This paper presents a Machine Learning-based system developed for WorkNearU, a platform designed to connect users with nearby job and work opportunities efficiently. Traditional job search methods often lack personalization, location-based filtering, and intelligent matching, resulting in reduced accuracy and increased search time. The proposed model aims to improve job recommendation accuracy and efficiency by analyzing user preferences, skills, and location data using machine learning techniques. The system is developed using modern technologies and evaluated using relevant datasets to measure its performance. Experimental results demonstrate improved recommendation accuracy and better user experience compared to conventional job-search platforms. This work contributes to the practical application of Machine Learning in real-world employment and workforce management solutions.
Salunke et al. (Tue,) studied this question.
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