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Hybrid clustering with application to Web mining

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1 Author(s)
Yue Xu ; Sch. of Software Eng. & Data Commun., Queensland Univ. of Technol., Brisbane, Qld., Australia

Clustering algorithms fall into two categories: hierarchical clustering and partitional clustering. For hierarchical algorithms, they are static in the sense that they never undo what was done previously, which means that, objects which are committed to a cluster in the early stages, cannot move to another cluster. Partitional clustering does not suffer from this problem, but requires a pre-specified number for the output clusters. This paper presents a hybrid clustering method that combines the advantages of hierarchical clustering and partitional clustering techniques. The proposed hybrid algorithm does not require a number for the output clusters prior to the clustering and the clusters can be rearranged according to a quality measurement. In the present paper, we apply this method to Web page clustering and provide necessary experimental results.

Published in:

Active Media Technology, 2005. (AMT 2005). Proceedings of the 2005 International Conference on

Date of Conference:

19-21 May 2005