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

news2024/11/13 16:48:43

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, 生成,拥堵预测,定价预测,气象预测,轨迹生成,预测,异常检测,信控优化等

ADS track中有2个session中与时空数据(城市计算)紧密相关:Spatiotemporal Applications 与 Urban Mobility,还有一些其余session中有一些做的时空数据任务。

KDD 2024 时空数据(Spatial-temporal) ADS论文总结
Spatiotemporal Applications

  1. Transportation Marketplace Rate Forecast Using Signature Transform
  2. MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer Recharge
  3. Diffusion Model-based Mobile Traffic Generation with Open Data for Network Planning and Optimization
  4. LaDe: The First Comprehensive Last-mile Express Dataset from Industry
  5. UrbanGPT: Spatio-Temporal Large Language Models
  6. Spatio-Temporal Consistency Enhanced Differential Network for Interpretable Indoor Temperature Prediction
  7. Weather Knows What Will Occur: Urban Public Nuisance Events Prediction and Control with Meteorological Assistance

Urban Mobility

  1. Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction
  2. TrajRecovery: An Efficient Vehicle Trajectory Recovery Framework based on Urban-Scale Traffic Camera Records
  3. DuMapNet: An End-to-End Vectorization System for City-Scale Lane-Level Map Generation
  4. An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems
  5. FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction
  6. PEMBOT: Pareto-Ensembled Multi-task Boosted Trees

其他

  1. FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting

🌟【紧跟前沿】“时空探索之旅”与你一起探索时空奥秘!🚀
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Spatiotemporal Applications

1. Transportation Marketplace Rate Forecast Using Signature Transform

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671637

链接https://arxiv.org/abs/2401.04857

作者:Haotian Gu (University of California, Berkeley); Xin Guo (Worldwide Operations Research Science, Amazon.com Inc., University of California, Berkeley); Timothy L. Jacobs (Worldwide Operations Research Science, Amazon.com Inc.); Philip Kaminsky (Worldwide Operations Research Science, Amazon.com Inc., University of California, Berkeley); Xinyu Li (University of California, Berkeley)

关键词:运价预测

2. MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer Recharge

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671533

链接https://arxiv.org/abs/2407.01005

作者:Yuning Chen (University of California, Merced); Kang Yang (University of California, Merced); Zhiyu An (University of California, Merced); Brady Holder (University of California, Agriculture and Natural Resources); Luke Paloutzian (University of California, Agriculture and Natural Resources); Khaled M. Bali (University of California, Agriculture and Natural Resources); Wan Du (University of California, Merced)

关键词:时序预测,因果学习,模型预测控制

MARLP

3. Diffusion Model-based Mobile Traffic Generation with Open Data for Network Planning and Optimization

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671544

作者:Haoye Chai (Department of Electronic Engineering, BNRist, Tsinghua University); Tao Jiang (Research Center of 6G Mobile Communications, School of Cyber Science and Engineering, Huazhong University of Science and Technology); Li Yu (Chinamobile Research Institute)

关键词:交通数据生成,扩散模型,卫星图像

OpenDiff

4. LaDe: The First Comprehensive Last-mile Express Dataset from Industry

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671548

链接https://arxiv.org/abs/2306.10675

代码https://github.com/wenhaomin/LaDe

作者:Lixia Wu (Cainiao Network); Haomin Wen (School of Computer and Information Technology, Beijing Jiaotong University, Cainiao Network); Haoyuan Hu (Cainiao Network); Xiaowei Mao (School of Computer and Information Technology, Beijing Jiaotong University, Cainiao Network); Yutong Xia (National University of Singapore); Ergang Shan (Cainiao Network); Jianbin Zheng (Artificial Intelligence Department, Cainiao Network); Junhong Lou (Cainiao Network); Yuxuan Liang (Hong Kong University of Science and Technology (Guangzhou)); Liuqing Yang (Hong Kong University of Science and Technology (Guangzhou)); Roger Zimmermann (National University of Singapore); Youfang Lin (School of Computer and Information Technology, Beijing Jiaotong Univercity); Huaiyu Wan (School of Computer and Information Technology, Beijing Jiaotong University)

关键词:物流数据集,最后一公里配送

LaDe

5. UrbanGPT: Spatio-Temporal Large Language Models

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671578

链接https://arxiv.org/abs/2403.00813

代码https://github.com/HKUDS/UrbanGPT

作者:Zhonghang Li (South China University of Technology, The University of Hong Kong); Lianghao Xia (The University of Hong Kong); Jiabin Tang (The University of Hong Kong); Yong Xu (South China University of Technology); Lei Shi (Baidu Inc.); Long Xia (Baidu Inc.); Dawei Yin (Baidu Inc.); Chao Huang (The University of Hong Kong)

关键词:交通预测,大模型

备注:没有部署的ADS

UrbanGPT

6. Spatio-Temporal Consistency Enhanced Differential Network for Interpretable Indoor Temperature Prediction

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671608

作者:Dekang Qi (Southwest Jiaotong University, JD iCity, JD Technology); Xiuwen Yi (JD iCity, JD Technology, JD Intelligent Cities Research); Chengjie Guo (Xidian University); Yanyong Huang (Southwestern University of Finance and Economics); Junbo Zhang (JD iCity, JD Technology, JD Intelligent Cities Research); Tianrui Li (Southwest Jiaotong University); Yu Zheng (JD iCity, JD Technology, JD Intelligent Cities Research)

