Identifying representative users in matrix factorization-based recommender systems: application to solving the content-less new item cold-start problem
Matrix factorization has proven to be one of the most accurate recommendation approaches.
However, it faces one major shortcoming: the latent features that result from the factorization …
However, it faces one major shortcoming: the latent features that result from the factorization …
Matrix factorization and contrast analysis techniques for recommendation
M Aleksandrova - 2017 - theses.hal.science
In many application areas, data elements can be high-dimensional. This raises the problem
of dimensionality reduction. The dimensionality reduction techniques can be classified …
of dimensionality reduction. The dimensionality reduction techniques can be classified …