A personality mining system for automated applicant ranking in online recruitment systems

Authors:
Evanthia Faliagka;Lefteris Kozanidis;Sofia Stamou;Athanasios Tsakalidis;Giannis Tzimas
Affiliations:
Computer Engineering and Informatics Department, University of Patras, Patras, Greece;Computer Engineering and Informatics Department, University of Patras, Patras, Greece;Computer Engineering and Informatics Department, University of Patras, Patras, Greece and Department of Archives and Library Science, Ionian University, Greece;Computer Engineering and Informatics Department, University of Patras, Patras, Greece;Department of Applied Informatics in Management & Economy, Faculty of Management and Economics, Technological Educational Institute of Messolonghi, Messolonghi, Greece
Venue:
ICWE'11 Proceedings of the 11th international conference on Web engineering
Year:
2011

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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.