CONTENT FILTER BASED MOVIE RECOMMENDATION SYSTEM USING AI AND ML

Abstract: Recommendation system refers to the system which, dependent on the particular data set, provides users with recommendations for certain resources, such as books, movies, songs and so forth. Generally speaking, movie recommendation system usually suggests films which the User would love to watch due to particular attributes of the User, as well as previously accumulated data. Recommendation systems are very beneficial for companies which collect their data from a large number of customers and need to provide them with the most appropriate recommendations possible. Several aspects can be considered when building a movie recommendation system, such as the movie genre, the actors, its plot and even the director. Recommendation systems can offer movies based on a single aspect or several combined ones. The recommended system used in our paper is constructed based on the tags generated from the combinations of the film genre, actors and description which may be interesting for the User to watch. We decided to apply Content-based Filtering approach in our work.

Keywords: Movie Recommendation Systems, Content-Based Filtering, Movie recommendation, ai and machine learning project.