Information Filtering Using the Riemannian SVD (R-SVD)

Matrix factorization is one of the most popular techniques for prediction problems in the fields of intelligent systems and data mining. It has shown its effectiveness in many real-world applications such as recommender systems. As a collaborative ...

We describe Nonnegative Double Singular Value Decomposition (NNDSVD), a new method designed to enhance the initialization stage of nonnegative matrix factorization (NMF). NNDSVD can readily be combined with existing NMF algorithms. The basic algorithm ...

RAAWS: In this paper we will examine the use of a matrix factorization technique called Singular Value Decomposition (SVD) in Item-Based Collaborative Filtering. After a brief introduction to SVD and some of its previous applications in Recommender ...