Comparing vessel trajectories using geographical domain knowledge and alignments

Authors
Publication date 2010
Host editors
  • W. Fan
  • W. Hsu
  • G.I. Webb
  • B. Liu
  • C. Zhang
  • D. Gunopulos
  • X. Wu
Book title Proceedings of the 10th IEEE International Conference on Data Mining Workshops (ICDMW 2010), Sydney, Australia
ISBN
  • 9781424492442
Event 10th IEEE International Conference on Data Mining Workshops (ICDMW 2010), Sydney, Australia
Pages (from-to) 209-216
Publisher Los Alamitos, CA: IEEE Computer Society
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
This paper presents a similarity measure that combines low-level trajectory information with geographical domain knowledge to compare vessel trajectories. The similarity measure is largely based on alignment techniques. In a clustering experiment we show how the measure can be used to discover behavior concepts in vessel trajectory data that are dependent both on the low-level trajectories and the domain knowledge. We also apply this measure in a classification task to predict the type of vessel. In this task the combined measure performs better than similarities based on domain knowledge or low-level information alone.
Document type Conference contribution
Language English
Published at https://doi.org/10.1109/ICDMW.2010.123
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