핵심 개념
Intent-aware Recommendation via Disentangled Graph Contrastive Learning (IDCL) enhances recommender systems by disentangling user intents and inferring behavior distributions.
통계
Graph neural networks (GNN) based recommender systems are mainstream.
IDCL substantially improves recommendation performance.
IDCL disentangles user intents and infers behavior distributions.