Carrer Compass: An Enhanced Job Recommendation System Using NLP, Machine Learning and Technical Assessment

Authors

  • Chandana H M Assistant Professor, Dept. of CSE, Malnad College of Engineering, Hassan, Karnataka, India. Author
  • Sunitha P UG Scholar, Dept. of CSE, Malnad College of Engineering, Hassan, Karnataka, India. Author
  • Sumanth B J UG Scholar, Dept. of CSE, Malnad College of Engineering, Hassan, Karnataka, India. Author
  • Suhas H UG Scholar, Dept. of CSE, Malnad College of Engineering, Hassan, Karnataka, India. Author
  • Raksha D UG Scholar, Dept. of CSE, Malnad College of Engineering, Hassan, Karnataka, India. Author

DOI:

https://doi.org/10.47392/IRJAEH.2025.0629

Keywords:

Job Recommendation, NLP, Machine Learning, Resume Parsing, Technical Test, Career Guidance

Abstract

In today’s digital era, finding the right job that aligns with a candidate’s skills, interests, and qualifications remains a major challenge. Traditional job portals rely on keyword matching, often leading to irrelevant recommendations. Career Compass introduces an enhanced job recommendation system leveraging Natural Language Processing (NLP) and Machine Learning (ML) to improve resume–job alignment. Additionally, it integrates a Technical Test Module that evaluates a candidate’s practical knowledge through multiple-choice questions and coding challenges. This feature allows for personalized recommendations based on both stated skills and verified abilities. Experimental results show improved accuracy and user satisfaction compared to traditional systems.

 

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Published

2025-12-26

How to Cite

Carrer Compass: An Enhanced Job Recommendation System Using NLP, Machine Learning and Technical Assessment . (2025). International Research Journal on Advanced Engineering Hub (IRJAEH), 3(12), 4305-4308. https://doi.org/10.47392/IRJAEH.2025.0629

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