A kernel-based approach to exploiting interaction-networks in heterogeneous information sources for improved recommender systems
Oluwasanmi O. Koyejo, Joydeep Ghosh · 2011
Pairwise interaction networks capture inter-user dependencies (e.g. social networks) and inter-item dependencies (e.g item categories) that provide insight into user and item behavior. It is often assumed that such interaction information is informative for preference prediction. This may not be the case, as the some of the observed interactions may not be correlated with the preferences, and their use may negatively impact performance by introducing undesired noise.