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@article{189182,
        author = {Srinivasa Rao P and N Bhoomika Sai and D Harshita and K Chandra Sekhar and V.Ramyasree},
        title = {AI in Recruitment: Personality Prediction through CV Analysis for Smarter Hiring},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {5136-5144},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=189182},
        abstract = {The personality of an individual plays an important role in driving organizational development and improving their self-progress. Identifying a person’s personality traits and professional suitability has traditionally been achieved through interviews or by analyzing their Curriculum Vitae (CV) manually. However, these traditional recruitment methods, which involves shortlisting the candidates manually based on specific requirements of the company, are often time-intensive and prone to bias. This system is designed as an online platform that facilitates candidate registration and conducts personality assessments using Multiple-Choice Question (MCQ) tests. These personality quizzes aim to provide insights into the behavioral and psychological traits of candidates. Simultaneously, the system evaluates professional eligibility by comparing uploaded CVs against a dataset trained using various ML algorithms. The key algorithms involved are Logistic Regression, Random Forest, Support Vector Machine and Decision Tree which were chosen for its strong decision-making capabilities and effectiveness in classification tasks. This ensures that recruitment decisions are data-driven and unbiased.},
        keywords = {Personality Prediction, Machine Learning Models, Big Five Model (OCEAN), Term Frequency Inverse Document Frequency (TF-IDF), Natural Language Processing (NLP).},
        month = {December},
        }