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Web-based recommendation strategies, known as RS, have become increasingly relevant and widely utilized due to the vast amount of information available online. The demand for personalized and filtered systems continues to grow as a result. Recommendation systems serve as information filtering schemes that address the problem of information overload by extracting crucial insights from immense and continuously generated data. They predict user ratings or preferences for items, aiding in decision-making. This work explores various recommendation systems and algorithms applied specifically to movie recommendations.