Abstract : Recommendation System are the systems provide suggestions to the user(Recommends the content). Contents like Books, Movies, Smart Phones, Vehicles. While movie recommendation systems suggest the user movies that are based on the previous movie’s attributes liked by the user. These recom- mendation systems are very helpful in companies, websites, stores where the amount of the content is large as well as number of customer (consumer) is huge & content is diverse. Designing such a system lot of factors are considered, mainly the genre of movie, While other factors may include the actors, language, director of the movie. Multiple factors may affect the suggestions, while Some factor might play bigger roles than other based on the user’s history of selection. This paper proposes a system that uses the K-Nearest Neighbors Algorithm, In injunction with Collaborative filtering. The data-set used for this system is TMDB. The data analysis tool used is Python.

| DOI: 10.17148/IARJSET.2021.81251