关键词:室内温度预测,可解释性预测,时空一致性

CONST

7. Weather Knows What Will Occur: Urban Public Nuisance Events Prediction and Control with Meteorological Assistance

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671639

作者:Yi Xie (Fudan University); Tianyu Qiu (Fudan University); Yun Xiong (Fudan University); Xiuqi Huang (Shanghai Jiaotong University); Xiaofeng Gao (Shanghai Jiao Tong University); Chao Chen (Sorbonne Université – Faculté des Sciences (Paris VI)); Qiang Wang (Shanghai Center for Meteorological Disaster Prevention Technology); Haihong Li (Shanghai Center for Meteorological Disaster Prevention Technology)

关键词:气象辅助的城市事件预测

ST-T3

Urban Mobility

8. Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction

链接https://arxiv.org/abs/2406.12923

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671507

作者:Wenzhao Jiang (The Hong Kong University of Science and Technology (Guangzhou)); Jindong Han (The Hong Kong University of Science and Technology); Hao Liu (The Hong Kong University of Science and Technology (Guangzhou), The Hong Kong University of Science and Technology); Tao Tao (Didichuxing Co. Ltd); Naiqiang Tan (Didichuxing Co. Ltd); Hui Xiong (The Hong Kong University of Science and Technology (Guangzhou), The Hong Kong University of Science and Technology)

关键词:拥堵预测,混合专家系统

CP-MoE

9. TrajRecovery: An Efficient Vehicle Trajectory Recovery Framework based on Urban-Scale Traffic Camera Records

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671558

作者:Dongen Wu (Zhejiang University); Ziquan Fang (Zhejiang University); Qichen Sun (Zhejiang University); Lu Chen (Zhejiang University); Haiyang Hu (Zhejiang University); Fei Wang (Zhejiang University); Yunjun Gao (Zhejiang University)

关键词:轨迹恢复

10. DuMapNet: An End-to-End Vectorization System for City-Scale Lane-Level Map Generation

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671579

链接https://arxiv.org/abs/2406.14255

代码https://github.com/XiyanLiu/DuMapNet

作者:Deguo Xia (Tsinghua University, Baidu Inc.); Weiming Zhang (Baidu Inc.); Xiyan Liu (Baidu Inc.); Wei Zhang (Baidu Inc.); Chenting Gong (Baidu Inc.); Jizhou Huang (Baidu Inc.); Mengmeng Yang (Tsinghua University); Diange Yang (Tsinghua University)

关键词:城市车道级别地图生成

DuMapNet

11. An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671606

链接https://arxiv.org/abs/2408.07327

作者:Taeyoung Yun (KAIST); Kanghoon Lee (KAIST); Sujin Yun (KAIST); Ilmyung Kim (Korea Telecom); Won-Woo Jung (Korea Telecom); Min-Cheol Kwon (Korea Telecom); Kyujin Choi (Korea Telecom); Yoohyeon Lee (Korea Telecom); Jinkyoo Park (KAIST)

关键词:交通灯,元学习,黑盒优化

12. FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction

链接https://zhouzimu.github.io/paper/kdd24-yang.pdf

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671613

代码https://github.com/LarryHawkingYoung/KDD2024_FedGTP

作者:Linghua Yang (SKLCCSE Lab, Beihang University); Wantong Chen (SKLCCSE Lab, Beihang University); Xiaoxi He (Faculty of Science and Technology, University of Macau); Shuyue Wei (SKLCCSE Lab, Beihang University); Yi Xu (SKLCCSE Lab, Institute of Artificial Intelligence, Beihang University); Zimu Zhou (School of Data Science, City University of Hong Kong); Yongxin Tong (SKLCCSE Lab, Beihang University)

关键词:交通预测,联邦学习

image-20240821172213246

13. PEMBOT: Pareto-Ensembled Multi-task Boosted Trees

链接https://www.amazon.science/publications/pembot-pareto-ensembled-multi-task-boosted-trees

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671619

作者:Gokul Swamy (International Machine Learning, Amazon); Anoop Saladi (International Machine Learning, Amazon); Arunita Das (International Machine Learning, Amazon); Shobhit Niranjan (International Machine Learning, Amazon)

关键词:帕累托最优,多任务

其他

14. FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting

链接https://arxiv.org/abs/2402.05823

ACM链接https://dl.acm.org/doi/abs/10.1145/3637528.3671509

作者:Ziqing Ma (DAMO Academy, Alibaba Group); Wenwei Wang (DAMO Academy, Alibaba Group); Tian Zhou (DAMO Academy, Alibaba Group); Chao Chen (DAMO Academy, Central South University); Bingqing Peng (DAMO Academy, Alibaba Group); Liang Sun (DAMO Academy, Alibaba Group); Rong Jin (DAMO Academy, Alibaba Group)

关键词:太阳能预测,模态聚合,向量量化,零样本

FusionSF

相关链接

; Bingqing Peng (DAMO Academy, Alibaba Group); Liang Sun (DAMO Academy, Alibaba Group); Rong Jin (DAMO Academy, Alibaba Group)

关键词:太阳能预测,模态聚合,向量量化,零样本

[外链图片转存中…(img-n0idp4l1-1725679952235)]

相关链接

KDD 2024 Applied Data Science Paperhttps://kdd2024.kdd.org/applied-data-science-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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