MOVIE RECOMMENDATION SYSTEM USING COMBINATION OF CONTENT-BASED AND COLLABORATIVE APPROACHES

Abstract

Recommendation systems have made discovering the things simple that one need. Movie recommendation systems target helping movies devotees by recommending what movies to observe without having to go through the long process of choosing from a large set of movies that go up to thousands and millions that is time-consuming and confusing. This research aims to lessen human exertion by proposing motion pictures dependent on the client's advantages. To handle such problems, a model is introduced that combines both content-based and collaborative approaches. It will give logically express results contrasted with various frameworks that depend on a content-based approach. Content-based proposal frameworks are compelled to individuals, these frameworks don't endorse things out of the container, along these lines restricting your decision to investigate more. In short, the proposed model focus on a framework that is able to address the issues of existing approaches.