Resume Analyzer and Skill Enhancement Recommender System
V J Prashanth, Sri Naga Jathin P, Suraj Gopinath, S Udith, C. R. Kavitha
Abstract
The research "Resume Parsing and Job Prediction" mainly deals with prediction of an appropriate job title for a person based on their resume. Due to rapid increase in job applicants, companies find it difficult to manually read every resume as this work requires tremendous amounts of time and effort. Hence the resume parser has gained a lot of importance in recent years. Here we use a custom CNN model to predict the job role suitable for an applicant based on their resume. We also compare the model’s performance with other machine learning models Random Forest and SVM and neural network models like custom CNN and a pre trained BERT model. Job applicants also find it difficult to check how compatible they would be for a job. Hence, we use a word2vec vectorization technique and cosine similarity and find the similarity between the resume and a company’s job description. This application also includes a scoring and a feedback system that provides personalized feedback for the applicant’s resume and scores it based on important contents like their education, skills, experience.