Resume Screening using NLP and LSTM
Sanjana Bharadwaj, Rudra Varun, Potukuchi Sreeram Aditya, Macherla Nikhil, G. Charles Babu
Abstract
Resume screening is the process of determining whether a candidate is qualified for a position based on their education, experience, and other information contained on their resume. Only if the resume of an experienced employee/fresher matches the job description will they be called for an interview. Manual examination of resumes might be a burdensome task. Manually doing it would take a long time. Companies utilize tracking systems to shortlist personnel based on their abilities. The most prevalent reason for rejection is a mismatch between the job role and the applicant's skill set. It is vital for job seekers to understand which job categories they should apply to based on their skill set. This project intends to develop an application that will categorize CVs according to the skills they contain into various job options. As a result, these programs aid job seekers in evaluating what types of positions they are qualified for based on their resume skills. Upgrades in application innovation for misconduct will probably result in higher overall expenditure in this area. This work also strives to make grouping more important by combining multiple classes into larger groups. At last, the analysis has been presented with a wide range of classifiers and new approaches have been suggested.