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Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on (2011)
Lyon, France
Aug. 22, 2011 to Aug. 27, 2011
ISBN: 978-0-7695-4513-4
pp: 479-482
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.
Geo-tree, clustering, visualization, geographic data

P. Cheng, C. Lu and C. Chen, "Clustering and Visualizing Geographic Data Using Geo-tree," 2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies(WI-IAT), Lyon, 2011, pp. 479-482.
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