Modified Agglomerative Clustering for Web Users Navigation Behavior

Clustering is the task of finding natural partitioning within a data set such that data items within the same group are more similar than those within different groups. At present all available clustering techniques for web usage mining are based upon usage patterns derived from user’s page preferences. To improve the efficiency of usage pattern, the similarities in user’s access behavior based on time locality of user’s navigational acts are used. The tuning algorithm defines cluster that show similar visiting behavior at the same time period and users page preferences by varying the priority given to the time visit.