When recommenders fail: predicting recommender failure for algorithm selection and combination

@inproceedings{Ekstrand2012WhenRF,
  title={When recommenders fail: predicting recommender failure for algorithm selection and combination},
  author={Michael D. Ekstrand and J. Riedl},
  booktitle={RecSys '12},
  year={2012}
}
Hybrid recommender systems --- systems using multiple algorithms together to improve recommendation quality --- have been well-known for many years and have shown good performance in recent demonstrations such as the NetFlix Prize. Modern hybridization techniques, such as feature-weighted linear stacking, take advantage of the hypothesis that the relative performance of recommenders varies by circumstance and attempt to optimize each item score to maximize the strengths of the component… Expand
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