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An effective method clustering web transactions using attribute information, and the relationship information between web transactions is proposed in the, paper. At first, each web transaction is transformed into a fuzzy vector with, the same length. Each element of a vector is a fuzzy variable representing the, time duration on a web page. Then we bring in a way to transform the relationship, between...
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...
Web log mining is the application of data mining techniques to Web log data repositories, in which clustering analysis is one of important Web usage mining techniques. Recently various clustering approaches have been developed for Web pages and customer segments clustering. However, most of them take user access frequency or Web page time duration as measurement of user navigation interest without...
The interest of web users can be revealed by the visited web pages and time duration on these web pages during their surfing. In this paper, each web access pattern from web logs is transformed into a fuzzy vector with predetermined dimension, each component being a fuzzy linguistic variable or 0 representing the visited web page and the time duration on this web page. Fuzzy simulation is used to...
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