[02329] Improve Error Prediction Using Regularization Model for Movie Recommendation System
Session Time & Room : 3E (Aug.23, 17:40-19:20) @E811
Type : Contributed Talk
Abstract : Currently, most applications (such as Netflix, Spotify, and the others) provide engaging facilities to improve the user’s experience. These applications highly depend on the effectiveness of their recommendation systems. The goal for this paper was to improve error prediction (RMSE and MAE) using Regularization model compared with state-of-art models. The proposed technique obtains a better result than a state-of-art model with an improvement of 0.48% and 1.43% on error prediction using ML-1M dataset, respectively.
