A Machine Learning and NLP Approach for Analyzing Eligibility Based on Resume and CV

Abstract

Today Jobs are curved to consider the wishes of the organization. Ideally, job design is destined to be a tired response to maintain the operational model and hence the functions needed. Every job should serve a purpose and contribute to the interests of business outcomes. All changes within the business should consider the impact on jobs and managers should re-design those jobs to suit. Good jobs may even contribute to motivating and inspiring generations to come. Dangerous job design can fail to make that motivation. Job descriptions are in all probability the foremost necessary employment-related documents for a firm. employment description underpins the utilization contract by commencing what management wants from an employee. They are thus a kind of the premise of all employer-employee interactions leading on to appraisal, development, pay and succession discussions. The application that will be presented will try to solve the above concern by acquiring the CV/Resume and related examination scores for the job description the candidate has applied to and by using Text Extraction Techniques the information extracted will be sent in the backend of the application and use the necessary data extracted and run it on the ML model and compare it with some of the top Resumes, Personality and Technical Knowledge evaluation and provide the candidate with good insights on various aspects. The proposed system will first extract the useful terms by using OCR engines from the scanned PDF of CV/Resume, analyze and split the data into categories like Education Qualifications, Experience, Skills, Projects, Candidate Description etc. And based on the data gathered, an evaluation for a particular job description will be done.