A study on applying data mining technologies for recruitments

• Main Authors: SHU-HAN HSIAO, 蕭書涵
• Other Authors: TIAN-SHYUG LEE
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/20391276165678129672

碩士 === 輔仁大學 === 管理學研究所 === 96 === There are many ways for recruitments. Interview is one of the most popular methods for recruitment. Before interview, the first step is to sift the information from the resume carefully to find right person for every specific position. It is difficult to do the filtering without advisable tools. In the research, we apply data mining techniques for recruitments, especially aim at filtering resumes. The techniques including discriminant analysis, multivariate adaptive regression splines (MARS), classification ,regression tree (CART) and artificial neural networks (ANN) are adopt to build classification models using every variables in the resume that may influence the performance of employees. The cross validation process is used in each classification model to understand the relations between the information in the resume and performance of employee. Experimental results showed that the data mining techniques can help companies to recruit right employees which produce higher performance.