Initially popularized by Amazon.com, recommendation technologies have become widespread over the past several years. However, the types of recommendations available to the users in these recommender systems are typically determined by the vendor and therefore are not flexible. In this paper, we...

This paper describes an approach for incorporating externally specified aggregate ratings informationinto certain types of recommender systems, including two types of collaborating filteringand a hierarchical linear regression model. First, we present a framework for incorporating...

Most of the work on Context-Aware Recommender Systems (CARSes) has focused on demonstrating that the contextual information leads to more accurate recommendations and on developing efficient recommendation algorithms utilizing this additional contextual information. Little work has been done,...

Many successful recommendation approaches rely on the optimization of a single objective function for a single stakeholder (i.e., the customer) based on customer-product interaction records. In this paper, we argue that for two-sided marketplaces such as music streaming platforms, it is more...