Abstract:
Recommender system applies discovery
technique to support online users find desired
products and services, etc. Recommender system
technologies are needed that people can quickly
produce high quality recommendations, even for
very large-scale problems. To address these
issues, this system implements movie
recommender system using item-based
collaborative filtering method.This system
calculates prediction values to show the
recommending movies.Therefore, to prove these
values are the best quality results of
recommending movies system and to show most
likely movies for active user, this system measures
average absolute deviation between a predicted
rating and the user’s actual rating of a movie
using MAE. Then, user requests ratings to the
movies and this system calculates item-item
similarity over movies. After that, this system
predicts and recommends movies to the active
user again.
