Abstract
Due to ever increasing number of newly released movies, a recommendation system may be of use to majority of cinematography fans. This paper presents an approach to create such a system using existing database containing informations about movies and how they are rated by people. Features describing year of production, cast, director, genres and average rating are being extracted and then used with a kNN classifier to decide how much would someone rate any movie in the database. Based on that rating, a number of not yet seen movies is selected and recommended.
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Frykowska, A., Zbieć, I., Kacperski, P., Vesely, P., Studenicova, A. (2020). Movies Recommendation System. In: Barolli, L., Nishino, H., Miwa, H. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2019. Advances in Intelligent Systems and Computing, vol 1035. Springer, Cham. https://doi.org/10.1007/978-3-030-29035-1_56
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DOI: https://doi.org/10.1007/978-3-030-29035-1_56
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