Publications (4)
Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks
Yufeng Zhang, Xueli Yu, Zeyu Cui +3
Text classification is fundamental in natural language processing (NLP), and Graph Neural Networks (GNN) are recently applied in this task. However, the existing graph-based works…
TFNet: Multi-Semantic Feature Interaction for CTR Prediction
Shu Wu, Feng Yu, Xueli Yu +5
The CTR (Click-Through Rate) prediction plays a central role in the domain of computational advertising and recommender systems. There exists several kinds of methods proposed in t…
Dynamic Graph Neural Networks for Sequential Recommendation
Mengqi Zhang, Shu Wu, Xueli Yu +2
Modeling user preference from his historical sequences is one of the core problems of sequential recommendation. Existing methods in this field are widely distributed from conventi…
Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval
Xueli Yu, Weizhi Xu, Zeyu Cui +2
The ad-hoc retrieval task is to rank related documents given a query and a document collection. A series of deep learning based approaches have been proposed to solve such problem…