International Journal of Education and Management Engineering (IJEME)
IJEME Vol. 15, No. 4, 8 Aug. 2025
Cover page and Table of Contents: PDF (size: 597KB)
Development of a Mobile Application for Employment Opportunities Matching in Nigeria Using the SVM Model
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Author(s)
Akpovoke Okoro
1
Gracious C. Omede
1
Franklin O. Okorodudu
1,*
Index Terms
Mobile Application, Front-End Techniques, Machine Learning, Support Vector Machines, and Unemployment
Abstract
A way to make job matching work better in Nigeria, where the jobless rate is consistently high. Businesses and users alike might gain from the app's user-friendly layout, which makes it simple to publish jobs. Post jobs and submit resumes. The foundation of the program is the SVM algorithm, which searches job ads and user profiles for appropriate matches depending on parameters like education, experience, and the kind of role. This system learns from user interactions and comments to produce even better matches than job boards, which have significantly lower prediction accuracy. We develop secure and scalable applications using front-end and back-end methodologies with React Native and Node.js. This article outlines the system architecture, algorithmic implementation, and first testing results, illustrating how machine learning might transform the employment sector in poor countries such as Nigeria.
Cite This Paper
Akpovoke Okoro, Gracious C. Omede, Franklin O. Okorodudu, "Development of a Mobile Application for Employment Opportunities Matching in Nigeria Using the SVM Model", International Journal of Education and Management Engineering (IJEME), Vol.15, No.4, pp. 1-11, 2025. DOI:10.5815/ijeme.2025.04.01
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