Based On Olam Technology Research In College Recruiting System

There is a prevalence of the phenomenon in higher education colleges, low attendance of the new students. This low rate not only affect the healthy development, also caused a huge waste of educational resources for the colleges. Currently, these are based on knowledge of recruitment piecemeal, decentralized approach exist, no system, the focus of knowledge. Therefore, this thesis puts forward an OLAM technique applied to the college entrance, analysis system method to calendar information, and candidates taking the students to report the information as input, using data mining techniques to obtain enrollment data in the report's implicit knowledge of the students.Based on the implementation process with OLAM college enrollment system, the thesis mainly focus on three aspects of the following:(1) The key of enrollment data is fusion the technology research, detailed analysis of the calendar year to report enrollment data and data structure, using the SSIS tools to be integrated to form a comprehensive data warehouse, provided for the realization of the data based OLAM with analysis of data.(2) The methods of filter the elements enrollment, the detailed information of the students contained in the admission data file calendar years. Use of association rules mining data warehouse integration of good, get the new report obtained key elements of its influence.(3) Data mining algorithm, to analyze the data mining algorithm for mining the characteristics of the common and constant application environment, select the association rules algorithm by obtaining the elements of admissions, after the cluster analysis algorithm used by the applicable rules to guide the enrollment policy development.Finally, dig out the knowledge of the system used to guide student enrollment in Hunan Institute of Environmental Biology 2010, the results show, that student's attendance to the college in 2010 reached 93.22%, compared with 13% growth in previous years.