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2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology
Clustering and Visualizing Geographic Data Using Geo-tree
Lyon, France
August 22-August 27
ISBN: 978-0-7695-4513-4
| ASCII Text | x | ||
| Che-An Lu, Chin-Hui Chen, Pu-Jen Cheng, "Clustering and Visualizing Geographic Data Using Geo-tree," Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on, vol. 1, pp. 479-482, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2011. | |||
| BibTex | x | ||
| @article{ 10.1109/WI-IAT.2011.171, author = {Che-An Lu and Chin-Hui Chen and Pu-Jen Cheng}, title = {Clustering and Visualizing Geographic Data Using Geo-tree}, journal ={Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on}, volume = {1}, year = {2011}, isbn = {978-0-7695-4513-4}, pages = {479-482}, doi = {http://doi.ieeecomputersociety.org/10.1109/WI-IAT.2011.171}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on TI - Clustering and Visualizing Geographic Data Using Geo-tree SN - 978-0-7695-4513-4 SP479 EP482 A1 - Che-An Lu, A1 - Chin-Hui Chen, A1 - Pu-Jen Cheng, PY - 2011 KW - Geo-tree KW - clustering KW - visualization KW - geographic data VL - 1 JA - Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on ER - | |||
Plotting lots of geographical data points usually clutters up a map. In this paper, we propose an approach to provide a summary view of geographical data by efficiently clustering. We present a novel data structure, called Geo-tree, which is extended from quad tree, and then develop two algorithms, which use Geo-tree to cluster geographic data and visualize the clusters with a heat map-like representation. The experimental results show that our approach is very efficient in a large scale, compared to K-means and HAC, and the clustering results are comparable to theirs.
Index Terms:
Geo-tree, clustering, visualization, geographic data
Citation:
Che-An Lu, Chin-Hui Chen, Pu-Jen Cheng, "Clustering and Visualizing Geographic Data Using Geo-tree," wi-iat, vol. 1, pp.479-482, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2011
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