Movie Recommendation System with Sentiment Analysis

Abstract

A recommendation system is a system that, depending on certain data, makes suggestions to users for specific resources like books, movies, songs, etc. The characteristics of previously loved movies are typically used by movie recommendation systems to anticipate what movies a user would like. Such recommendation systems are advantageous for businesses that gather data from a lot of clients and want to successfully offer the finest recommendations. When creating a movie recommendation system, several variables may be taken into account, including the movie's genre, cast, and even director. The algorithms are capable of recommending movies based on a single attribute or a combination of two or more. The recommendation algorithm in this study is based on the kinds of genres that the user would want to watch. The method used to do this is content-based filtering with genre relevance. Movie Lens set of data is the one processed by the system. R is the data analysis programmed utilized.