Publications

1. Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning.
   WWW 2023. (CCF-A)
   Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, and Liang Wang.
2. Learning Latent Relations for Temporal Knowledge Graph Reasoning.
   ACL 2023. (CCF-A)
   Mengqi Zhang, Yuwei Xia, Qiang Liu, Shu Wu, and Liang Wang.
3. Dynamic Graph Neural Networks for Sequential Recommendation.
   IEEE Transactions on Knowledge and Data Engineering 2023. (CCF-A)
   Mengqi Zhang, Shu Wu, Xueli Yu, Qiang Liu, and Liang Wang.
4. Stage-Aware Hierarchical Attentive Relational Network for Diagnosis Prediction.
   IEEE Transactions on Knowledge and Data Engineering 2023. (CCF-A)
   Liping Wang, Qiang Liu, Mengqi Zhang, Yaxuan Hu, Shu Wu, and Liang Wang.
5. Latent Structure Mining with Contrastive Modality Fusion for Multimedia Recommendation.
   IEEE Transactions on Knowledge and Data Engineering 2022. (CCF-A)
   Jianghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu, and Liang Wang.
6. MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning.
   EMNLP 2022. (CCF-B)
   Yuwei Xia, Mengqi Zhang, Qiang Liu, Shu Wu, and Xiaoyu Zhang.
7. Deep Contrastive Multiview Network Embedding.
   CIKM 2022. (CCF-B)
   Mengqi Zhang, Yanqiao Zhu, Qiang Liu, Shu Wu, and Liang Wang.
8. Personalized Graph Neural Networks with Attention Mechanism for Session-Aware Recommendation.
   IEEE Transactions on Knowledge and Data Engineering 2020. (CCF-A)
   Mengqi Zhang, Shu Wu, Meng Gao, Xin Jiang, Ke Xu, and Liang Wang.
9. Dynamic Graph Collaborative Filtering.
   ICDM 2020. Regular Paper (CCF-B)
   Xiaohan Li*, Mengqi Zhang *, Shu Wu, Zheng Liu, Liang Wang, and Philip S Yu.
10. High-order Hidden Markov Model for Trend Prediction in Financial Time Series.
    Physica A: Statistical Mechanics and its Applications 2019.
    Mengqi Zhang, Xin Jiang, Zehua Fang, Yue Zeng, and Ke Xu.