Intelligent shortlisting process for job applicants using fuzzy logic-based profiling
A modified version of shortlisting algorithm is presented to improve the selection process of hiring skilled and competent individuals. This algorithm uses fuzzy logic to quantify the educational background and alignment of the applicants as well as their skills and experience. The proposed algorith...
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| Main Authors: | , , |
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| Format: | text |
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Animo Repository
2019
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1876 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2875/type/native/viewcontent |
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| Institution: | De La Salle University |
| Summary: | A modified version of shortlisting algorithm is presented to improve the selection process of hiring skilled and competent individuals. This algorithm uses fuzzy logic to quantify the educational background and alignment of the applicants as well as their skills and experience. The proposed algorithm shows added flexibility to the human resource managers to choose between the educational background and work experience of a candidate. Two significant numerical outputs are given by the proposed fuzzy inference system namely the Highly Educated Area and the Highly Skilled Area. This scheme enables the company to include the educational alignment of the applicant with respect to the position applied for, and the work experience he had in his previous employments. This intelligent system predicts and filters mechanisms to measure a candidate’s alignment to a specific job post, predicting their possible future performance by ranking each individual candidate in real time. This creates a more equitable hiring and selection process for organizations as it determines the best fit candidates according to its needs. © 2019, World Academy of Research in Science and Engineering. All rights reserved. |
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