WorkNearU with CareerPath: An Integrated Job Search and Machine Learning Based Career Recommendation System Using Decision Tree Algorithm

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Authors: Pragati Salunke, Kasturi N. Patil, Maaria I. Shaikh
Cited by: 0

Abstract

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.

Fields of Study & Subjects

Recommender Systems and Techniques AI and HR Technologies Information Retrieval and Search Behavior

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
3 March 2026
Language
EN