Comparative recommender system evaluation: benchmarking recommendation frameworks

@inproceedings{Said2014ComparativeRS,
  title={Comparative recommender system evaluation: benchmarking recommendation frameworks},
  author={A. Said and Alejandro Bellog{\'i}n},
  booktitle={RecSys '14},
  year={2014}
}
  • A. Said, Alejandro Bellogín
  • Published in RecSys '14 2014
  • Computer Science
  • Recommender systems research is often based on comparisons of predictive accuracy: the better the evaluation scores, the better the recommender. [...] Key Method To provide a fair comparison, we have complete control of the evaluation dimensions being benchmarked: dataset, data splitting, evaluation strategies, and metrics. We also include results using the internal evaluation mechanisms of these frameworks. Our analysis points to large differences in recommendation accuracy across frameworks and strategies, i…Expand Abstract
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