• DocumentCode
    2191252
  • Title

    Comparing Vessel Trajectories Using Geographical Domain Knowledge and Alignments

  • Author

    De Vries, Gerben K D ; Van Hage, Willem Robert ; Van Someren, Maarten

  • Author_Institution
    Inf. Inst., Univ. of Amsterdam, Amsterdam, Netherlands
  • fYear
    2010
  • fDate
    13-13 Dec. 2010
  • Firstpage
    209
  • Lastpage
    216
  • 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.
  • Keywords
    data mining; marine engineering; pattern classification; pattern clustering; ships; alignment technique; behavior discovery; classification task; clustering experiment; geographical domain alignments; geographical domain knowledge; low-level trajectory information; similarity measure; vessel trajectory data; vessel type prediction; geographical domain knowledge; trajectory alignments; trajectory clustering; vessel trajectories;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining Workshops (ICDMW), 2010 IEEE International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-1-4244-9244-2
  • Electronic_ISBN
    978-0-7695-4257-7
  • Type

    conf

  • DOI
    10.1109/ICDMW.2010.123
  • Filename
    5693302