Resume Analyser and Job RecommendationSystem Based on NLP
Gautam Jaiswal, Aryan Uttam, Devesh Dhar Dubey, Pawan Kumar Mall
Abstract
The Resume Analyser is a streamlit-based web app that is used to analyse resumes which are in PDF format to extract information from it using different NLP techniques. We have proposed a hybrid system which includes BERT for Name entity recognition and NLP pipeline to streamline the workflow. Our hybrid system excels in extracting key information from the resumes which include skills, experiences, and qualifications etc. This enables a more state of the art performance, achieving higher accuracy and faster execution time. SP ACY's advanced linguistic features empower the system to discern not only the explicit qualifications but also the implicit nuances that playa crucial role in candidate-job alignment. It returns a resume score based on the presence of key elements such as a Declaration, qualifications, Experience etc. It also suggests jobs and internships based on the analysis of the resume and also helps in filtering resumes. This analyzer reduces the need for people to manually check their resumes. This analyzer works using natural language processing and text mining to deduce information from the resume. Finally, we were able to create such a hybrid model whose efficiency was approximately 95% and was able to perform its job on many different structures of resumes very efficiently.