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Improved CURE algorithm and application of clustering for large-scale data

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2 Author(s)
Shao Xiufeng ; Dept. of Soft & Inf. Manage., BeiJing City Univ., Beijing, China ; Cheng Wei

Aiming at the classification problem of large-scale document information, a large-scale data clustering algorithm based on improved CURE algorithm is proposed. By clustering the data partition and the initial class of after partition, data tracking, the large-scale data hierarchical clustering and sample classification is achieved, that better solved the balance of clustering quality and clustering effectiveness. Taking the actual document processing of Large-scale network data, the experiment results show that the algorithm is efficient.

Published in:

IT in Medicine and Education (ITME), 2011 International Symposium on  (Volume:1 )

Date of Conference:

9-11 Dec. 2011