Resume Inflation System for Improvement of Employability among Graduates

A Resume Inflation System proposed in this research is a progressive, computer-based framework engineered to optimise the personnel recruitment cycle by facilitating hands-free operation and performance review of job seekers’ resumes. In the recruitment cycle, hiring managers are often flooded with numerous resumes from applicants. This large volume of applicants can lead to difficulties in selecting candidates for various positions. However, there is no open-source application that assists in shortlisting resumes for a particular position directly using the job description. This inspires us to introduce a methodology for a resume Inflation system. The resume Inflation system mitigates these issues by introducing the initial review activity, which reduces the time spent on manual screening by up to 80%. This Inflation system employs machine learning models and NLP to proficiently inspect resumes, extract relevant skills, experiences, and qualifications, and match them against specific job descriptions with maximum accuracy. The procedure ensures that the most promising applicants are prioritised for further rounds of evaluation, which enhances the standards of shortlisted applicants and decreases the risk of mismatch. The Resume Inflation System ensures a fairer recruiting procedure and nurtures diversity in the hiring process. This latest application not only saves time but also increases the efficiency and accuracy of candidate selection.