Resume Screening using NLP

Abstract

Abstract: Presently, we have seen the technology reaching new heights than ever ahead. But each association has a different way of working but for this they need people who have a specific skill set. Selection of the candidate is done on the base of seeing the skill set mentioned in the person's capsule who is applying at the organization. Generally, resumes are sorted manually but, going through the resumes of these people manually is extremely time- consuming and lower effective as there are chances of human intervention error. Hence, we have proposed a design which will sort all the resumes according to the demand of the company and reduce the working time for further recruitment process. In this design we are going to use the technology of Artificial Intelligence and Natural Language Processing. We are going to train the model for recognizing the words which actually define the skill set of the person and demanded by the association by rendering in Python language. The algorithm will work in such a way that when a resume is to be scanned it will search only for the words according to the demand by the company and sort it accordingly. The required resume is shortlisted and the rest are auto rejected by the model. This will give high effectiveness compared to the manual sorting and give produce good results. This will lots of time and work of recruiters. Keywords: Information Retrieval, Natural Language Processing, Resume Parser, Resume Analyzer, Resume Summarisation, cv sorting, e-recruitment, Content-based Recommendation