Abstract
In this paper, we combine sampUng technique with DBSCAN algorithm to cluster large spatial databases, two sampling-based DBSCAN (SDBSCAN) algorithms are developed. One algorithm introduces sampling technique inside DBSCAN; and the other uses sampling procedure outside DBSCAN. Experimental results demonstrate that our algorithms are effective and efficient in clustering large-scale spatial databases.
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CITATION STYLE
Zhou, S., Zhou, A., Cao, J., Wen, J., Fan, Y., & Hu, Y. (2000). Combining sampling technique with dbscan algorithm for clustering large spatial databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1805, pp. 169–172). Springer Verlag. https://doi.org/10.1007/3-540-45571-x_20
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