scholarly journals A survey of temporal knowledge discovery paradigms and methods

2002 ◽  
Vol 14 (4) ◽  
pp. 750-767 ◽  
Author(s):  
J.F. Roddick ◽  
M. Spiliopoulou
Keyword(s):  
Knowledge Discovery ◽  
Temporal Knowledge Discovery

Vessel Spatio-temporal Knowledge Discovery with AIS Trajectories Using Co-clustering

2017 ◽  
Vol 70 (6) ◽  
pp. 1383-1400 ◽  
Author(s):  
Jiang Wang ◽  
Cheng Zhu ◽  
Yun Zhou ◽  
Weiming Zhang
Keyword(s):  
Knowledge Discovery ◽  
Situational Awareness ◽  
Automatic Identification ◽  
Identification System ◽  
Mobility Patterns ◽  
Multidimensional Arrays ◽  
Temporal Knowledge Discovery ◽  
Spatio Temporal ◽  
Vessel Motion ◽  
Occurrence Patterns

Large volumes of data collected by the Automatic Identification System (AIS) provide opportunities for studying both single vessel motion behaviours and collective mobility patterns on the sea. Understanding these behaviours or patterns is of great importance to maritime situational awareness applications. In this paper, we leveraged AIS trajectories to discover vessel spatio-temporal co-occurrence patterns, which distinguish vessel behaviours simultaneously in terms of space, time and other dimensions (such as ship type, speed, width etc.). To this end, available AIS data were processed to generate spatio-temporal matrices and spatio-temporal tensors (i.e., multidimensional arrays). We then imposed a sparse bilinear decomposition on the matrices and a sparse multi-linear decomposition on the tensors. Experimental results on a real-world dataset demonstrated the effectiveness of this methodology, with which we show the existence of connection among regions, time, and vessel attributes.

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