An Efficient Movie Recommender Engine: Application of Artificial Intelligence
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Abstract
A recommendation system is a system that provides suggestions to users for certain resources like
books, movies, songs, etc., based on some data set. Movie recommendation systems usually predict
what movies a user will like based on the attributes present in previously liked movies. Such
recommendation systems are beneficial for organizations that collect data from large amounts of
customers and wish to effectively provide the best suggestions possible. A lot of factors can be
considered while designing a movie recommendation system like the genre of the movie, actors
present in it or even the director of the movie. The systems can recommend movies based on one or a
combination of two or more attributes. In this paper, the recommendation system has been built on the
type of genres that the user might prefer to watch. The approach adopted to do so is content-based
filtering using genre correlation. The dataset used for the system is Movie Lens dataset
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