Paper Info
Title
A new method for measuring topological structure similarity between complex trajectories
Abstract
We proposed a new framework to measure the similarity of topological structure between complex trajectories. A complex trajectory is first represented by a graph structure with nodes and edges. Secondly, we developed a Comprehensive Structure Matching (CSM) algorithm to identify all common structures between the complex trajectories of interest. Thirdly, we used the Jaccard similarity coefficient to evaluate the similarity between complex trajectories. We used synthetic data to evaluate the CSM method by comparing the VF2 and the exact graph edit distance (EGED) algorithms. Results show that the CSM algorithm outperforms the EGED in terms of the computation efficiency. The CSM is more comprehensive than the VF2 algorithm as it further considers the partial isomorphism. We used the CSM algorithm to examine the 1993 to 2012 complex trajectories of anticyclonic eddies in the South China Sea (SCS). The CSM successfully found the complex trajectories that are similar to a thoroughly-studied ACE3 trajectory in the SCS. From the similar trajectories, we identified a dominant migrating path of the eddies in the northern SCS and some new trajectories that propagated across the 18°N parallel, which were not reported before. These findings help us better understand the behaviors and the evolution of the mesoscale eddies in the SCS.
Year
DOI
Venue
2019
10.1109/tkde.2018.2872523
IEEE Transactions on Knowledge and Data Engineering
Keywords
Field
DocType
Trajectory,Sea measurements,Oceans,Sun,Computational efficiency,Spatial databases,Data mining
Topology,Structure matching,Graph,Computer science,Mesoscale meteorology,Isomorphism,Jaccard index,Trajectory,Computation,Graph edit distance
Journal
Volume
Issue
ISSN
31
10
1041-4347
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Hui Meng Wang101.35
Yunyan Du23411.76
jiawei yi310.69
Y. Sun41249.12
Fuyuan Liang5174.35