Mining class association rules in Web log data.
Yuanchun Jiang · Computer Engineering and Applications Journal · 2007
Web users classification is an important issue in Web access pattern mining research area.A method of classifying Web users using associative classification technique is proposed.First the train transaction dataset is obtained by pre-processing Web log file,then the class association rules is discovered from the dataset,finally a classifier based on the discovered rules set is built.By doing so,we realize users classification according to their access history.