Abstract
In the paper, a new kind of clustering algorithm called GCARD is proposed. Besides the merits of Density-Based clustering analysis and its efficiency, GCARD can capture the shape and extent of clusters by core grid units, and then analyze data based on the references of core grid units. We present a method of RGUBR to improve the accuracy of grid clustering method, so it can be used to discover information in very large databases.
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Yong-Sheng, X., Wei, Z., Juan, W., Zong-Yi, H., Tian-Qi, K., Xin-Zheng, X. (2005). A Grid Clustering Algorithm Based on Reference and Density. In: Grumbach, S., Sui, L., Vianu, V. (eds) Advances in Computer Science – ASIAN 2005. Data Management on the Web. ASIAN 2005. Lecture Notes in Computer Science, vol 3818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596370_34
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DOI: https://doi.org/10.1007/11596370_34
Publisher Name: Springer, Berlin, Heidelberg
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