Neural Reasoning Machines for Recommendation

Abstract

Most of the existing recommendation models are designed based on the principles of learning and matching by learning the user and item embeddings and using learned or designed functions as matching models they try to explore the similarity pattern between users and items for recommendation However recommendation is not only a perceptual matching task but also a cognitive reasoning task because user behaviors are not merely based on item similarity but also based on users careful reasoning about what they need and what they want