Application Oriented Web Usage Mining with Customized Web Log Preprocessing & Frequent Pattern Tree

Web Usage Mining discovers interesting patterns in accesses to various Web pages within the Web space associated with a particular server. The Web Usage Mining architecture divides the process into two main partsthe first part includes preprocessing, transaction identification, and data integration components. The second part includes the largely domain independent application of generic data mining and pattern matching. This paper contains an efficient improved iterative FP Tree algorithm for generating frequent access patterns from the access paths of the users. The frequent access patterns are generated by backward tree traversals. This operation will take less time compare to the existing algorithms. Paper also composed of customized web log preprocessing for mined in different applications.