抄録
Recruitment and selection have the first priority in human resource management. Poor selection decisions can be enormously costly to organization. So a valid decision method is needed. Traditional selection method is based on linear model. However, it is not proper for this intricate nonlinear relationship between applicants and job performance. In this paper, we introduce a new human resource selection system using weighted support vector machine (WSVM) which is fit for the nonlinear problem. It gives the selection process a feedback and improves classification results. Besides, we also proposed a new weight generating method to keep the characteristic of human resource. It reduces the effect of outliers and noise for classification, and distinguishes different importance of selection criterions. Furthermore, different weights are compared for WSVM. Questionnaire survey was issued to acquire dataset. Simulation results show that our proposed selection system is valid for human resource selection;it performs higher classification accuracy than traditional linear method. It can be used to support the decision making in human resource selection. Besides, different weight generating methods are compared for WSVM, our proposed weight generating method obtains better efficiency than standard SVM and class center based weight generating method.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 407-415 |
| ページ数 | 9 |
| ジャーナル | Journal of Advanced Computational Intelligence and Intelligent Informatics |
| 巻 | 13 |
| 発行部数 | 4 |
| 出版物ステータス | Published - 2009 |
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ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Human-Computer Interaction
これを引用
Human resource selection based on performance classification using weighted support vector machine. / Wang, Qiangwei; Li, Boyang; Furuzuki, Takayuki.
：: Journal of Advanced Computational Intelligence and Intelligent Informatics, 巻 13, 番号 4, 2009, p. 407-415.研究成果: Article
}
TY - JOUR
T1 - Human resource selection based on performance classification using weighted support vector machine
AU - Wang, Qiangwei
AU - Li, Boyang
AU - Furuzuki, Takayuki
PY - 2009
Y1 - 2009
N2 - Recruitment and selection have the first priority in human resource management. Poor selection decisions can be enormously costly to organization. So a valid decision method is needed. Traditional selection method is based on linear model. However, it is not proper for this intricate nonlinear relationship between applicants and job performance. In this paper, we introduce a new human resource selection system using weighted support vector machine (WSVM) which is fit for the nonlinear problem. It gives the selection process a feedback and improves classification results. Besides, we also proposed a new weight generating method to keep the characteristic of human resource. It reduces the effect of outliers and noise for classification, and distinguishes different importance of selection criterions. Furthermore, different weights are compared for WSVM. Questionnaire survey was issued to acquire dataset. Simulation results show that our proposed selection system is valid for human resource selection;it performs higher classification accuracy than traditional linear method. It can be used to support the decision making in human resource selection. Besides, different weight generating methods are compared for WSVM, our proposed weight generating method obtains better efficiency than standard SVM and class center based weight generating method.
AB - Recruitment and selection have the first priority in human resource management. Poor selection decisions can be enormously costly to organization. So a valid decision method is needed. Traditional selection method is based on linear model. However, it is not proper for this intricate nonlinear relationship between applicants and job performance. In this paper, we introduce a new human resource selection system using weighted support vector machine (WSVM) which is fit for the nonlinear problem. It gives the selection process a feedback and improves classification results. Besides, we also proposed a new weight generating method to keep the characteristic of human resource. It reduces the effect of outliers and noise for classification, and distinguishes different importance of selection criterions. Furthermore, different weights are compared for WSVM. Questionnaire survey was issued to acquire dataset. Simulation results show that our proposed selection system is valid for human resource selection;it performs higher classification accuracy than traditional linear method. It can be used to support the decision making in human resource selection. Besides, different weight generating methods are compared for WSVM, our proposed weight generating method obtains better efficiency than standard SVM and class center based weight generating method.
KW - Human resource selection
KW - Weighted support vector machine
KW - Weights generating method
UR - http://www.scopus.com/inward/record.url?scp=77749338955&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77749338955&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:77749338955
VL - 13
SP - 407
EP - 415
JO - Journal of Advanced Computational Intelligence and Intelligent Informatics
JF - Journal of Advanced Computational Intelligence and Intelligent Informatics
SN - 1343-0130
IS - 4
ER -