Fast context-aware recommendations with factorization machines

  title={Fast context-aware recommendations with factorization machines},
  author={Steffen Rendle and Zeno Gantner and Christoph Freudenthaler and Lars Schmidt-Thieme},
The situation in which a choice is made is an important information for recommender systems. Context-aware recommenders take this information into account to make predictions. So far, the best performing method for context-aware rating prediction in terms of predictive accuracy is Multiverse Recommendation based on the Tucker tensor factorization model. However this method has two drawbacks: (1) its model complexity is exponential in the number of context variables and polynomial in the size of… CONTINUE READING
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