Abstract
In this article, we present an algorithm based on genetic algorithm (GA) and R-tree structure to solve a clustering task in spatial data mining. The algorithm is applied to find a cluster for a new spatial object. Spatial objects that represent for each cluster computed dynamically and quickly according to a clustering object in the clustering process. This improves the speed and accuracy of the algorithm. The experimental results show that our algorithm yields the same result as any other algorithm and is accommodated to the clustering task in spatial data warehouses.
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Vinh, N.N., Le, B. (2012). Incremental Spatial Clustering in Data Mining Using Genetic Algorithm and R-Tree. In: Bui, L.T., Ong, Y.S., Hoai, N.X., Ishibuchi, H., Suganthan, P.N. (eds) Simulated Evolution and Learning. SEAL 2012. Lecture Notes in Computer Science, vol 7673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34859-4_27
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DOI: https://doi.org/10.1007/978-3-642-34859-4_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34858-7
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