Title: A constraint-based job recommender system integrating FoDRA

Authors: Nikolaos D. Almalis; George A. Tsihrintzis; Evangelos Kyritsis

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: We present a framework for a constraint-based recommender system that matches available job positions with job seekers. Our framework utilises the four dimensions recommendation algorithm (FoDRA) in which a job attribute (e.g., age of candidate) can be modelled in four classes: exact value (E), a range with lower limit (L), a range with upper limit (U) and a range with both lower and upper limit (LU). FoDRA allows us to better formulate the job seeking and recruiting domain in a computational form. We describe both the system architecture in a high-level and the algorithm formulation of the job seeking and recruiting domain required by FoDRA. Our framework is validated through comparative experiments with real data obtained from the website of Kaggle.

Keywords: constraint-based; recommender system; job recommender; job seeking; job recruiting; recommendation algorithm.

DOI: 10.1504/IJCISTUDIES.2018.094894

International Journal of Computational Intelligence Studies, 2018 Vol.7 No.2, pp.103 - 123

Received: 20 Sep 2017
Accepted: 20 Sep 2017

Published online: 13 Sep 2018 *

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