KDD 2024 时空数据(Spatio-temporal) Research论文总结

2024 KDD( ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 知识发现和数据挖掘会议)在2024年8月25日-29日在西班牙巴塞罗那举行。

本文总结了KDD2024有关时空数据(Spatial-temporal) 的相关论文,如有疏漏,欢迎大家补充。

时空数据Topic:时空(交通)预测,插补,气象预测,轨迹生成,预测,异常检测,信控优化等

Research track中有3个session中与时空数据(城市计算)紧密相关:Urban data Ⅰ,Ⅱ 与 spatio-temporal data,还有一些其余session中有一些做的时空数据任务。

Urban data Ⅰ

  1. Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
  2. CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Control
  3. CrossLight: Offline-to-Online Reinforcement Learning for Cross-City Traffic Signal Control
  4. Online Preference Weight Estimation Algorithm with Vanishing Regret for Car-Hailing in Road Network
  5. Rethinking Order Dispatching in Online Ride-Hailing Platforms
  6. STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts
  7. UniST: A Prompt-empowered Universal Model for Urban Spatio-temporal Prediction

Urban Data II

  1. ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model
  2. Communication-efficient Multi-service Mobile Traffic Prediction by Leveraging Cross-service Correlations
  3. Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks
  4. ITPNet: Towards Instantaneous Trajectory Prediction for Autonomous Driving
  5. Profiling Urban Streets: A Semi-Supervised Prediction Model Based on Street View Imagery and Spatial Topology
  6. Physics-informed Neural ODE for Post-disaster Mobility Recovery
  7. DiffCrime: A Multimodal Conditional Diffusion Model for Crime Risk Map Inference

Spatio-temporal Data

  1. Self-consistent Deep Geometric Learning for Heterogeneous Multi-source Spatial Point Data Prediction
  2. MulSTE: A Multi-view Spatio-temporal Learning Framework with Heterogeneous Event Fusion for Demand-supply Prediction
  3. Long-Term Vessel Trajectory Imputation with Physics-Guided Diffusion Probabilistic Model
  4. RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data
  5. Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting
  6. ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation
  7. Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks
  8. DyPS: Dynamic Parameter Sharing in Multi-Agent Reinforcement Learning for Spatio-Temporal Resource Allocation
  9. STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning
  10. Multi-Scale Detection of Anomalous Spatio-Temporal Trajectories in Evolving Trajectory Datasets
  11. ReFound: Crafting a Foundation Model for Urban Region Understanding upon Language and Visual Foundations
  12. Where Have You Been? A Study of Privacy Risk for Point-of-Interest Recommendation
  13. ROTAN: A Rotation-based Temporal Attention Network for Time-Specific Next POI Recommendation
  14. Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations

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Urban data Ⅰ

1. Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization

链接https://arxiv.org/abs/2402.16891

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3672040

代码https://github.com/FeiLiu36/MTNCO

作者:Fei Liu (City University of Hong Kong); Xi Lin (City University of Hong Kong); Zhenkun Wang (Southern University of Science and Technology); Qingfu Zhang (City University of Hong Kong); Tong Xialiang (Huawei Technologies Ltd.); Mingxuan Yuan (Huawei Technologies Ltd.)

关键词:供应链管理,零样本

2. CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Control

链接https://arxiv.org/abs/2405.17152

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671998

代码https://github.com/bonaldli/CoSLight

作者:Jingqing Ruan (Institute of Automation, Chinese Academy of Science, Chinese Academy of Sciences); Ziyue Li (EWI gGmbH, Sensetime Research); Hua Wei (Arizona State University); Haoyuan Jiang (Baidu Inc.); Jiaming Lu (Fudan University); Xuantang Xiong (Institute of Automation, Chinese Academy of Science, Chinese Academy of Sciences); Hangyu Mao (Sensetime Research); Rui Zhao (Sensetime Research, Qing Yuan Research Institute, Shanghai Jiao Tong University)

关键词:信控优化,多智能体强化学习

CoSLight

3. CrossLight: Offline-to-Online Reinforcement Learning for Cross-City Traffic Signal Control

链接https://zhoujingbo.github.io/paper/2024CrossLightKDD.pdf

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671927

作者:Qian Sun (Hong Kong University of Science and Technology); Rui Zha (University of Science and Technology of China); Le Zhang (Baidu Inc.); Jingbo Zhou (Baidu Inc.); Yu Mei (Baidu Inc.); Zhiling Li (Baidu Inc.); Hui Xiong (Hong Kong University of Science and Technology (Guangzhou), Hong Kong University of Science and Technology)

