A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressivel...
Data sparsity is a major problem for collaborative filtering (CF) techniques in recommender systems, especially for new users and items. We observe that, while our target data are...
Weike Pan, Evan Wei Xiang, Nathan Nan Liu, Qiang Y...
Object-oriented system development is wideley recognized as improving productivity and reducing system maintenance costs. However, existing approaches have not su ciently addresse...
Recommender systems — systems that suggest to users in e-commerce sites items that might interest them — adopt a static view of the recommendation process and treat it as a pr...
We propose a novel sequential decision approach to modeling ordinal ratings in collaborative filtering problems. The rating process is assumed to start from the lowest level, eva...