Enhancing Movie Recommendations: AI-Driven Hybrid Systems with Text-to-Number Conversion and Cosine Similarity

Authors

  • Pitter Pack, Jully Jack Department of Computer science, University of Delhi

Keywords:

Movie Recommendations, Artificial Intelligence, Hybrid Systems, Text-to-Number Conversion, Cosine Similarity, Personalization, User Preferences

Abstract

Abstract: This study presents an innovative approach to improving movie recommendation systems through the integration of artificial intelligence (AI), text-to-number conversion, and cosine similarity. The hybrid system aims to enhance the accuracy and relevance of movie suggestions by leveraging both textual information and user preferences. Through extensive experimentation, we demonstrate the effectiveness of our proposed methodology in providing personalized and context-aware recommendations.

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Published

2024-02-10