Title :
Maritime traffic data mining using R
Author :
Hadzagic, M. ; St-Hilaire, Marie-Odette ; Webb, Sean ; Shahbazian, Elisa
Author_Institution :
OODA Technol. Inc., Univ. de Montreal, Montreal, QC, Canada
Abstract :
Human operators trying to establish individual or collective maritime situational awareness often find themselves overloaded by huge amounts of information obtained from multiple and possibly dissimilar sources. This paper explores potential use of open source data mining tools, in particular R software, to enable discovery of maritime traffic patterns. It also presents an assessment of R software as a data mining tool using spatio-temporal maritime traffic data such as from the Automatic Identification System (AIS), and includes scenarios of potential interest to the maritime environment.
Keywords :
data mining; marine engineering; public domain software; AIS; R software; automatic identification system; human operators; maritime environment; maritime situational awareness; maritime traffic data mining; maritime traffic patterns discovery; open source data mining tools; spatio-temporal maritime traffic data; Algorithm design and analysis; Association rules; Clustering algorithms; Databases; Marine vehicles; Ports (Computers); AIS; R; data mining; maritime traffic data;
Conference_Titel :
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-605-86311-1-3