EIGENREC: An Efficient and Scalable Latent Factor Family for Top-N Recommendation

@article{Nikolakopoulos2015EIGENRECAE,
  title={EIGENREC: An Efficient and Scalable Latent Factor Family for Top-N Recommendation},
  author={Athanasios N. Nikolakopoulos and Vassilis Kalantzis and John D. Garofalakis},
  journal={ArXiv},
  year={2015},
  volume={abs/1511.06033}
}
Sparsity presents one of the major challenges of Collaborative Filtering. Graph-based methods are known to alleviate its effects, however their use is often computationally prohibitive; Latent-Factor methods, on the other hand, present a reasonable and viable alternative. In this paper, we introduce EigenRec; a versatile and efficient Latent-Factor framework for Top-N Recommendations, that generalizes the well-known PureSVD algorithm (a) providing intuition about its inner structure, (b) paving… Expand
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