Web page clustering using a self-organizing map of user navigation patterns

被引:72
作者
Smith, KA [1 ]
Ng, A [1 ]
机构
[1] Monash Univ, Sch Business Syst, Clayton, Vic, Australia
关键词
data mining; self-organizing maps; clustering; web usage mining;
D O I
10.1016/S0167-9236(02)00109-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The continuous growth in the size and use of the Internet is creating difficulties in the search for information. A sophisticated method to organize the layout of the information and assist user navigation is therefore particularly important. In this paper, we evaluate the feasibility of using a self-organizing map (SOM) to mine web log data and provide a visual tool to assist user navigation. We have developed LOGSOM, a system that utilizes Kohonen's self-organizing map to organize web pages into a two-dimensional map. The organization of the web pages is based solely on the users' navigation behavior, rather than the content of the web pages. The resulting map not only provides a meaningful navigation tool (for web users) that is easily incorporated with web browsers, but also serves as a visual analysis tool for webmasters to better understand the characteristics and navigation behaviors of web users visiting their pages. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:245 / 256
页数:12
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