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Interest-Based Career Domain Recommender Using Personality Profiling

Abstract

This work presents an Interest-Based Career Domain Recommender System that helps students choose suitable career paths through personality and interest analysis. The system uses the Big Five Personality Traits (OCEAN) alongwith dynamic questionnaire to provide personalized career suggestions. A rule-based and AI-supported recommendation engine matches student traits with relevant career domains. The system also offers career road maps, curated resources, and chatbot support to guide students further. With an adaptive feedback mechanism, recommendations improve over time. Overall, the system aims to reduce career confusion, improve decision-making, and provide a scalable solution for educational institutions

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