This University Final Year Project (FYP) uses Natural Language Processing (NLP) to automate the parsing of candidate resumes (PDF, DOCX formats), extracts core skills, education, and job roles, and rates them against job descriptions. It features a dashboard for recruiters and an optimizer tool for job seekers.
Core Features & Functions
Resume text extraction & formatting (PDF/Word parser)
Named Entity Recognition (NER) for skill/education extraction
Semantic matching score against job descriptions
Interactive dashboard for candidate ranking and filters
