Association Rule Mining for Academic Talent Introduction
With the advancement of higher education, many colleges have given increasing attention to talent introduction.On the other hand, the association rule mining technique is a useful method which extracts the useful association rules from the complex data repositories.In this study, we take the example of 245 academic staff from Zhejiang University of Finance and Economics, China and use Apriori algorithm to explore the association rules on whether an academic staff can obtain the Natural Science Foundation of China (NSFC) within three years after s/he is recruited to the university.The aim of this study is to better introduce talents for colleges so that the academic levels of colleges can be improved.The results of association rule mining have shown that having published high quality papers such as SCI paper and SSCI paper has an important effect on the probability of academic staff to obtain NSFC within three years.Besides, the grade of PhD school has also an effect on the probability of academic staff to obtain NSFC within three years.The higher the grade of a staffs PhD school is, the easier for him to obtain NSFC within three years.
data mining association rule mining apriori algorithm
Zixuan Chen Jiepin Ding Zhiguang Zhou Yin Zhu Wenyu Zhang
School of Information Zhejiang University of Finance and Economics Hangzhou,China
国际会议
郑州
英文
141-147
2018-09-21（万方平台首次上网日期，不代表论文的发表时间）