关键词:信控优化,offline2online

CrossLight

4. Online Preference Weight Estimation Algorithm with Vanishing Regret for Car-Hailing in Road Network

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671664

作者:Yucen Gao (Shanghai Jiaotong University); Zhehao Zhu (Shanghai Jiaotong University); Mingqian Ma (Shanghai Jiaotong University); Fei Gao (Didi Global Inc.); Hui Gao (Didi Global Inc.); Yangguang Shi (Shandong University); Xiaofeng Gao (Shanghai Jiao Tong University)

关键词:偏好权重、状态在线学习、消失遗憾、动态确定性马尔可夫决策过程

PWC

5. Rethinking Order Dispatching in Online Ride-Hailing Platforms

ACM链接https://dl.acm.org/doi/10.1145/3637528.3672028

作者:Zhaoxing Yang (Shanghai Jiao Tong University); Haiming Jin (Shanghai Jiao Tong University); Guiyun Fan (Shanghai Jiao Tong University); Min Lu (Didi Chuxing); Yiran Liu (Didi Chuxing); Xinlang Yue (Didi Chuxing); Hao Pan (Didi Chuxing); Zhe Xu (Didi Chuxing); Guobin Wu (Didi Chuxing); Qun Li (Didi Chuxing); Xiaotong Wang (Didi Chuxing); Jiecheng Guo (Didi Chuxing)

关键词:订单调度、网约车、多智能体强化学习

GRC

6. STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671680

作者:Binwu Wang (University of Science and Technology of China); Jiaming Ma(University of Science and Technology of China); Pengkun Wang (Suzhou Institute for Advanced Research, University of Science and Technology of China); Xu Wang (Suzhou Institute for Advanced Research, University of Science and Technology of China); Yudong Zhang (University of Science and Technology of China); Zhengyang Zhou(Suzhou Institute for Advanced Research, University of Science and Technology of China); Yang Wang(University of Science and Technology of China)

关键词:时空OOD,分布偏移,因果图学习

STONE

7. UniST: A Prompt-empowered Universal Model for Urban Spatio-temporal Prediction

链接https://arxiv.org/abs/2402.11838

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671662

代码https://github.com/tsinghua-fib-lab/UniST

作者:Yuan Yuan (Department of Electronic Engineering, BNRist, Tsinghua University); Jingtao Ding (Department of Electronic Engineering, BNRist, Tsinghua University); Jie Feng (Department of Electronic Engineering, BNRist, Tsinghua University); Depeng Jin (Department of Electronic Engineering, BNRist, Tsinghua University); Yong Li (Department of Electronic Engineering, BNRist, Tsinghua University)

关键词:时空(网格)预测,基础模型

UniST

8. ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model

链接https://arxiv.org/abs/2404.15380

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671730

作者:Yuanshao Zhu (Southern University of Science and Technology, City University of Hong Kong); James Jianqiao Yu (University of York); Xiangyu Zhao (City University of Hong Kong); Qidong Liu (Xi’an Jiao Tong University, City University of Hong Kong); Yongchao Ye (City University of Hong Kong); Wei Chen (Hong Kong University of Science and Technology (Guangzhou)); Zijian Zhang (Jilin University, City University of Hong Kong); Xuetao Wei (Southern University of Science and Technology); Yuxuan Liang (The Hong Kong University of Science and Technology (Guangzhou))

关键词:轨迹生成,扩散模型

ControlTraj

9. Communication-efficient Multi-service Mobile Traffic Prediction by Leveraging Cross-service Correlations

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671866

作者:Zhiying Feng (School of Computer Science and Engineering, Sun Yat-sen University); Qiong Wu (Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology); Xu Chen (School of Computer Science and Engineering, Sun Yat-sen University)

关键词:交通预测,跨设备聚合,迁移学习,图卷积

CsASTGCN

10. Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks

链接https://arxiv.org/abs/2308.16818

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671665

作者:Weijia Zhang (HKUST(GZ)); Le Zhang(Baidu Research); Jindong Han (HKUST); Hao Liu (HKUST(GZ), HKUST); Yanjie Fu (Arizona State University); Jingbo Zhou (Baidu Research); Yu Mei(Baidu Inc.); Hui Xiong (HKUST(GZ), HKUST)

关键词:不规则时序交通预测,时空图神经网络

ASeer

11. ITPNet: Towards Instantaneous Trajectory Prediction for Autonomous Driving

链接https://openreview.net/forum?id=mDIXfHvoqH

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671681

作者:Rongqing Li (Beijing Institute of Technology); Changsheng Li (Beijing Institute of Technology); Yuhang Li (Beijing Institute of Technology); Hanjie Li (Beijing Institute of Technology); Yi Chen (Beijing Institute of Technology); Ye Yuan (Beijing Institute of Technology); Guoren Wang (Beijing Institute of Technology)

