Research on Application of Data Mining Based on Improved APRIORI Algorithm in Enrollment Management in Colleges and Universities

Abstract

The quality of higher education is the most important criterion to measure the level of higher education. The enrollment of colleges and universities is related to the survival and development of colleges and universities. It is one of the important links to improve the quality of talent training in Colleges and universities, which is one of the important links to improve the quality of talent training in Colleges and universities. Data Mining is a process of extracting potentially useful information and knowledge from a large, incomplete, noisy, fuzzy, and random data, also known as the Knowledge Discovery in Database (KDD), and APRIORI algorithm is a number of frequent item sets. According to the mining clustering algorithm, it is widely used in the field of data mining, but the algorithm also has some limitations. In the process of data mining, there may be some useless branches, which makes the algorithm inefficient and may result in error. The improvement of the APRIORI algorithm is applied to the college enrollment work, which can make the college admissions workers. No longer only rely on experience, it can be based on data, make the enrollment work more pertinent, more scientific and reasonable, so as to promote the improvement of the quality of talent training and enhance the overall competitiveness of colleges and universities.