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Title: Handling the crowd avoidance problem in job recommendation systems integrating FoDRA

Authors: Nikolaos D. Almalis; George A. Tsihrintzis; Ioannis Papaioannou

Addresses: Department of Informatics, University of Piraeus, Piraeus, Greece ' Department of Informatics, University of Piraeus, Piraeus, Greece ' National Technical University of Athens, Zografou Campus 9, IroonPolytechnioustr, 15780 Zografou, Greece

Abstract: In this article, we present the basic principles and approaches of job recommender systems (JRSs). Furthermore, we describe the four different relation types of the job seeking and recruiting problem, derived directly from the formal definition of JRSs. We use our previously published four dimensions recommendation algorithm (FoDRA) to calculate the suitability of a person for a job and then we model a job seeking and recruiting problem consisting of many candidates and many jobs (N-N case). Finally, we test the algorithm and present the results proposing a solution - the minimum acceptable suitability level - for the crowd avoidance problem that occurs. Our study produces good results and shows that this approach can be considered as an important asset in the domain of job seeking and recruiting.

Keywords: recommender system; job seeking and recruiting; job recommender; information filtering.

DOI: 10.1504/IJCISTUDIES.2020.106476

International Journal of Computational Intelligence Studies, 2020 Vol.9 No.1/2, pp.128 - 145

Received: 19 Feb 2018
Accepted: 25 Feb 2018

Published online: 02 Apr 2020 *

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