79 citations · 119 across the 6 of their papers we have counts for
4 papers · 1 filter
AIGQ: An End-to-End Hybrid Generative Architecture for E-commerce Query Recommendation
Jingcao Xu, Jianyun Zou, Renkai Yang +3
Pre-search query recommendation, widely known as HintQ on Taobao's homepage, plays a vital role in intent capture and demand discovery, yet traditional methods suffer from shallow…
PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation
Ziyang Liu, Chaokun Wang, Jingcao Xu +5
Recommender systems play a crucial role in addressing the issue of information overload by delivering personalized recommendations to users. In recent years, there has been a growi…
Instant Representation Learning for Recommendation over Large Dynamic Graphs
Cheng Wu, Chaokun Wang, Jingcao Xu +7
Recommender systems are able to learn user preferences based on user and item representations via their historical behaviors. To improve representation learning, recent recommendat…
Multi-behavior Self-supervised Learning for Recommendation
Jingcao Xu, Chaokun Wang, Cheng Wu +6
Modern recommender systems often deal with a variety of user interactions, e.g., click, forward, purchase, etc., which requires the underlying recommender engines to fully understa…