期刊名称：The Online Journal of Applied Knowledge Management
印刷版ISSN：2325-4688
出版年度：2014
卷号：2
期号：1
页码：82-92
出版社：The International Institute for Applied Knowledge Management
摘要：The immense volume of web usage data that exists on web servers can be mined to generate association rules that contain the information about website visitor interests, which can then be utilized for enhancing the website effectiveness, or increasing the profit in e-commerce applications. One of the problems in web usage association rule mining is the generation of too many rules with extremely high statistical interestingness measures, which are not necessarily interesting to the domain expert. In this paper, we propose a modified version of added value as an interestingness measure for particular groups of association rules consisting of web pages that occur as sub -items of the web site commo n menus. Our real life data experiments show that the modified added value outperforms added value, resembling the domain expert defined interestingness more closely
关键词：web usage mining; association rules; interestingness measures; website menu
