in these data. In order to obtain the potential information to guide production and living, Data Mining Technology has been proposed. Data Mining is also known as knowledge discovery in database, that is the process of extracting available information and knowledge from mass, incomplete, noisy, fuzzy and random data. From the beginning of the concept on Data Mining, Data Mining Technology has been widely studied and has been successfully applied in the business, financial, medical and other fields.In recent years, with the reform and development of graduate student education, as well as the difficulty of obtaining a job becoming increasing prominent, graduate enrollment scale has to expand continually, and enrollment patterns also tend to diversify and autonomy. The competition between universities becomes fiercely. In order to expand the size of colleges, they all lowered the admission threshold, at present, the social have already hold a skeptical attitude. Therefore, how to improve the quality of graduate students has became a problem that colleges are eager to solve. Graduate enrollment is the first stage of the graduate education cycle, then the role of graduate enrollment is equivalent to the initial quality control. If raising the quality of graduate student, then it will improve the training quality. Therefore, the paper use Data warehouse and Data Mining Technology. Through the association rule and the decision tree classification algorithm, the paper provide support for the colleges' decision-makers.The research based on Data Mining, as well as the technology of Data warehouse, association rule algorithm and the decision tree algorithm, this paper mainly carry out research in the following areas:1) The paper research the theoretical knowledge of Data warehouse and Data Mining, include the organization of data in the data warehouse, data warehouse construction, the concept, the main content, processes, applications and algorithms of Data Mining. Select the appropriate Data Mining algorithms for this topic.2) With the theme "D university candidates source" describes in detail the data warehouse construction, the preparation of basic data, including data extraction, data cleaning, data conversion and the cube establishment.3) In the choice of test subjects, the classification of transfer students and the students with exemption of examinations, this paper used the Data Mining Technology. By analyzing the choice of test subjects, this paper can find the setting for courses whether reasonable, and predict the selection results. By classifying the transfer students and the students with exemption of examinations, this paper can find which areas or colleges are the main enrollment objects, the conclusion may assist managers to develop the enrollment publicity.4) Introduce the association rule algorithm into the analysis of the factors that affecting student admission, the conclusion can assist the college to select the outstanding candidates.According to the theories of the association rules algorithms and the decision tree algorithms, this paper finally conclude the rules and results for the graduate enrollment quality analysis.