AI Resume Screening and Ranking Technology

 The project aims to develop an automated system that efficiently screens job applicants’ resumes.  It ranks candidates based on how relevant their resumes are to a specific job description.  This approach addresses the challenge that manual resume screening is often slow and susceptible to human bias.  By leveraging artificial intelligence, the system helps streamline the recruitment process.  The goal is to quickly shortlist the most suitable candidates, saving recruiters significant time and effort.  The methodology centers around Natural Language Processing (NLP) techniques to analyze resumes.  NLP is used to extract important details such as skills, educational qualifications, and work experience.  The system can handle resumes in various formats, including commonly used PDF and DOCX files.  Once extracted, the resume data is compared against job descriptions to assess compatibility.  Similarity measures such as cosine similarity with TF-IDF vectors are used to perform the initial matching.  For more nuanced understanding, semantic embeddings are employed to capture contextual relationships between terms.  Each candidate receives a match score based on how closely their resume aligns with the job requirements.  The system outputs a ranked list of candidates sorted by their match scores, highlighting the best fits.  Overall, this AI-driven solution enhances recruitment efficiency by reducing manual errors, minimizing bias, and accelerating the hiring process while maintaining objectivity.