Knowledge-aware Neural Networks with Personalized Feature Referencing for Cold-start Recommendation

no code implementations • 28 Sep 2022 • Xinni Zhang, Yankai Chen, Cuiyun Gao, Qing Liao, Shenglin Zhao, Irwin King

Incorporating knowledge graphs (KGs) as side information in recommendation has recently attracted considerable attention.

Knowledge Graphs

DAGNN: Demand-aware Graph Neural Networks for Session-based Recommendation

no code implementations • 30 May 2021 • Liqi Yang, Linhan Luo, Lifeng Xin, Xiaofeng Zhang, Xinni Zhang

Then, the demand-aware graph neural network is designed to extract session demand graph to learn the demand-aware item embedddings for the later recommendations.

Graph Neural Network Session-Based Recommendations

Probing Negative Sampling Strategies to Learn GraphRepresentations via Unsupervised Contrastive Learning

no code implementations • 13 Apr 2021 • Shiyi Chen, Ziao Wang, Xinni Zhang, Xiaofeng Zhang, Dan Peng

Graph representation learning has long been an important yet challenging task for various real-world applications.

Contrastive Learning Graph Representation Learning

Heterogeneous-Temporal Graph Convolutional Networks: Make the Community Detection Much Better

no code implementations • 23 Sep 2019 • Yaping Zheng, Shiyi Chen, Xinni Zhang, Xiaofeng Zhang, Xiaofei Yang, Di Wang

Community detection has long been an important yet challenging task to analyze complex networks with a focus on detecting topological structures of graph data.

Community Detection