31 citations · 70 across the 3 of their papers we have counts for
4 papers
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…
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…
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…