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Tensor Methods and Recommender Systems
[article]
2018
arXiv
pre-print
A substantial progress in development of new and efficient tensor factorization techniques has led to an extensive research of their applicability in recommender systems field. Tensor-based recommender models push the boundaries of traditional collaborative filtering techniques by taking into account a multifaceted nature of real environments, which allows to produce more accurate, situational (e.g. context-aware, criteria-driven) recommendations. Despite the promising results, tensor-based
arXiv:1603.06038v2
fatcat:yn4ozyphr5hwheignf65j26xsy