关键词:轨迹预测,自动驾驶

ITPNet

12. Profiling Urban Streets: A Semi-Supervised Prediction Model Based on Street View Imagery and Spatial Topology

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671918

作者:Meng Chen (School of Software, Shandong University); Zechen Li (School of Software, Shandong University); Weiming Huang (School of Computer Science and Engineering, Nanyang Technological University); Yongshun Gong (School of Software, Shandong University); Yilong Yin (School of Software, Shandong University)

关键词:城市街道剖析,街景图像,街道表征学习,大语言模型

USPM

13. Physics-informed Neural ODE for Post-disaster Mobility Recovery

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3672027

作者:Jiahao Li (Shenzhen International Graduate School, Tsinghua University); Huandong Wang (Department of Electronic Engineering, Tsinghua University); Xinlei Chen (Shenzhen International Graduate School, Tsinghua University, Pengcheng Laboratory)

关键词:移动恢复,物理驱动,神经常微分方程

14. DiffCrime: A Multimodal Conditional Diffusion Model for Crime Risk Map Inference

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671843

作者:Shuliang Wang (Beijing Institute of Technology); Xinyu Pan (Beijing Institute of Technology); Sijie Ruan (Beijing Institute of Technology); Haoyu Han (Beijing Institute of Technology); Ziyu Wang (Beijing Institute of Technology); Hanning Yuan (Beijing Institute of Technology); Jiabao Zhu (Beijing Institute of Technology); Qi Li (Beijing Institute of Technology)

关键词:犯罪风险图推理,多模态,扩散模型

DiffCrime

15. Self-consistent Deep Geometric Learning for Heterogeneous Multi-source Spatial Point Data Prediction

链接https://arxiv.org/abs/2407.00748

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671737

作者:Dazhou Yu (Emory University); Xiaoyun Gong (Emory University); Yun Li (Emory University); Meikang Qiu (Augusta University); Liang Zhao (Emory University)

关键词:空间点数据预测,多源空间数据,几何深度学习

DMSP

16. MulSTE: A Multi-view Spatio-temporal Learning Framework with Heterogeneous Event Fusion for Demand-supply Prediction

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3672030

作者:Li Lin (Southeast University); Zhiqiang Lu (Southeast University); Shuai Wang (Southeast University); Yunhuai Liu (Peking University); Zhiqing Hong (Rutgers University); Haotian Wang (JD Logistics); Shuai Wang (Southeast University)

关键词:供需预测,事件表示,图神经网络,时空图

MulSTE

17. Long-Term Vessel Trajectory Imputation with Physics-Guided Diffusion Probabilistic Model

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3672086

作者:Zhiwen Zhang (School of Artificial Intelligence, Jilin University); Zipei Fan (School of Artificial Intelligence, Jilin University); Zewu Lv (School of Artificial Intelligence, Jilin University); Xuan Song (School of Artificial Intelligence, Jilin University, Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology (SUSTech)); Ryosuke Shibasaki (Research & Development Department, LocationMind Inc.)

关键词:船舶轨迹插补,扩散模型、轨迹嵌入、物理引导

18. RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data

链接https://www.researchgate.net/publication/381321813_RPMixer_Shaking_Up_Time_Series_Forecasting_with_Random_Projections_for_Large_Spatial-Temporal_Data

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671881

作者:Chin-Chia Michael Yeh (Visa Research); Yujie Fan (Visa Research); Xin Dai (Visa Research); Uday Singh Saini (Visa Research); Vivian Lai (Visa Research); Prince Aboagye (Visa Research); Junpeng Wang (Visa Research); Huiyuan Chen (Visa Research); Yan Zheng (Visa Research); Zhongfang Zhuang (Visa Research); Liang Wang (Visa Research); Wei Zhang (Visa Research)

关键词:时空预测,大规模时空图

RPMixer

19. Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting

链接https://arxiv.org/abs/2405.10800

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671961

代码https://github.com/XDZhelheim/HimNet

作者:Zheng Dong (Southern University of Science and Technology); Renhe Jiang (The University of Tokyo); Haotian Gao (The University of Tokyo); Hangchen Liu (Southern University of Science and Technology); Jinliang Deng (Hong Kong University of Science and Technology); Qingsong Wen (Squirrel AI); Xuan Song (Jilin University, Southern University of Science and Technology)

关键词:时空预测,异质性,元参数学习

HimNet

20. ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation

链接https://arxiv.org/abs/2312.01728

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671751

代码https://github.com/tongnie/ImputeFormer

作者:Tong Nie (Tongji University); Guoyang Qin (Tongji University); Wei Ma (The Hong Kong Polytechnic University); Yuewen Mei (Tongji University); Jian Sun (Tongji University)

