An end-to-end neighborhood-based interaction model for knowledge-enhanced recommendation
An end-to-end neighborhood-based interaction model for knowledge-enhanced recommendation
This paper studies graph-based recommendation, where an interaction graph is built from historical responses and is leveraged to alleviate data sparsity and cold start problems. We reveal an early summarization problem in previous graph-based models, and propose Neighborhood Interaction (NI) model to capture each neighbor pair (between user-side and item-side) …