Mining generalized fuzzy association rules from Web logs

Discovery the association between web pages is an important task as the rapid growth of web data. This article uses the fuzzy method to discover generalized fuzzy association rules among theWeb pages fromWeb logs. In the paper, whether a web page is visited or not and time duration on it are considered two important factors to reflect users´ interest and preference. Numerical time duration is fuzzified into a corresponding fuzzy variable with membership values. The mined rule has the form as page(fuzzy duration) → page(fuzzy duration). These rules can reflect association among Web pages with fuzzy duration. By the analysis of the example, the generalized fuzzy association rules can be effectively mined in a sustainable computational period from Web user access patterns in Web logs.