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本文总结了SIGMOD 2024有关时间序列#xff08;time series#xff09;,包括时序数据库#xff0c;查询优化等内容。以及时空数据#xff08;spatial-temporal data#xff09;的…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。 【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
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ETAOD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
