A constraint-based job recommender system integrating FoDRA
by Nikolaos D. Almalis; George A. Tsihrintzis; Evangelos Kyritsis
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 7, No. 2, 2018

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.

Online publication date: Wed, 26-Sep-2018

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