关键词:时空插补,低秩建模

ImputeFormer

21. Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks

链接https://arxiv.org/abs/2406.08287

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671912

代码https://anonymous.4open.science/r/paper-1430

作者:Wenying Duan (Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction, Nanchang University); Tianxiang Fang (Nanchang University); Hong Rao (School of Software, Nanchang University); Xiaoxi He (Faculty of Science and Technology, University of Macau)

关键词:时空图神经网络,彩票假说

其他

22. DyPS: Dynamic Parameter Sharing in Multi-Agent Reinforcement Learning for Spatio-Temporal Resource Allocation

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3672052

作者:Jingwei Wang (Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University); Qianyue Hao (Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University); Wenzhen Huang (Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University); Xiaochen Fan (Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University); Zhentao Tang (Huawei Noah’s Ark Lab); Bin Wang (Huawei Noah’s Ark Lab); Jianye Hao (Huawei Noah’s Ark Lab, Tianjin University); Yong Li (Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University)

关键词:多智能体强化学习,时空资源分配

DyPS

23. STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning

链接https://arxiv.org/abs/2406.04035

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671922

代码https://github.com/coco0106/MO-STEP

作者:Wei Shao (Data61, CSIRO); Yufan Kang (RMIT University); Ziyan Peng (Xidian University); Xiao Xiao (Xidian University); Lei Wang (Zhejiang University); Yuhui Yang (Xidian University); Flora D. Salim (University of New South Wales)

关键词:早期预测,强化学习

STEMO

24. Multi-Scale Detection of Anomalous Spatio-Temporal Trajectories in Evolving Trajectory Datasets

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671874

作者:Chenhao Wang (University of Electronic Science and Technology of China); Lisi Chen (University of Electronic Science and Technology of China); Shuo Shang (University of Electronic Science and Technology of China); Christian S. Jensen (Aalborg University); Panos Kalnis (King Abdullah University of Science and Technology)

关键词:轨迹异常检测

MST-OATD

25. ReFound: Crafting a Foundation Model for Urban Region Understanding upon Language and Visual Foundations

链接https://zhoujingbo.github.io/paper/2024ReFoundKDD.pdf

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671992

作者:Congxi Xiao (School of Computer Science and Technology, University of Science and Technology of China); Jingbo Zhou (Business Intelligence Lab, Baidu Research); Yixiong Xiao (Business Intelligence Lab, Baidu Research); Jizhou Huang (Baidu Inc.); Hui Xiong (Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou), Department of Computer Science and Engineering, The Hong Kong University of Science and Technology)

关键词:城市区域理解,多模态

ReFound

26. Where Have You Been? A Study of Privacy Risk for Point-of-Interest Recommendation

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671758

代码https://github.com/KunlinChoi/POIPrivacy

作者:Kunlin Cai (University of California, Los Angeles); Jinghuai Zhang (University of California, Los Angeles); Zhiqing Hong (Rutgers University); William Shand (University of California, Los Angeles); Guang Wang (Florida State University); Desheng Zhang (Rutgers University); Jianfeng Chi (Meta); Yuan Tian (University of California, Los Angeles)

关键词:POI推荐,隐私保护,关系推理

27.ROTAN: A Rotation-based Temporal Attention Network for Time-Specific Next POI Recommendation

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.36718098

代码https://github.com/ruiwenfan/ROTAN

作者:Shanshan Feng (Centre for Frontier AI Research, ASTAR, Institute of High Performance Computing, ASTAR); Feiyu Meng (University of Electronic Science and Technology of China); Lisi Chen (University of Electronic Science and Technology of China); Shuo Shang (University of Electronic Science and Technology of China); Yew Soon Ong (Centre for Frontier AI Research, A*STAR, Nanyang Technological University)

关键词:POI推荐,旋转(Rotations)

ROTAN

28. Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations

链接https://arxiv.org/abs/2405.13811

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671743

代码https://github.com/ruiwenfan/ROTAN

作者:Jing Long (The University of Queensland); Guanhua Ye (Beijing University of Posts and Telecommunications); Tong Chen (The University of Queensland); Yang Wang (Hefei University of Technology); Meng Wang (Hefei University of Technology); Hongzhi Yin (The University of Queensland)

关键词:POI推荐,on-device,扩散模型

DCPR

相关链接

KDD 2024 Research Paperhttps://kdd2024.kdd.org/research-track-papers/

🌟【紧跟前沿】“时空探索之旅”与你一起探索时空奥秘!🚀
欢迎大家关注时空探索之旅时空探索之旅在这里插入图片描述

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