Abstract
In the last decades the explosion of ICT has opened up new avenues regarding peoples' accessibility to new job opportunities. Current technological advances in conjunction with people's online presence provide a great opportunity to automate the recruitment process and make it more effective. In this paper, we propose a novel approach for improving the efficiency of e-recruitment systems. Our approach relies on the linguistic analysis of data available for job applicants, in order to infer the applicants' personality traits and rank them accordingly. To showcase the functionality of our method, we employed it in a web based e-recruitment system that we implemented. © 2011 Springer-Verlag.
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CITATION STYLE
Faliagka, E., Kozanidis, L., Stamou, S., Tsakalidis, A., & Tzimas, G. (2011). A personality mining system for automated applicant ranking in online recruitment systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6757 LNCS, pp. 379–382). https://doi.org/10.1007/978-3-642-22233-7_30
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