Mining Web Usage Using FRS

被引:0
|
作者
Omar, Rosli [1 ]
Abdullah, Zainatul Shima [1 ]
机构
[1] Int Islamic Univ Malaysia, Kulliyyah Informat & Commun Technol, Kuala Lumpur, Malaysia
关键词
web mining; web usage mining; data mining; sequential pattern; machine learning;
D O I
10.1109/ICT4M.2018.00062
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Web Usage Mining (WUM) is the application of data mining methods in extracting potentially useful information from web usage data. Its application includes improving website design, personalised service, target marketing etc. Among the outstanding research issues in WUM include inefficiency in mining large weblogs, extracted patterns that are not representative of actual user behavior, and mining results which are too general, uninteresting and lack insights. This paper attempts to address the above problems using a method of mining that captures user traversing activities more effectively based on the notion of regularity. A mining algorithm is introduced using the approach of vertical database. The experiments suggest that the method is efficient, scalable, and able to address confusion caused by large number of extracted patterns.
引用
收藏
页码:301 / 304
页数:4
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