Discovering Co-Location Patterns in Datasets with Extended Spatial Objects
- Aibek Adilmagambetov
- Osmar R. Zaiane, University of Alberta (Database)
- Alvaro R. Osornio-Vargas
Co-location mining is one of the tasks of spatial data mining, which focuses on the detection of the sets of spatial features frequently located in close proximity of each other. Previous work is based on transaction-free apriori-like algorithms. The approach we propose is based on a grid transactionization of geographic space and designed to mine datasets with extended spatial objects. A statistical test is used instead of global thresholds to detect significant co-location patterns.
Citation
A. Adilmagambetov, O. Zaiane, A. Osornio-Vargas. "Discovering Co-Location Patterns in Datasets with Extended Spatial Objects". International Conference on Big Data Analytics and Knowledge Discovery (DAWAK), (ed: Ladjel Bellatreche, Mukesh K. Mohania), pp 84-96, August 2013.| Keywords: | |
| Category: | In Conference |
| Web Links: | Springer Link |
BibTeX
@incollection{Adilmagambetov+al:DAWAK13,
author = {Aibek Adilmagambetov and Osmar R. Zaiane and Alvaro R.
Osornio-Vargas},
title = {Discovering Co-Location Patterns in Datasets with Extended Spatial
Objects},
Editor = {Ladjel Bellatreche, Mukesh K. Mohania},
Pages = {84-96},
booktitle = {International Conference on Big Data Analytics and Knowledge
Discovery (DAWAK)},
year = 2013,
}Last Updated: January 13, 2020Submitted by Sabina P
