Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering

  title={Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering},
  author={Alexandros Karatzoglou and Xavier Amatriain and Linas Baltrunas and Nuria Oliver},
Context has been recognized as an important factor to consider in personalized Recommender Systems. However, most model-based Collaborative Filtering approaches such as Matrix Factorization do not provide a straightforward way of integrating context information into the model. In this work, we introduce a Collaborative Filtering method based on Tensor Factorization, a generalization of Matrix Factorization that allows for a flexible and generic integration of contextual information by modeling… CONTINUE READING
Highly Influential
This paper has highly influenced 36 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 595 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 1 time over the past 90 days. VIEW TWEETS


Publications citing this paper.
Showing 1-10 of 370 extracted citations

595 Citations

Citations per Year
Semantic Scholar estimates that this publication has 595 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-2 of 2 references

Similar Papers

Loading similar papers…