Personality Prediction System Curriculum Vitae is a M.Tech project topic for Computer Science & Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Personality Prediction System Curriculum Vitae Project Details
| Abstract |
Traditional recruitment processes heavily rely on manual screening of Curriculum Vitae (CV), which is inherently time-consuming, labor-intensive, and prone to subjective bias. To address these inefficiencies, this research project focuses on the development and evaluation of an automated personality prediction system that analyzes candidate CVs using Natural Language Processing (NLP) and Logistic Regression. Grounded in the Big Five personality trait model (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism), the proposed system parses unstructured text from uploaded resumes to extract key behavioral indicators, linguistic patterns, and professional experiences. Additionally, the framework integrates an optional structured questionnaire to complement the textual analysis, providing a multi-dimensional assessment of candidate suitability. By leveraging TF-IDF vectorization
and a trained Logistic Regression classifier, the system categorizes applicants into distinct personality profiles, thereby streamlining the initial stages of talent acquisition. This implementation-oriented research provides comprehensive guidance on feature engineering, text preprocessing pipelines, and classification performance metrics, offering a robust decision-support tool for modern human resource management.
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| Reference Paper |
Personality Prediction System via Curriculum Vitae (CV) Analysis Using Natural Language Processing (NLP) and Logistic Regression. |
| Domain |
Computer Science & Engineering |
| Sub-Domain |
Artificial Intelligence & Machine Learning / Natural Language Processing |
| PDF Download |
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| Get Help |
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