Abstract
In this paper a new approach to hierarchical clustering of huge data sets is presented, which is based on a Grid-Clustering approach [Sch96]. It uses a multi-dimensional grid data structure, the BANG structure, to organize the value space surrounding the pattern values. The patterns are grouped into blocks and clustered with respect to the blocks by a topological neighbor search algorithm.
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References
A.J. Broder. Strategies for efficient incremental nearest neighbor search. Pattern Recognition, 23:171–178, 1990.
R. Dubes and gA.K. Jain. Clustering methodologies in exploratory data analysis, volume 19, pages 113–228. Academia Press, 1980.
M.W. Freestone. The bang file: A new kind of grid file. In Proc. Special Interest Group on Management of Data, pages 260–269. ACM, May 1987.
E. Schikuta. Grid clustering: An efficient hierarchical clustering method for very large data sets. In Proc. 13th Int. Conf. on Pattern Recognition, volume 2, pages 101–105. IEEE Computer Society, 1996.
Erich Schikuta and Martin Erhart. The bang-clustering system: Grid-based data analysis. In X Liu, P. Cohen, and M. Berthold, editors, Advances in Intelligent Data Analysis. reasoning about Data, Proc. Second International Sym posium IDA-97, volume 1280 of LNCS, London, UK, August 1997. Springer-Verlag.
C.S. Warnekar and G. Krishna. A heuristic clustering algorithm using union of overlapping pattern-cells. Pattern Recognition, 11:85–93, 1979.
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© 1998 Springer-Verlag Berlin Heidelberg
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Schikuta, E., Erhart, M. (1998). BANG-Clustering: A novel grid-clustering algorithm for huge data sets. In: Amin, A., Dori, D., Pudil, P., Freeman, H. (eds) Advances in Pattern Recognition. SSPR /SPR 1998. Lecture Notes in Computer Science, vol 1451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033313
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DOI: https://doi.org/10.1007/BFb0033313
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