Abstract
Spatial information processing is an active research field in database technology. Spatial databases store information about the position of individual objects in space [6]. Our current research is focused on providing an efficient caching structure for a telemetric data warehouse. We perform spatial objects clustering when creating levels of the structure. For this purpose we employ a density-based clustering algorithm. The algorithm requires an user-defined parameter Eps. As we cannot get the Eps from user for every level of the structure we propose a heuristic approach for calculating the Eps parameter. Automatic Eps Calculation (AEC) algorithm analyzes pairs of points defining two quantities: distance between the points and density of the stripe between the points. In this paper we describe in detail the algorithm operation and interpretation of the results. The AEC algorithm was implemented in one centralized and two distributed versions. Included test results present the algorithm correctness and efficiency against various datasets.
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Barclay, T., Slutz, D.R., Gray, J.: TerraServer: A Spatial Data Warehouse. In: Proc. ACM SIGMOD 2000, pp. 307–318 (June 2000)
http://www.lsgi.polyu.edu.hk/sTAFF/zl.li/vol_2_2/02_chen.pdf
Ester, M., Kriegel, H.-P., Sander, J., Wimmer, M.: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In: Proc. of 2nd International Conference on Knowledge Discovery and Data Mining (1996)
Gorawski, M., Malczok, R.: On Efficient Storing and Processing of Long Aggregate Lists. DaWaK, Copenhagen, Denmark (2005)
Papadias, D., Kalnis, P., Zhang, J., Tao, Y.: Effcient OLAP Operations in Spatial Data Warehouses. LNCS. Springer, Heidelberg (2001)
Wang, X., Hamilton, H.J.: DBRS: A Density-Based Spatial Clustering Method with Random Sampling. In: Proceedings of the 7th PAKDD, Seoul, Korea (2003)
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Gorawski, M., Malczok, R. (2006). AEC Algorithm: A Heuristic Approach to Calculating Density-Based Clustering Eps Parameter. In: Yakhno, T., Neuhold, E.J. (eds) Advances in Information Systems. ADVIS 2006. Lecture Notes in Computer Science, vol 4243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11890393_10
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DOI: https://doi.org/10.1007/11890393_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46291-0
Online ISBN: 978-3-540-46292-7
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