|Title:||Mining candidate causal relationships in movement patterns|
|Authors :||Bleisch, Susanne|
|Published in :||International Journal of Geographical Information Science|
|Publisher / Ed. Institution :||Taylor & Francis|
|License (according to publishing contract) :||Licence according to publishing contract|
|Type of review:||Peer review (Publication)|
|Subjects :||Sequence mining; Data mining|
|Subject (DDC) :||005: Computer programming, programs and data|
|Abstract:||In many applications, the environmental context for and drivers of movement patterns are just as important as the patterns themselves. This article adapts standard data mining techniques, combined with a foundational ontology of causation, with the objective of helping domain experts identify candidate causal relationships between movement patterns and their environmental context. In addition to data about movement and its dynamic environmental context, our approach requires as input definitions of the states and events of interest. The technique outputs causal and causal-like relationships of potential interest, along with associated measures of support and confidence. As a validation of our approach, the analysis is applied to real data about fish movement in the Murray River in Australia. The results demonstrate that the technique is capable of identifying statistically significant patterns of movement indicative of causal and causal-like relationships.|
|Departement:||Life Sciences and Facility Management|
|Organisational Unit:||Institute of Natural Resource Sciences (IUNR)|
|Publication type:||Article in scientific Journal|
|Appears in Collections:||Publikationen Life Sciences und Facility Management|
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