Content-Based Filtering Using K-Nearest Neighbor

The purpose of recommendation system is to guide to user, drew on their preferences. This saves consumers to take moment to browse on web for films where millions of films accessible on web. Film based on one or more attribute or mixture of two combinations of categories of films (comedy, action) is proposed by system. In this article, recommendation process constructed the types of films categories, directors, IMDB rating or stars that consumer may decide to view. The methodology used it to accomplish this by filtering technique using KNN (K-Nearest Neighbor) Algorithm. It predicts user’s like or dislike about movie based on different parameters like genres categories, movie titles, imdb ratings. Proposed system using Movie_meta data from Kaggle and data analysis done using python.