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Proceedings Paper

Obstacle constraint spatial clustering
Author(s): Yuan-ni Wang; Fu-ling Bian
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Paper Abstract

Constraints in the real world must be seriously considered in the process of spatial clustering. In this paper we study the spatial clustering issue in the presence of obstacles. The cluster algorithm is based on the K-medoid algorithm, and an improved algorithm Guo Tao is introduced to obtain the distance of spatial objects in the presence of obstacles. It is more efficient for small and medium-sized data through theoretical analysis. The experiments results prove that the algorithm is feasible.

Paper Details

Date Published: 14 October 2009
PDF: 7 pages
Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 749217 (14 October 2009); doi: 10.1117/12.837648
Show Author Affiliations
Yuan-ni Wang, Wuhan Univ. (China)
Computer College of China Univ. of Geosciences (China)
Fu-ling Bian, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 7492:
International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining
Yaolin Liu; Xinming Tang, Editor(s)

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