Adaptive Preference Modeling via Explicit Indirect Relational Learning for Personalized Fashion Matching

Personalized fashion complementary recommendation requires jointly modeling user preferences and item compatibility under sparse and multimodal data conditions. Existing approaches often capture higher-order relational signals implicitly through graph propagation or rely on direct interaction data,