Personalised rating prediction for new users using latent factor models

Abstract

In recent years, personalised recommendations have gained importance in helping users deal with the abundance of information available online. Personalised recommendations are often based on rating predictions, and thus accurate rating prediction is essential for the generation of useful recommendations. Recently, rating prediction algorithms that are based on matrix factorisation have become increasingly popular, due to their high accuracy and scalability. However, these algorithms still deliver inaccurate rating predictions for new users, who submitted only a few ratings.