Selected Publications (# Corresponding Author):

• Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation [paper] [arXiv] [code]

  Jinghao Zhang, Yanqiao Zhu, Qiang Liu, Mengqi Zhang, Shu Wu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), Accepted

  
  

• RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring [paper] [arXiv]

  Qiang Liu, Yingtao Luo, Shu Wu, Zhen Zhang, Xiangnan Yue, Hong Jin and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), Accepted

  
  

• Dynamic Graph Neural Networks for Sequential Recommendation [paper] [code]

  Mengqi Zhang, Shu Wu, Xueli Yu, Qiang Liu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), Accepted

  
  

• DyGCN: Efficient Dynamic Graph Embedding with Graph Convolutional Network [paper] [arXiv] [code]

  Zeyu Cui, Zekun Li, Shu Wu, Xiaoyu Zhang, Qiang Liu, Liang Wang and Mengmeng Ai

  IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), Accepted

  
  

• MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning [paper]

  Yuwei Xia, Mengqi Zhang, Qiang Liu#, Shu Wu and Xiao-Yu Zhang

  Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022

  
  

• Deep Stable Representation Learning on Electronic Health Records [paper] [arXiv]

  Yingtao Luo, Zhaocheng Liu and Qiang Liu#

  IEEE International Conference on Data Mining (ICDM), 2022

  
  

• The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detection [paper] [arXiv]

  Zhixun Li, Dingshuo Chen, Qiang Liu and Shu Wu

  IEEE International Conference on Data Mining (ICDM), 2022

  
  

• GraphDIVE: Graph Classification by Mixture of Diverse Experts [paper] [arXiv]

  Fenyu Hu, Liping Wang, Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan

  International Joint Conference on Artificial Intelligence (IJCAI), 2022

  
  

• Bias Mitigation for Evidence-aware Fake News Detection by Causal Intervention [paper] [code]

  Junfei Wu, Qiang Liu, Weizhi Xu and Shu Wu

  International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2022

  
  

• Evidence-aware Fake News Detection with Graph Neural Networks [paper] [arXiv] [code]

  Weizhi Xu, Junfei Wu, Qiang Liu, Shu Wu and Liang Wang

  The Web Conference (WWW), 2022

  
  

• An Empirical Study of Graph Contrastive Learning [paper] [arXiv] [code]

  Yanqiao Zhu, Yichen Xu, Qiang Liu and Shu Wu

  Advances in Neural Information Processing Systems (NeurIPS), 2021

  
  

• Mining Cross Features for Financial Credit Risk Assessment [paper] [arXiv]

  Qiang Liu, Zhaocheng Liu, Haoli Zhang, Yuntian Chen and Jun Zhu

  ACM International Conference on Information and Knowledge Management (CIKM), 2021

  
  

• Mining Latent Structures for Multimedia Recommendation [paper] [arXiv] [code]

  Jinghao Zhang, Yanqiao Zhu, Qiang Liu#, Shu Wu, Shuhui Wang and Liang Wang

  ACM International Conference on Multimedia (ACMMM), 2021

  
  

• STAN: Spatio-Temporal Attention Network for Next Point-of-Interest Recommendation [paper] [arXiv] [code]

  Yingtao Luo, Qiang Liu# and Zhaocheng Liu

  The Web Conference (WWW), 2021

  
  

• Graph Contrastive Learning with Adaptive Augmentation [paper] [arXiv] [code]

  Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu and Liang Wang

  The Web Conference (WWW), 2021

  
  

• MV-RNN: A Multi-view Recurrent Neural Network for Sequential Recommendation [paper] [arXiv] [code]

  Qiang Cui, Shu Wu, Qiang Liu, Wen Zhong and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2020

  
  

• Towards Accurate and Interpretable Sequential Prediction: A CNN & Attention-based Feature Extractor [paper]

  Jingyi Wang, Qiang Liu, Zhaocheng Liu and Shu Wu

  ACM International Conference on Information and Knowledge Management (CIKM), 2019

  
  

• Mining Significant Microblogs for Misinformation Identification: An Attention-based Approach [paper] [arXiv]

  Qiang Liu, Feng Yu, Shu Wu and Liang Wang

  ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2018

  
  

• A Convolutional Approach for Misinformation Identification [paper]

  Feng Yu, Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan

  International Joint Conference on Artificial Intelligence (IJCAI), 2017

  
  

• DeepStyle: Learning User Preferences for Visual Recommendation [paper] [arXiv]

  Qiang Liu, Shu Wu and Liang Wang

  International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2017

  
  

• Multi-behavioral Sequential Prediction with Recurrent Log-bilinear Model [paper] [arXiv]

  Qiang Liu, Shu Wu and Liang Wang

  IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2017

  
  

• Context-aware Sequential Recommendation [paper] [arXiv]

  Qiang Liu, Shu Wu, Diyi Wang, Zhaokang Li and Liang Wang

  IEEE International Conference on Data Mining (ICDM), 2016

  
  

• A Dynamic Recurrent Model for Next Basket Recommendation [paper]

  Feng Yu, Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan

  International ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR), 2016

  
  

• Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts [paper]

  Qiang Liu, Shu Wu, Liang Wang and Tieniu Tan

  AAAI Conference on Artificial Intelligence (AAAI), 2016

  
  

• COT: Contextual Operating Tensor for Context-aware Recommender Systems [paper]

  Qiang Liu, Shu Wu and Liang Wang

  AAAI Conference on Artificial Intelligence (AAAI), 2015