Movie Recommender System

Abstract

A Recommendation framework could be a framework that gives suggestions to users for certain assets like movies, motion pictures, web series, etc., based on a few data that system collects from user. The Movie Recommendation System is a web-based application that provides best movie recommendations to users based on their preferences. The system uses data-based filtering techniques to analyze user behavior and generate recommendations based on similar preferences of other users. The system utilizes a large dataset of movies and their attributes such as genre, cast, director, year of release, and ratings to generate recommendations for users. The users can provide their preferences by rating movies they have watched, and the system then generates a list of recommended movies based on their ratings. The Movie Recommendation System is designed to be user-friendly and interactive. Users can browse through the recommended movies, view their details, and even watch trailers of the movies. The system also provides users with the option to add movies to their watchlist or mark them as already watched. The system is beneficial for users who are looking for new movies to watch but are overwhelmed by the vast amount of options available. The personalized recommendations make it easier for users to find movies that they are likely to enjoy, based on their preferences and past behavior.