Movie Recommender System by using Item-based Collaborative Filtering Algorithm

Recommender system applies discoverytechnique to support online users find desiredproducts and services, etc. Recommender systemtechnologies are needed that people can quicklyproduce high quality recommendations, even forvery large-scale problems. To address theseissues, this system implements movierecommender system using item-basedcollaborative filtering method.This systemcalculates prediction values to show therecommending movies.Therefore, to prove thesevalues are the best quality results ofrecommending movies system and to show mostlikely movies for active user, this system measuresaverage absolute deviation between a predictedrating and the user’s actual rating of a movieusing MAE. Then, user requests ratings to themovies and this system calculates item-itemsimilarity over movies. After that, this systempredicts and recommends movies to the activeuser again