Publications

(* Indicates corresponding author)

• Yuxiang Guo, Lu Chen, Zhengjie Zhou, Baihua Zheng, Ziquan Fang, Zhikun Zhang, Yuren Mao, and Yunjun Gao.
  CampER: An Effective Framework for Privacy-Aware Deep Entity Resolution.
  Proceedings of the 29th Conference on Knowledge Discovery and Data Mining (KDD), 2023.

• Yuntao Du, Yujia Hu, Zhikun Zhang, Ziquan Fang, Lu Chen, Baihua Zheng, and Yunjun Gao.
  LDPTrace: Locally Differentially Private Trajectory Synthesis.
  Proceedings of the 49th International Conference on Very Large Data Bases (VLDB), 2023.

• 邱林山, 房子荃, 陈璐, 张天明, 李天义.
  面向异质信息网络的双通道协同聚类算法.
  《计算机学报》, 2023.

• Zhihao Zeng, Yuntao Du, Ziquan Fang, Lu Chen, Shiliang Pu, Guodong Chen, Hui Wang, and Yunjun Gao.
  FLBooster: A Unified and Efficient Platform for Federated Learning Acceleration.
  Proceedings of the 39th IEEE International Conference on Data Engineering (ICDE), 2023.

• Ziquan Fang, Shenghao Gong, Lu Chen, Jiachen Xu, Yunjun Gao, and Christian S. Jensen.
  Ghost: A General Framework for High-performance Online Similarity Queries over Distributed Trajectory Streams.
  Proceedings of the ACM International Conference on Management of Data (SIGMOD), 2023.

• Ziquan Fang, Changhao He, Lu Chen, Danlei Hu, Qichen Sun, Linsen Li, and Yunjun Gao.
  A Lightweight Framework for Fast Trajectory Simplification.
  Proceedings of the 39th IEEE International Conference on Data Engineering (ICDE), 2023.

• Yunjun Gao, Yuntao Du, Yujia Hu, Lu Chen, Xinjun Zhu, Ziquan Fang, and Baihua Zheng.
  Self-Guided Learning to Denoise for Robust Recommendation.
  Proceedings of the 45th ACM conference on research and development in Information Retrieval (SIGIR), 2022.

• Yuntao Du, Xinjun Zhu, Lu Chen, Ziquan Fang, and Yunjun Gao.
  MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation.
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.

• 金鹏飞, 常雪芹, 房子荃, 李淼.
  地理社交网络中基于多目标组合优化的空间感知影响力联合最大化.
  《计算机研究与发展》, 2022.

• Ziquan Fang, Yuntao Du, Xinjun Zhu, Danlei Hu, Lu Chen, Yunjun Gao, Christian S. Jensen.
  Spatio-Temporal Trajectory Similarity Learning in Road Networks.
  Proceedings of the 28th Conference on Knowledge Discovery and Data Mining (KDD), 2022.

• Ziquan Fang, Dongen Wu, Lu Pan, Lu Chen, and Yunjun Gao.
  When Transfer Learning Meets Cross-City Urban Flow Prediction: Spatio-Temporal Adaptation Matters.
  Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022.

• Ziquan Fang, Lu Pan, Lu Chen, Yuntao Du, and Yunjun Gao.
  A Multi-source Deep Traffic Prediction Framework over Spatio-Temporal Trajectory Data.
  Proceedings of the 47th International Conference on Very Large Data Bases (VLDB), 2021.

• Ziquan Fang, Yuntao Du, Lu Chen, Yujia Hu, Yunjun Gao, and Gang Chen.
  E2DTC: An End to End Automatic Deep Trajectory Clustering Framework via Self-Training.
  Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021.

• Ziquan Fang, Lu Chen, Yunjun Gao, Lu Pan, and Christian S. Jensen.
  A Hybrid and Efficient Big Trajectory Management System for Offline and Online Analytics.
  The VLDB Journal (VLDBJ), 2021.

• Ziquan Fang, Yunjun Gao, Lu Pan, Lu Chen, Xiaoye Miao, and Christian S. Jensen.
  CoMing: A Real-time Co-Movement Mining System for Streaming Trajectories.
  Proceedings of the ACM International Conference on Management of Data (SIGMOD), 2020.

• Lu Chen, Yunjun Gao, Ziquan Fang, Xiaoye Miao, Christian S. Jensen, and Chenjuan Guo.
  Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories.
  Proceedings of the 45th International Conference on Very Large Data Bases (VLDB), 2019.