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[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.
  • Classification : 68T07, 68T09, Machine Learning
  • Format : Online Talk on Zoom
  • Author(s) :
    • Malim Muhammad (Universitas Gadjah Mada)
    • Dedi Rosadi (Universitas Gadjah Mada)
    • Danardono Danardono (Universitas Gadjah Mada)