Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40129
Title: Efficient yet accurate clustering
Authors: Dash, M.
Tan, K.L. 
Liu, H.
Issue Date: 2001
Source: Dash, M.,Tan, K.L.,Liu, H. (2001). Efficient yet accurate clustering. Proceedings - IEEE International Conference on Data Mining, ICDM : 99-106. ScholarBank@NUS Repository.
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 eficiently, 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. © 2001 IEEE.
Source Title: Proceedings - IEEE International Conference on Data Mining, ICDM
URI: http://scholarbank.nus.edu.sg/handle/10635/40129
ISBN: 0769511198
ISSN: 15504786
Appears in Collections:Staff Publications

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