Multi-level association rules and directed graphs for spatial data analysis
作者：
Highlights：
• We propose a new methodology for spatial–temporal data mining of Lagrangian trajectories.
• We use spatial–temporal association rules and multi-level directed graphs.
• We develop a new, highly efficient algorithm for finding cycles and paths in multi-level directed graphs.
• We apply our methodology to the numerical model Mediterranean Ocean Forecasting System.
• We present the results; some confirm existing oceanographic expertise, while others represent new, previously unknown knowledge.
摘要
Highlights•We propose a new methodology for spatial–temporal data mining of Lagrangian trajectories.•We use spatial–temporal association rules and multi-level directed graphs.•We develop a new, highly efficient algorithm for finding cycles and paths in multi-level directed graphs.•We apply our methodology to the numerical model Mediterranean Ocean Forecasting System.•We present the results; some confirm existing oceanographic expertise, while others represent new, previously unknown knowledge.
论文关键词：Spatial data mining,Lagrangian analysis,Spatial–temporal association rules,Multi-level directed graphs,Oceanography
论文评审过程：Available online 13 March 2013.
论文官网地址：https://doi.org/10.1016/j.eswa.2013.03.004
