Data Mining Techniques Applied Research In The Evaluation Of The Overall Quality Of College Students

With the development of computer technology and communication technology development, the amount of data accumulated in all walks of life is in explosive growth, at the same time there is an urgent need for people to extract useful knowledge from these huge mounts of data to guide decision-making, win economic benefit and social benefits. Data mining technology arise from this demand. Data mining based on data statistic and analysis, comprehensive and reasoning, guide practical problems solved, found the mutual correlation between things and make prediction, its research and application has become a hot of computer science and engineering research.With the change of higher education from elite education to mass education, the number of college students surge, student management work is facing many new problems. At the same time, individual management department accumulate massive student data, these data often imply some deep useful information. Using the data mining technology to the university's student management, we can better manage college students, improve their ability and quality in all aspects, it is an active exploration to solve new problems.The research mainly divided into two parts. First part describe data mining technology, data warehouse technology and LOAP technology, focusing on introducing the thoughts and methods of data mining and the mining processing combining with OLAP and data warehouse technology. This part is mainly theoretical research, provide a theoretical basis for the application of data mining technology in the comprehensive evaluation system of university studentsThe second part study comprehensive evaluation system of university students, not only Introduce the situation of the comprehensive evaluation system of university students on the current, but also summary the problems in the comprehensive evaluation system of university students. Proposing a new kind of method of evaluation students'Comprehensive quality, with quantitative analysis and the qualitative analysis unified, by integrating the existing method and approach of the university students'management and utilizing the decision tree, relevancy rule analysis, and clustering analysis, building up model to analyze objects'index and figures. We Create multidimensional mining models of comprehensive evaluation of students, achieve the application of decision tree in the comprehensive evaluation and graduate recommendation, and the application of clustering in the course.