Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation
Disentangled Cascaded Graph Convolution Networks for Multi-Behavior Recommendation
Multi-behavioral recommender systems have emerged as a solution to address data sparsity and cold-start issues by incorporating auxiliary behaviors alongside target behaviors. However, existing models struggle to accurately capture varying user preferences across different behaviors and fail to account for diverse item preferences within behaviors. Various user preference factors (such …