Machine Learning and Natural Language Processing based Personality prediction system via cv analysis

Abstract

Organizations are depending more and more on automated tools to expedite the hiring process in the digital age. Conventional resume screening techniques sometimes ignore fundamental personality factors that affect effectiveness in the workplace in favor of concentrating largely on skills and experience. This study introduces a novel Personality Prediction System that uses machine learning and natural language processing (NLP) to evaluate resumes and determine personality traits from language content, structure, and trends. Our methodology extracts personality insights straight from professional papers, guaranteeing an objective and contextually appropriate assessment, in contrast to traditional methods that rely on selfreported tests or social media analysis. By connecting textual and structural elements to well-known psychological models, including the Big Five Personality Traits, the suggested model gives recruiters a more comprehensive picture of applicants. This paper addresses potential biases and ethical issues in AI-driven hiring while examining feature extraction, classification algorithms, and data pretreatment strategies. The technology can predict personality traits with promising accuracy, according to experimental data, opening the door to more equitable and effective talent acquisition.