Building a qualitative recruitment system via SVM with MCDM approach

Yung-Ming Li*, Cheng Yang Lai, Chien Pang Kao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Advances in information technology have led to behavioral changes in people and submission of curriculum vitae (CV) via the Internet has become an often-seen phenomenon. Without any technological support for the filtering process, recruitment can be difficult. In this research, a method combining five-factor personality inventory, support vector machine (SVM), and multi-criteria decision-making (MCDM) method was proposed to improve the quality of recruiting appropriate candidates. The online questionnaire personality testing developed by the International Personality Item Pool (IPIP) was utilized to identify the personal traits of candidates and both SVM and MCDM were employed to predict and support the decision of personnel choice. SVM was utilized to predict the fitness of candidates, while MCDM was employed to estimate the performance for a job placement. The results show the proposed system provides a qualified matching according to the results collected from enterprise managers.

Original languageEnglish
Pages (from-to)75-88
Number of pages14
JournalApplied Intelligence
Issue number1
StatePublished - Aug 2011


  • Candidate recruiting
  • Five-factor personality inventory
  • Personality trait
  • Support vector machine


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