Ensemble Learning for Hybrid Music Recommendation

We investigate ensemble learning methods for hybrid music recommenders, combining a social and a content-based recommender algorithm in an initial experiment by applying a simple combination rule to merge recommender results. A first experiment suggests that such a combination can reduce the mean absolute prediction error compared to the used recommenders’ individual errors.