The application of fuzzy association rules in the employment data mining of a higher vocational college
Laiquan Liu1, Li Lei2, Yanrui Lei1
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(3) 283-287
1 Hainan College of Software Technology, Fuhai Road No.128, Qionghai, Hainan, China
2 Chongqing University of Arts and Sciences, Huachuang Road No.598, Yongchuan, Chongqing, China
Data mining is able to extract potentially useful information from plentiful seemingly unrelated data. A high efficiency is therefore obtained using these useful data in work or study. Association rules mining is a significant branch in data mining. It mirrors the implicit relations among transactions in mass data. In addition, association rules can intuitively reflect the associations among item sets in data, and the relations are established according to the frequencies of the item sets appearing in data. This method, which explains its rules clearly and is easily to understand, therefore is different from the traditional statistical method. This research introduced and applied the mining algorithms of fuzzy association rules to the employment data analysis of a higher vocational college, in order to find significant association rules from numerous data and provide guidance for the education and employment in the future, therefore improving the employment rate further.