HeteroMF: recommendation in heterogeneous information networks using context dependent factor models

With the growing amount of information available online, recommender systems are starting to provide a viable alternative and complement to search engines, in helping users to find objects of interest. Methods based on Matrix Factorization (MF) models are the state-of-the-art in recommender systems. The input to MF is user feedback, in th...More