International Journal of Computer Applications
Analysis of Web logs is one of the important challenges to provide Web intelligent services. Association rule mining algorithms are used widely to track users' web behavior. Due to large amount of data many times the rules formed by these algorithms are very long and redundant. Recently constraint based mining approaches have received attention to deal with these big and redundant association rules. In this paper, the authors discuss the constraint based web mining approach used to reduce the size of association rules derived from Web log.