Peng Dai

Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation

2021 · arXiv (Cornell University)

Session-based recommendation plays a central role in a wide spectrum of online applications, ranging from e-commerce to online advertising services. However, the majority of existing session-based recommendation techniques (e.g., attention-based recurrent network or graph neural …

Graph Meta Network for Multi-Behavior Recommendation

2021

Modern recommender systems often embed users and items into low-dimensional latent representations, based on their observed interactions. In practical recommendation scenarios, users often exhibit various intents which drive them to interact with items with multiple …

Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

Accurate user and item embedding learning is crucial for modern recommender systems. However, most existing recommendation techniques have thus far focused on modeling users' preferences over singular type of user-item interactions. Many practical recommendation scenarios …

Knowledge-aware Coupled Graph Neural Network for Social Recommendation

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

Social recommendation task aims to predict users' preferences over items with the incorporation of social connections among users, so as to alleviate the sparse issue of collaborative filtering. While many recent efforts show the effectiveness …