dc.contributor.author | Galton, A | |
dc.contributor.author | Bleisch, S | |
dc.contributor.author | Duckham, M | |
dc.contributor.author | Laube, P | |
dc.contributor.author | Lyon, J | |
dc.date.accessioned | 2016-01-28T10:53:38Z | |
dc.date.issued | 2013-10-01 | |
dc.description.abstract | In many applications, the environmental context for, and drivers of movement patterns are just as important as the patterns themselves. This paper 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 the technique is capable of identifying statistically significant patterns of movement indicative of causal and causal-like relationships. 1365-8816 | en_GB |
dc.description.sponsorship | Australian Research Council Discovery Project | en_GB |
dc.identifier.citation | International Journal of Geographical Information Science, 2014, Volume 28, Issue 2, p.363-382 | en_GB |
dc.identifier.doi | 10.1080/13658816.2013.841167 | |
dc.identifier.grantnumber | DP120100072 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/19398 | |
dc.language.iso | en | en_GB |
dc.publisher | Taylor & Francis | en_GB |
dc.relation.url | http://www.tandfonline.com/doi/abs/10.1080/13658816.2013.841167 | en_GB |
dc.rights | © 2013 Taylor & Francis | en_GB |
dc.subject | movement patterns | en_GB |
dc.subject | context-aware movement analysis | en_GB |
dc.subject | sequence mining | en_GB |
dc.subject | causation | en_GB |
dc.subject | geosensor networks | en_GB |
dc.subject | environmental monitoring | en_GB |
dc.title | Mining candidate causal relationships in movement patterns | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2016-01-28T10:53:38Z | |
dc.identifier.issn | 1365-8816 | |
pubs.declined | 2016-03-30T16:01:08.338+0100 | |
pubs.deleted | 2016-03-30T16:01:08.576+0100 | |
dc.description | This is an Accepted Manuscript of an article published by Taylor & Francis in the International Journal of Geographical Information Science on 01 October 2013, available online: http://wwww.tandfonline.com/10.1080/13658816.2013.841167 | en_GB |
dc.identifier.journal | International Journal of Geographical Information Science | en_GB |