A COMPETENCY BASED RECRUITMENT MECHANISM USING COGNITIVE TAXONOMY AND VECTORIZATION TECHNIQUES
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a competency-based recruitment platform designed to address the limitations of traditional resume-driven hiring systems. In existing recruitment processes, candidates often rely on self-declared skills and unverifiable credentials, leading to inefficiencies, bias, and incorrect hiring decisions. This paper proposes a skill-first hiring system where candidates are evaluated through structured assessments and are issued verified certificates based on their actual performance. The system integrates skill testing, certification, job matching, and hiring analytics into a unified platform. Employers can utilize intelligent metrics such as hiring confidence score, risk score, and role fit index to make data-driven decisions. The platform reduces dependency on resumes and enables fair opportunities for candidates, especially freshers, to prove their abilities. Additionally, it improves hiring accuracy, reduces recruitment time, and enhances transparency in the hiring process. Future enhancements include AI-based recommendation systems and blockchain-enabled certificate verification for global trust. Devourtise aims to create a scalable, unbiased, and efficient hiring ecosystem driven by real skill validation.
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Kumar, J. S., S.Soundarya, & Joseva, S. (2026). A Competency Based Recruitment Mechanism using Cognitive Taxonomy and Vectorization Techniques. International Journal of Science, Strategic Management and Technology, 02(04). https://doi.org/10.55041/ijsmt.v2i4.029
Kumar, J.Meshak, et al.. "A Competency Based Recruitment Mechanism using Cognitive Taxonomy and Vectorization Techniques." International Journal of Science, Strategic Management and Technology, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i4.029.
Kumar, J.Meshak, S.Soundarya, and S.Kivin Joseva. "A Competency Based Recruitment Mechanism using Cognitive Taxonomy and Vectorization Techniques." International Journal of Science, Strategic Management and Technology 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i4.029.
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