Hybrid O(n√n) clustering for sequential web usage mining

Conference Publication ResearchOnline@JCU

Yang, Jianhua;Lee, Ickjai

Abstract

We propose a natural neighbor inspired O(n√n) hybrid clustering algorithm that combines medoid-based partitioning and agglomerative hierarchial clustering. This algorithm works efficiently by inheriting partitioning clustering strategy and operates effectively by following hierarchial clustering. More importantly, the algorithm is designed by taking into account the specific features of sequential data modeled in metric space. Experimental results demonstrate the virtue of our approach.

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4304

ISBN/ISSN

1611-3349

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Location

Hobart, TAS, Australia

Publisher

Springer

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Publisher Location

Berlin, Germany

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DOI

10.1007/11941439_115