SmartRecruit: A Fuzzy Rule-Based Expert System for Candidate Screening and Ranking
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Abstract
Human Resource (HR) management plays a pivotal role in organizational success, with recruitment being one of its most critical functions. In recent years, the integration of Artificial Intelligence (AI) into HR processes has gained significant attention, particularly in automating recruitment to enhance efficiency and reduce biases. While AI-driven systems have demonstrated advanced capabilities, many lack adaptability across diverse job roles and often fail to provide transparency in decision-making. This research addresses these limitations by proposing a novel fuzzy A Fuzzy Rule-Based Expert System for Candidate Screening and Ranking (SmartRecruit). The system evaluates candidates based on key parameters such as skills, educational qualifications (e.g., CGPA), and work experience, offering an efficient, unbiased and transparent approach to hiring.
Manuscript received: 9 Apr 2025 | Revised: 12 Jun 2025 | Accepted: 30 Jun 2025 | Published: 30 Nov 2025
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References
K. Ekuma, "Artificial Intelligence and Automation in Human Resource Development: A Systematic Review," Human Resource Development Review, vol. 23, no. 2, pp. 199-229, 2024.
DOI: https://doi.org/10.1177/15344843231224009
V. D., J. M. and M. I., "Application of Fuzzy Logic for Personnel Selection," International Journal of Computer Applications, vol. 179, no. 15, pp. 21-25, 2018.
DOI: https://doi.org/10.5120/ijca2018916093
R. Afshari, M. Nikolic and D. Cockalo, "Applications of fuzzy decision making for personnel selection problem: A review," Journal of Engineering Management and Competitiveness, vol. 4, no. 2, pp. 68-77, 2014.
DOI: https//doi.org/10.5937/jemc1402068A
G. Kaur and R. Kaur, "A critical review on analysis of human resource functions using AI technologies," AIP Conference Proceedings, vol. 2555, pp. 020004, 2022.
DOI: https://doi.org/10.1063/5.0108980
M. Ivanov, S. Ivanov, N. Terentieva, V. Maltiz and J. Kalyuzhnaya, "Fuzzy modeling in human resource management," E3S Web of Conferences, vol. 166, pp. 13010, 2020.
DOI: https://doi.org/10.1051/e3sconf/202016613010
Z. Demirel and C. Çubukçu, "Measurement of Employees on Human Resources with Fuzzy Logic," EMAJ: Emerging Markets Journal, vol. 11, no. 2, pp. 1-7, 2021.
DOI: https://doi.org/10.5195/emaj.2021.226
M. Hellmann, “Fuzzy Logic Introduction,” Rennes Cedex: Université de Rennes, 2001.
URL: http://epsilon.nought.de/tutorials/fuzzy/fuzzy.pdf
P. Horodyski, "Applicants' perception of artificial intelligence in the recruitment process," Computers in Human Behavior Reports, vol. 11, pp. 100303, 2023.
DOI: https://doi.org/10.1016/j.chbr.2023.100303
R. Meshram, "The role of artificial intelligence (AI) in recruitment and selection of employees in the organisation," Russian Law Journal, vol. 11, no. 9s, 2023.