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

Yang, Jianhua, and Lee, Ickjai (2006) Hybrid O(n√n) clustering for sequential web usage mining. In: AI 2006: Advances in Artificial Intelligence (4304), pp. 1022-1026. From: 19th Australian Joint Conference on Artificial Intelligence, 4-8 December 2006, Hobart, TAS, Australia.

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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.

Item ID: 4352
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: clustering; web usage mining; sequence mining
ISBN: 978-3-540-49787-5
ISSN: 1611-3349
Date Deposited: 18 Nov 2009 03:38
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890299 Computer Software and Services not elsewhere classified @ 60%
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