网站上的动效是用ae做的今日刚刚发生的军事新闻
SIGMOD2024于6月9号-6月14号正在智利圣地亚戈举行（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。
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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
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
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
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
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
