Abstract
Spatial clustering is an active research area in spatial data mining with various methods reported. In this paper, we compare two density-based methods, DBSCAN and DBRS. First, we briefly describe the methods and then compare them from a theoretical view. Finally, we give an empirical comparison of the algorithms.
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Wang, X., Hamilton, H.J. (2005). A Comparative Study of Two Density-Based Spatial Clustering Algorithms for Very Large Datasets. In: Kégl, B., Lapalme, G. (eds) Advances in Artificial Intelligence. Canadian AI 2005. Lecture Notes in Computer Science(), vol 3501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424918_14
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DOI: https://doi.org/10.1007/11424918_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25864-3
Online ISBN: 978-3-540-31952-8
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