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Proceedings 2001 IEEE International Conference on Data Mining (2001)
San Jose, California
Nov. 29, 2001 to Dec. 2, 2001
ISBN: 0-7695-1119-8
pp: 99
ABSTRACT
In this paper we show that most hierarchical agglomerative clustering (HAC)algorithms follow a 90-10 rule where roughly 90%iterations from the beginning merge cluster pairs with dissimilarity less than 10%of the maximum dissimilarity. We propose two algorithms - 2-phase and nested - based on partially overlapping partitioning (POP).To handle high-dimensional data efficiently, we propose a tree structure particularly suitable for POP. Extensive experiments show that the proposed algorithms reduce the time and memory requirement of existing HAC algorithms significantly without compromising in accuracy.
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CITATION

M. Dash, H. Liu and K. L. Tan, "Efficient Yet Accurate Clustering," Proceedings 2001 IEEE International Conference on Data Mining(ICDM), San Jose, California, 2001, pp. 99.
doi:10.1109/ICDM.2001.989506
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