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. AI 2006: Advances in Artificial Intelligence . 19th Australian Joint Conference on Artificial Intelligence , 4-8 December 2006, Hobart, TAS, Australia , pp. 1022-1026.
|PDF (Published Version) - Repository staff only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader|
View at Publisher Website: http://dx.doi.org/10.1007/11941439_115
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 Type:||Conference Item (Refereed Research Paper - E1)|
|Keywords:||clustering; web usage mining; sequence mining|
|SEO Codes:||89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890299 Computer Software and Services not elsewhere classified @ 60%|
89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 40%
|Deposited On:||18 Nov 2009 13:38|
|Last Modified:||13 Feb 2011 06:16|
Last 12 Months: 0
Repository Staff Only: item control page