Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior

@article{Kanagal2012SuperchargingRS,
  title={Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior},
  author={Bhargav Kanagal and Amr Ahmed and S. Pandey and V. Josifovski and Jeffrey Yuan and Lluis Garcia Pueyo},
  journal={ArXiv},
  year={2012},
  volume={abs/1207.0136}
}
Recommender systems based on latent factor models have been effectively used for understanding user interests and predicting future actions. Such models work by projecting the users and items into a smaller dimensional space, thereby clustering similar users and items together and subsequently compute similarity between unknown user-item pairs. When user-item interactions are sparse (sparsity problem) or when new items continuously appear (cold start problem), these models perform poorly. In… Expand
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