Resume Shortlisting Using NLP

Recruitment processes have evolved from manual sorting of the resumes to automation with the integration of Natural Language Processing. The benefits of NLP in hiring new employees are examined in this paper, with a focus on how it might increase candidate selection's effectiveness, objectivity, and fairness. This automated approach streamlines the candidates resume evaluation process. The core steps in the system include parsing resume to text, performing NLP of parsed text, creating a NER (Named Entity Recognition) model and using NER model to calculate P, R and F score to generate final score to sort resume based on final score.