SIGMOD 2024 | 时空数据（Spatial-Temporal）和时间序列论文总结

文摘 2024-06-12 12:37 北京

SIGMOD2024于6月9号-6月14号正在智利圣地亚哥举行（Santiago Chile）

本文总结了SIGMOD 2024有关时间序列（time series）,包括时序数据库，查询优化等内容。以及时空数据（spatial-temporal data）的相关论文，主要包含时空时空数据管理，时空数据挖掘，数据库等内容，如有疏漏，欢迎大家补充。笔者对DB了解浅薄，如有表述不当，欢迎大家指正。

SIGMOD24的detailed program中有专门的时空数据的session。

1. Origin-Destination Travel Time Oracle for Map-based Services

链接：https://dl.acm.org/doi/abs/10.1145/3617337

作者：Yan Lin (Beijing Jiaotong University); Huaiyu Wan (Beijing Jiaotong University); Jilin Hu (Aalborg University)*; Shengnan Guo (Beijing Jiaotong University); Bin Yang (Aalborg University); Youfang Lin (Beijing Jiaotong University); Christian S. Jensen (Aalborg University)

关键词：ETA（OD），扩散模型

代码：https://github.com/Logan-Lin/DOT

公众号解读：时空数据学习：本组成果 |【SIGMOD 2024】DOT: 基于扩散模型的OD矩阵行程时间估计

2. Temporal JSON Keyword Search

链接：https://dl.acm.org/doi/abs/10.1145/3654980

作者：Curtis Dyreson (Utah State University)*; Amani Shatnawi (Yarmouk University ); Sourav S Bhowmick (Nanyang Technological University); Vishal Sharma (University of Nevada, Las Vegas)

关键词：时序关键词搜索，JSON

代码：https://github.com/cdyreson/temporalHierarchicalKeywordSearch

3. Proximity Queries on Point Clouds using Rapid Construction Path Oracle

链接：https://dl.acm.org/doi/abs/10.1145/3639261

作者：Yinzhao YAN (Hong Kong University of Science and Technology)*; Raymond Chi-Wing Wong (Hong Kong University of Science and Technology)

关键词：POI最短路径查询，Oracle

4. Optimizing Time Series Queries with Versions

链接：https://dl.acm.org/doi/abs/10.1145/3654962

作者：Rui Kang (Tsinghua University); Shaoxu Song (Tsinghua University)*

关键词：时间序列查询，物联网数据库

5. Hierarchical Cut Labelling – Scaling Up Distance Queries on Road Networks

链接：https://dl.acm.org/doi/abs/10.1145/3626731

作者：Muhammad Farhan (Australian National University)*; Henning Koehler (Massey University); Robert Ohms (Australian National University); Qing Wang (ANU)

关键词：最短路查询，路网，层次划分

6. Nexus: Correlation Discovery over Collections of Spatio-Temporal Tabular Data

链接：https://dl.acm.org/doi/abs/10.1145/3654957

作者：Yue Gong (The University of Chicago)*; Sainyam Galhotra (Cornell University); Raul Castro Fernandez (The University of Chicago)

关键词：数据发现，时空数据，相关性分析，假设生成，表格数据

7. DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks

链接：https://dl.acm.org/doi/abs/10.1145/3626724

作者：Fahao Chen (The University of Aizu); Peng Li (the University of Aizu)*; Celimuge Wu (The University of Electro-Communications)

关键词：动态图，分布式机器学习，图划分

DGC

8. Akane: Perplexity-Guided Time Series Data Cleaning

链接：https://dl.acm.org/doi/abs/10.1145/3654993

作者：Xiaoyu Han (Fudan University)*; Haoran Xiong (Fudan University); Zhenying He (Fudan University); Peng Wang (" Fudan University, China"); Chen Wang (" Tsinghua University, China"); X. Sean Wang (Fudan University)

关键词：时间序列数据清洗

9. Time Series Representation for Visualization in Apache IoTDB

链接：https://dl.acm.org/doi/abs/10.1145/3639290

作者：Lei Rui (Tsinghua University); Xiangdong Huang (Tsinghua University); Shaoxu Song (Tsinghua University)*; Yuyuan Kang (University of Wisconsin-Madison); Chen Wang (Timecho Limited); Jianmin Wang ("Tsinghua University, China")

关键词：时序数据可视化，数据库查询处理

10. MOST: Model-Based Compression with Outlier Storage for Time Series Data

链接：https://dl.acm.org/doi/abs/10.1145/3626737

作者：Zehai Yang (Institute of Computing Technology, CAS & University of Chinese Academy of Sciences); Shimin Chen (Chinese Academy of Sciences)*

关键词：时间序列数据异常存储压缩

公众号解读：时空实验室：SIGMOD 2023 | MOST：基于模型的压缩与离群值存储的时间序列数据

11. Correlation Joins over Time Series Data Streams Utilizing Complementary Dimension Reduction and Transformation

链接：https://dl.acm.org/doi/abs/10.1145/3626722

作者：AmirReza Alizade Nikoo (University of Zürich)*; Sven Helmer (University of Zurich); Michael H Böhlen (University of Zurich)

关键词：时间序列，数据流， join processing

12. (Demo)UniTS: A Universal Time Series Analysis Framework Powered by Self-supervised Representation Learning

链接：https://dl.acm.org/doi/abs/10.1145/3626246.3654733

作者：Zhiyu Liang (Harbin Institute of Technology); Chen Liang (Harbin Institute of technology); Zheng Liang (Harbin Institute of Technology); Hongzhi Wang (Harbin Institute of Technology); Bo Zheng (CnosDB Inc.)

关键词：时间序列分析，自监督学习，预训练

代码：https://github.com/LceOmlet/UniTS