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Abstract

A recommendation system is a system based on some data set that provides users with recommendations for certain tools such as books, films, songs, etc. Generally, film recommendation systems predict what movies a consumer will like based on the attributes present in previously liked films. These recommendation systems help organisations that collect data from large amounts of consumers and want to provide the best possible recommendations efficiently. Other considerations can be taken into account when creating a film recommendation system, such as the type of the film, the actors involved in it or even the film director. The proposed paper studies and reviews w the techniques used for recommendation of movies and which among them is best and based on the result proposed our own architecture for the hybrid recommendation system. This paper includes details of implemented model, its architecture and methodology. The research paper also defines how our proposed model is robust, efficient, and effective in working with good performance in turn returning best result.

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