Enhancing Multi-Behavior Recommendation through Behavior-Contextualized Item Preference Modeling

The core message of this paper is to introduce a novel approach, Behavior-Contextualized Item Preference Modeling (BCIPM), for multi-behavior recommendation. The proposed Behavior-Contextualized Item Preference Network (BIPN) discerns and learns users' specific item preferences within each behavior, considering only those preferences relevant to the target behavior for final recommendations, thereby significantly reducing noise from auxiliary behaviors.