A GENERAL INCREMENTAL HIERARCHICAL CLUSTERING METHOD
Data mining, i.e., clustering analysis, is a challenging task due to the huge amounts of data. In this paper, we propose a general incremental hierarchical clustering method dealing with incremental data sets in data warehouse environment for data mining to reduce the cost further. As an example, we put forward ICHAMELEON, the improvement of CHAMELEON, which is a hierarchical clustering method, and demonstrate that ICHAMELEON is highly efficient in terms of time complexity. Experimental results on very large data sets are presented which show the efficiency of ICHAMELEON compared with CHAMELEON.
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