A Survey on Personalized Movie Recommendation System Using Machine Learning

In the era of big data, recommender systems (RS) have emerged as vital information filtering tools, particularly in digital entertainment and e-commerce domains. This survey paper delves into the intricate realm of RS, with a primary focus on movie recommender systems. In an age where the Internet inundates users with unfiltered information, RSs act as indispensable software tools, adept at validating and ranking available options while aligning with user preferences. It meticulously evaluates filtering techniques, including collaborative, content-based, and hybrid methods.