The Application Of Data Mining In College Entrance Examination(CEE) Admission Factor Analysis

College Entrance Examination(CEE) is the most widely-adopted and influential examination in China. It has a huge impact on examinees’ lives and therefore the post-CEE application process is a delicate and important matter. The examinee and parents badly need a scientific way to research and analyze how to reasonably fill out the application so that it meets personal wishes and effectively avoids risk.On the other hand, CEE is more than an examination, but a systematic process that combines multiple tasks including registration, examination, application and admission, during which enormous amount of data is generated. For now, this data is not efficiently used. Most data process is limited to simple statistical analysis and inquiry. Information exchange between multiple systems and cross platform and feature-oriented high-level data analysis rarely occurs.This paper gathers a large amount of CEE-related data in a city, including CEE results data, admission data, examinee’s high school information and the admitted college information. Through data integration, data cleaning, data conversion and data specification to construct cube, and completed the entire process of On-Line Analytical Processing(OLAP) and data mining by SQL Server Analysis Services from a new perspective. It discovers conclusions such as common characters shared by examinees admitted by key universities, admission details of each administrative region, matching rate of examinees’ applications and popular provinces and cities applied by examinees. These conclusion are beneficial for developing new education and teaching evaluation standard,improving and enhancing teaching method and guiding examinee to fill out the application scientifically. It can effectively improve the utilization of the data and discover the hidden knowledge behind the data.