A ROUGH SET APPROACH FOR WEB USAGE MINING

被引：0
|
作者：
Salem, Abdel-Badeeh M. [1 ]
Arafat, Shaimaa [1 ]
Khalifa, Wael H. [1 ]
机构：
[1] Ain Shams Univ, Fac Comp & Informat Sci, Cairo, Egypt
来源：
MENDEL 2008 | 2008年
关键词：
Machine Learning; Rough Sets; Web Usage Mining; Web Log Mining; Association Rules;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Web Usage Mining is a branch of web mining concerned with the extraction of interesting patterns logs generated from user's navigation across web sites. The main difference between web mining and data mining is nature of data mined. The web mining data is semi-structured and in a pretty large amounts. The logs generated by web servers provide a good example of the type of data used in web mining. A rough set is a formal approximation of a crisp set, which give the lower and the upper approximation of the original set. In this paper we present an approach to extract association rules from web usage data using rough sets. We describe how we convert the web usage data into a decision table and then use rough set approximation to generate association rules.
引用
收藏
页码：281 / 286
页数：6
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