Dominating Movie Recommendations: Exploring the Power of AI and Cosine Similarity in Hybrid Systems

EasyChair Preprint 12119

Abstract

This paper delves into the realm of movie recommendations, presenting a hybrid system that combines artificial intelligence (AI) algorithms with cosine similarity measures. We investigate the effectiveness of this approach in enhancing the accuracy and relevance of movie recommendations. Through extensive experimentation, we demonstrate the potential of our hybrid system to outperform traditional recommendation methods, providing users with personalized and engaging movie suggestions.

Keyphrases: Artificial Intelligence, Movie Recommendations, collaborative filtering, content-based filtering, cosine similarity, hybrid systems

@booklet{EasyChair:12119,
  author    = {Basit Abbas},
  title     = {Dominating Movie Recommendations: Exploring the Power of AI and Cosine Similarity in Hybrid Systems},
  howpublished = {EasyChair Preprint 12119},
  year      = {EasyChair, 2024}}